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SEC v. Consensys Software Inc. Court Filing, retrieved on June 28, 2024, is part of HackerNoon’s Legal PDF Series. You can jump to any part in this filing here. This part is 20 of 26. C. Consensys—through MetaMask Staking—Offers and Sells the Lido and Rocket Pool Investment Contracts. i. Through MetaMask Staking, Consensys Promotes, Offers, and Sells the Lido and Rocket Pool Investment Contracts To Its Users. 286. On January 13, 2023, Consensys publicly announced the release of a program called MetaMask Staking. 287. Consensys created MetaMask Staking to offer and sell the Lido and Rocket Pool staking program investment contracts to investors. 288. The January 13 announcement stated: “MetaMask Staking allows you to engage in liquid staking with two prominent providers, Lido and Rocket Pool, where by you can deposit your ETH and receive a token representing the value of your stake in return.” 289. It called MetaMask Staking “an easy and convenient way to stake ETH.” 290. On January 13, 2023, Consensys posted on the MetaMask Twitter account: “We are extremely happy to announce that you can now stake ETH with Lido or Rocket Pool through the [MetaMask] Portfolio Dapp.” This post included an image advertising “5.22% rewards” with Lido and “4.59% rewards” with Rocket Pool—highlighting the former as the “Highest rewards.” 291. On May 16, 2023, Consensys posted on the MetaMask Twitter account: “[U]sers can now stake and withdraw ETH directly from our liquid staking providers, Rocket Pool and Lido.” And “Get started here,” pointing to a link to the MetaMask portfolio website. 292. In promotional materials, Consensys claimed that MetaMask Staking would make it easier for individual holders of ETH to participate in staking. 293. Specifically, in its January 13, 2023, announcement on its website, Consensys stated: “[S]taking can be a convoluted and complicated process for end-users. MetaMask Staking will offer an easy-to-understand and trusted entry point for users interested in staking. Through this new feature, users can compare the rewards rate, network control, and popularity of different liquid staking providers and choose the one they want to stake with.” ii. Consensys’s MetaMask Staking User Interface. 294. To use MetaMask Staking, investors must have ETH in their MetaMask Wallet. 295. First, from the browser extension or mobile app, the investor clicks on “Stake,” or “Staking.” They are then taken to the MetaMask Portfolio site, where they can then choose “ETH.” 296. At this point, Consensys’s graphical interface presents the investor with two options: Lido and Rocket Pool. 298. If either Lido or Rocket Pool is at or near capacity, Consensys’s MetaMask Staking software disables the ability to stake with that program. 299. In any event, an investor can choose either the Lido or Rocket Pool staking program by clicking “Stake.” 300. On the following screen, an investor can input the number of ETH that they would like to invest in one of the staking program investment contracts and click “review.” 301. At that point, Consensys’s MetaMask Staking software shows the investor a screen with the number of the staking pool tokens they will receive in return, their “estimated rewards,” and the “estimated gas fee.” 302. If the investor wishes to proceed with their request to invest in the staking program investment contract, the investor clicks “confirm.” 303. If MetaMask Staking successfully completes the transaction, the investor will see a screen that says, “Transaction Complete.” iii. Consensys Offers and Sells the Lido and Rocket Pool Investment Contracts To Investors. 304. Accordingly, Consensys offers and sells the Lido and Rocket Pool investment contracts to investors through the MetaMask Staking platform. 305. Consensys makes this process appear simple and easy to non-technical investors, while performing the technical series of actions necessary to transfer the investor’s ETH to Lido or Rocket Pool and transfer stETH or rETH to the investor in return. 306. When the investor clicks “confirm,” this signals the MetaMask Staking software to take the steps necessary to exchange the investor’s ETH for rETH or stETH. Specifically, Consensys has programed MetaMask Staking software to take the steps described below. 307. First, Consensys’s MetaMask Staking software reads the private key associated with the ETH in the investor’s MetaMask Wallet. 308. Second, using this key, the software creates a blockchain transaction and transfers the investor’s ETH from the investor’s MetaMask Wallet into a smart contract called the MetaMask Staking Aggregator Router Smart Contract (the “MM Staking Router Smart Contract”). 309. The MM Staking Router Smart Contract has its own Ethereum blockchain address. 310. The investor has no control over the MM Staking Router Smart Contract. 311. The MM Staking Router Smart Contract address temporarily holds the investor’s ETH. 312. Although Consensys has programmed its MetaMask Staking software so that Consensys can take a fee for each transaction, Consensys currently sets the fee variable at zero (i.e., it does not take a fee at this time). 313. Consensys could, however, change the software at any time to assess a fee, in which case the amount of the fee would be diverted from the MM Staking Router Smart Contract into a blockchain address designated by Consensys. 314. Third, Consensys’s software transfers the investor’s ETH from the MM Staking Router Smart Contract to the Lido or Rocket Pool Proxy smart contract (deployed by Lido and Rocket Pool, respectively). 315. These Proxy smart contracts mint stETH or rETH, respectively, upon receiving a deposit of ETH, and, if the MM Staking Router Smart Contract sends ETH to the Proxy smart contracts, the Proxy smart contracts will transfer newly minted stETH or rETH, respectively, to the MM Staking Router Smart Contract. 316. Fourth, the MM Staking Router Smart Contract transfers the stETH or rETH, as the case may be, to the investor’s MetaMask Wallet. 317. As of March 11, 2024, investors had invested 100,252 ETH in the Lido staking program through MetaMask Staking and 8,375 ETH in the Rocket Pool staking program through MetaMask Staking. 318. As of March 11, 2024, Consensys, through MetaMask Staking, offered and sold the Lido staking program to 32,449 unique blockchain addresses and offered and sold the Rocket Pool staking programs to 2,215 unique blockchain addresses. 319. For its part, Lido embraced MetaMask Staking as a platform through which its staking program would be offered and sold. 320. On January 17, 2023, Lido announced on its blog that “Ethereum staking with Lido is now live on MetaMask! Stake your ETH on MetaMask to earn yield and secure the Ethereum network from the comfort of your wallet.” 321. Moreover, a former Lido employee testified that “in terms of a distribution channel [Consensys’s MetaMask was] a very highly valued target.” 322. Accordingly, by the conduct described above, Consensys offered and sold, and continues to offer and sell, investment contracts for Lido and Rocket Pool, participating directly in the distribution of securities from the issuers—Lido and Rocket Pool—to the investor. Continue Reading Here. About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings.
This court case retrieved on June 28, 2024, storage.courtlistener.com is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. SEC v. Consensys Software Inc. Court Filing, retrieved on June 28, 2024, is part of HackerNoon’s Legal PDF Series. You can jump to any part in this filing here. This part is 20 of 26. SEC v. Consensys Software Inc. Court Filing, retrieved on June 28, 2024, is part of HackerNoon’s Legal PDF Series . You can jump to any part in this filing here . This part is 20 of 26. HackerNoon’s Legal PDF Series here C. Consensys—through MetaMask Staking—Offers and Sells the Lido and Rocket Pool Investment Contracts. i. Through MetaMask Staking, Consensys Promotes, Offers, and Sells the Lido and Rocket Pool Investment Contracts To Its Users. i. Through MetaMask Staking, Consensys Promotes, Offers, and Sells the Lido and Rocket Pool Investment Contracts To Its Users. 286. On January 13, 2023, Consensys publicly announced the release of a program called MetaMask Staking. 287. Consensys created MetaMask Staking to offer and sell the Lido and Rocket Pool staking program investment contracts to investors. 288. The January 13 announcement stated: “MetaMask Staking allows you to engage in liquid staking with two prominent providers, Lido and Rocket Pool, where by you can deposit your ETH and receive a token representing the value of your stake in return.” 289. It called MetaMask Staking “an easy and convenient way to stake ETH.” 290. On January 13, 2023, Consensys posted on the MetaMask Twitter account: “We are extremely happy to announce that you can now stake ETH with Lido or Rocket Pool through the [MetaMask] Portfolio Dapp.” This post included an image advertising “5.22% rewards” with Lido and “4.59% rewards” with Rocket Pool—highlighting the former as the “Highest rewards.” 291. On May 16, 2023, Consensys posted on the MetaMask Twitter account: “[U]sers can now stake and withdraw ETH directly from our liquid staking providers, Rocket Pool and Lido.” And “Get started here,” pointing to a link to the MetaMask portfolio website. 292. In promotional materials, Consensys claimed that MetaMask Staking would make it easier for individual holders of ETH to participate in staking. 293. Specifically, in its January 13, 2023, announcement on its website, Consensys stated: “[S]taking can be a convoluted and complicated process for end-users. MetaMask Staking will offer an easy-to-understand and trusted entry point for users interested in staking. Through this new feature, users can compare the rewards rate, network control, and popularity of different liquid staking providers and choose the one they want to stake with.” ii. Consensys’s MetaMask Staking User Interface. ii. Consensys’s MetaMask Staking User Interface. 294. To use MetaMask Staking, investors must have ETH in their MetaMask Wallet. 295. First, from the browser extension or mobile app, the investor clicks on “Stake,” or “Staking.” They are then taken to the MetaMask Portfolio site, where they can then choose “ETH.” 296. At this point, Consensys’s graphical interface presents the investor with two options: Lido and Rocket Pool. 298. If either Lido or Rocket Pool is at or near capacity, Consensys’s MetaMask Staking software disables the ability to stake with that program. 299. In any event, an investor can choose either the Lido or Rocket Pool staking program by clicking “Stake.” 300. On the following screen, an investor can input the number of ETH that they would like to invest in one of the staking program investment contracts and click “review.” 301. At that point, Consensys’s MetaMask Staking software shows the investor a screen with the number of the staking pool tokens they will receive in return, their “estimated rewards,” and the “estimated gas fee.” 302. If the investor wishes to proceed with their request to invest in the staking program investment contract, the investor clicks “confirm.” 303. If MetaMask Staking successfully completes the transaction, the investor will see a screen that says, “Transaction Complete.” iii. Consensys Offers and Sells the Lido and Rocket Pool Investment Contracts To Investors. iii. Consensys Offers and Sells the Lido and Rocket Pool Investment Contracts To Investors. 304. Accordingly, Consensys offers and sells the Lido and Rocket Pool investment contracts to investors through the MetaMask Staking platform. 305. Consensys makes this process appear simple and easy to non-technical investors, while performing the technical series of actions necessary to transfer the investor’s ETH to Lido or Rocket Pool and transfer stETH or rETH to the investor in return. 306. When the investor clicks “confirm,” this signals the MetaMask Staking software to take the steps necessary to exchange the investor’s ETH for rETH or stETH. Specifically, Consensys has programed MetaMask Staking software to take the steps described below. 307. First, Consensys’s MetaMask Staking software reads the private key associated with the ETH in the investor’s MetaMask Wallet. 308. Second, using this key, the software creates a blockchain transaction and transfers the investor’s ETH from the investor’s MetaMask Wallet into a smart contract called the MetaMask Staking Aggregator Router Smart Contract (the “MM Staking Router Smart Contract”). 309. The MM Staking Router Smart Contract has its own Ethereum blockchain address. 310. The investor has no control over the MM Staking Router Smart Contract. 311. The MM Staking Router Smart Contract address temporarily holds the investor’s ETH. 312. Although Consensys has programmed its MetaMask Staking software so that Consensys can take a fee for each transaction, Consensys currently sets the fee variable at zero (i.e., it does not take a fee at this time). 313. Consensys could, however, change the software at any time to assess a fee, in which case the amount of the fee would be diverted from the MM Staking Router Smart Contract into a blockchain address designated by Consensys. 314. Third, Consensys’s software transfers the investor’s ETH from the MM Staking Router Smart Contract to the Lido or Rocket Pool Proxy smart contract (deployed by Lido and Rocket Pool, respectively). 315. These Proxy smart contracts mint stETH or rETH, respectively, upon receiving a deposit of ETH, and, if the MM Staking Router Smart Contract sends ETH to the Proxy smart contracts, the Proxy smart contracts will transfer newly minted stETH or rETH, respectively, to the MM Staking Router Smart Contract. 316. Fourth, the MM Staking Router Smart Contract transfers the stETH or rETH, as the case may be, to the investor’s MetaMask Wallet. 317. As of March 11, 2024, investors had invested 100,252 ETH in the Lido staking program through MetaMask Staking and 8,375 ETH in the Rocket Pool staking program through MetaMask Staking. 318. As of March 11, 2024, Consensys, through MetaMask Staking, offered and sold the Lido staking program to 32,449 unique blockchain addresses and offered and sold the Rocket Pool staking programs to 2,215 unique blockchain addresses. 319. For its part, Lido embraced MetaMask Staking as a platform through which its staking program would be offered and sold. 320. On January 17, 2023, Lido announced on its blog that “Ethereum staking with Lido is now live on MetaMask! Stake your ETH on MetaMask to earn yield and secure the Ethereum network from the comfort of your wallet.” 321. Moreover, a former Lido employee testified that “in terms of a distribution channel [Consensys’s MetaMask was] a very highly valued target.” 322. Accordingly, by the conduct described above, Consensys offered and sold, and continues to offer and sell, investment contracts for Lido and Rocket Pool, participating directly in the distribution of securities from the issuers—Lido and Rocket Pool—to the investor. Continue Reading Here. Continue Reading Here . Here About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved on June 28, 2024, storage.courtlistener.com is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved on June 28, 2024, storage.courtlistener.com is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. storage.courtlistener.com

MetaMask Staking Faces SEC Scrutiny Over Lido and Rocket Pool Offerings

মেটামাস্ক স্টেকিং লিডো এবং রকেট পুল অফারগুলির উপর এসইসি স্ক্রুটিনির মুখোমুখি হয়

MetaMask Staking steht wegen Lido- und Rocket Pool-Angeboten unter Beobachtung der SEC

MetaMask Stake se enfrenta al escrutinio de la SEC por las ofertas de Lido y Rocket Pool

MetaMask Staking fait l'objet d'un examen minutieux par la SEC sur les offres de Lido et de Rocket Pool

मेटामास्क स्टेकिंग को लीडो और रॉकेट पूल ऑफरिंग पर SEC जांच का सामना करना पड़ रहा है

MetaMask ステーキング、Lido および Rocket Pool の提供に関して SEC の監視に直面

MetaMask 스테이킹, Lido 및 로켓 풀 제공에 대한 SEC 조사에 직면

MetaMask Staking enfrenta escrutínio da SEC sobre ofertas de Lido e Rocket Pool

Стейкинг MetaMask подвергается проверке SEC в отношении предложений Lido и Rocket Pool

MetaMask Staking, Lido ve Roket Havuzu Teklifleri Üzerinden SEC İncelemesiyle Karşı Karşıya

MetaMask Stake phải đối mặt với sự giám sát của SEC đối với các dịch vụ Lido và Rocket Pool

MetaMask Staking 因 Lido 和 Rocket Pool 发行面临美国证券交易委员会的审查

SEC v. Consensys Software Inc. Court Filing, retrieved on June 28, 2024, is part of HackerNoon’s Legal PDF Series. You can jump to any part in this filing here. This part is 19 of 26. B. Liquid Staking Pool Providers: Lido and Rocket Pool 238. Lido and Rocket Pool have each created and maintained respective staking programs, designed to capture the staking rewards described above. 239. Lido and Rocket Pool each call their program a “liquid staking” program because— as described below—investors are issued a tradable token in exchange for depositing funds into the program. This token represents the investor’s interest in the program. The token issued in exchange is referred to as a “liquid staking token” or “LST” and the LST can be traded on the secondary market. 240. In Lido, the LST is called stETH; in Rocket Pool, the LST is called rETH. 241. The amount of LST an investor receives is proportional to the amount of ETH they deposit. 242. These staking programs allow investors to both obtain the rewards of staking and also purportedly retain the ability to redeem the value of their investment at any time. i. The Lido Staking Program Is An Investment Contract. 243. Lido launched its liquid staking platform in December 2020. 244. To participate, investors deposit ETH with Lido. 245. In return, Lido issues the investor another crypto asset, “stETH,” representing the investor’s pro rata interest in Lido’s staking program, including the investor’s original deposit of ETH plus any accumulated returns. 246. Lido then uses investors’ deposited ETH in the Ethereum consensus mechanism to earn staking rewards—the financial returns for investors. 247. Specifically, Lido pools the ETH deposited by investors into a Lido smart contract, which initiates the creation of a validator by depositing a 32 ETH bundle to the Ethereum validator deposit contract. 248. As of June 25, 2024, over 28% of all staked ETH on Ethereum is staked in Lido’s staking program. 249. Lido takes, as a fee, 10% of the staking rewards earned. 250. The remaining rewards are accrued, pro rata, by stETH token holders. 251. Lido markets its staking program as an investment opportunity. 252. Lido also leads investors to reasonably expect that investors’ profits will come from Lido’s efforts. 253. According to Lido’s website, from December 2020 to February 2024, Lido’s staking program returned an annualized percentage gain of 3% to 9%. 254. In a blog post dated December 28, 2020, Lido stated: “Lido allows users to stake any amount of ETH – without the need to maintain complex infrastructure.” 255. From at least June 2021 to June 2024, in a “Help” article on its website, Lido stated that staking “requires expert knowledge and complex and costly infrastructure” and that through Lido “users can eliminate these inconveniences.” 256. Lido claimed in an October 2020 document posted to its website that it is “more profitable” than other staking pool providers because of its fee model and the quality of its node operators. 257. From at least February 2023 to June 2024, another “Help” article on Lido’s website claims to allocate investors’ staked ETH across multiple, high-quality validator node operators (that is, participants in the Ethereum network consensus mechanism), minimizing the risks associated with staking ETH. 258. In the same Help article, Lido states that it elects “professional and reputable node operators” and that the penalty and slashing risks are reduced “given the quality of the Lido validator set and its proven track record.” 259. In short, Lido purportedly offers investors a “simplified participation in staking”— deploying its resources and expertise to achieve staking rewards that individual investors typically would not be able to achieve on their own. 260. The holder of any stETH—whether issued directly from Lido or purchased in the secondary market—has the right to deliver the stETH to Lido to get back the pro-rata staked ETH plus accrued rewards. 261. Lido treats all investors’ deposited ETH as fungible. It does not purport to segregate investor funds. 262. In light of the above, Lido offered and sold its staking program as an investment contract. ii. The Rocket Pool Staking Program Is An Investment Contract 263. Rocket Pool launched its platform in October 2021. 264. To participate, investors deposit ETH with Rocket Pool. 265. In return, Rocket Pool issues another crypto asset, “rETH,” representing the investor’s pro rata interest in Rocket Pool’s staking program, including the investor’s original deposit of ETH plus any accumulated returns. 266. Rocket Pool then uses investors’ deposited ETH in the Ethereum consensus mechanism to earn staking rewards—the financial returns for investors. 267. Specifically, Rocket Pool pools the ETH deposited by investors into a Rocket Pool smart contract, which initiates the creation of a validator by depositing a 32-ETH bundle to the Ethereum validator deposit contract. 268. Rocket Pool takes a 0.05% fee of the staking rewards it earns. 269. The remaining staking rewards accrue, pro-rata, to investors. 270. Rocket Pool also markets its staking program as an investment opportunity. 271. According to Rocket Pool’s website, rETH “accrues value over time.” 272. Rocket Pool also leads investors to reasonably expect that investors’ profits will come from the efforts of Rocket Pool. 273. As of June 2024, Rocket Pool advertised on its website an annual percentage return of approximately 3.11%. 274. In an FAQ available on its website, Rocket Pool notes that its staking service makes staking available to investors who might not otherwise have the technical expertise necessary to interact with smart contracts or keep a node running 24/7. 275. Indeed, according to Rocket Pool’s FAQ, its program “removes several high barriers to entry that exist with Proof of Stake on Ethereum.” 276. In a January 22, 2021, Medium Post, Rocket Pool stated that its program was “an easy and permissionless way to engage in staking without needing to run any staking infrastructure or even have 32 ETH.” 277. The Rocket Pool FAQ states that it will “allow anyone to earn rewards on deposits as small as 0.01 ETH.” 278. On its website, Rocket Pool also attempts to differentiate itself from other staking pool providers, claiming that “Rocket Pool is the only staking platform with a perfect score on ethereum.org.” 279. According to Rocket Pool’s website, its protocol is highly secure and its “smart contracts have been extensively audited, multiple times, by some of the best auditors in the Ethereum ecosystem.” 280. Rocket Pool also touts other reasons for investors to stake their ETH with Rocket Pool. 281. In the January 2021 Medium post, Rocket Pool notes that the value of rETH is “protected against node slashing and downtime by several built in insurance mechanisms.” 282. Specifically, Rocket Pool requires individuals that run Rocket Pool validator nodes to put up collateral to protect against losses that may result from penalties and slashing. 283. Rocket Pool’s website states that “every rETH token is exactly the same, you will automatically receive the benefits of staking just by holding the token!” (Emphasis in original.) 284. In light of the above, Rocket Pool offered and sold its staking program as an investment contract. 285. Neither Lido nor Rocket Pool have ever filed registration statements with the SEC for the offer and sale of their respective staking program investment contracts. Continue Reading Here. About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings.
This court case retrieved on June 28, 2024, storage.courtlistener.com is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. SEC v. Consensys Software Inc. Court Filing, retrieved on June 28, 2024, is part of HackerNoon’s Legal PDF Series. You can jump to any part in this filing here. This part is 19 of 26. SEC v. Consensys Software Inc. Court Filing, retrieved on June 28, 2024, is part of HackerNoon’s Legal PDF Series . You can jump to any part in this filing here . This part is 19 of 26. HackerNoon’s Legal PDF Series here B. Liquid Staking Pool Providers: Lido and Rocket Pool 238. Lido and Rocket Pool have each created and maintained respective staking programs, designed to capture the staking rewards described above. 239. Lido and Rocket Pool each call their program a “liquid staking” program because— as described below—investors are issued a tradable token in exchange for depositing funds into the program. This token represents the investor’s interest in the program. The token issued in exchange is referred to as a “liquid staking token” or “LST” and the LST can be traded on the secondary market. 240. In Lido, the LST is called stETH; in Rocket Pool, the LST is called rETH. 241. The amount of LST an investor receives is proportional to the amount of ETH they deposit. 242. These staking programs allow investors to both obtain the rewards of staking and also purportedly retain the ability to redeem the value of their investment at any time. i. The Lido Staking Program Is An Investment Contract. i. The Lido Staking Program Is An Investment Contract. 243. Lido launched its liquid staking platform in December 2020. 244. To participate, investors deposit ETH with Lido. 245. In return, Lido issues the investor another crypto asset, “stETH,” representing the investor’s pro rata interest in Lido’s staking program, including the investor’s original deposit of ETH plus any accumulated returns. 246. Lido then uses investors’ deposited ETH in the Ethereum consensus mechanism to earn staking rewards—the financial returns for investors. 247. Specifically, Lido pools the ETH deposited by investors into a Lido smart contract, which initiates the creation of a validator by depositing a 32 ETH bundle to the Ethereum validator deposit contract. 248. As of June 25, 2024, over 28% of all staked ETH on Ethereum is staked in Lido’s staking program. 249. Lido takes, as a fee, 10% of the staking rewards earned. 250. The remaining rewards are accrued, pro rata, by stETH token holders. 251. Lido markets its staking program as an investment opportunity. 252. Lido also leads investors to reasonably expect that investors’ profits will come from Lido’s efforts. 253. According to Lido’s website, from December 2020 to February 2024, Lido’s staking program returned an annualized percentage gain of 3% to 9%. 254. In a blog post dated December 28, 2020, Lido stated: “Lido allows users to stake any amount of ETH – without the need to maintain complex infrastructure.” 255. From at least June 2021 to June 2024, in a “Help” article on its website, Lido stated that staking “requires expert knowledge and complex and costly infrastructure” and that through Lido “users can eliminate these inconveniences.” 256. Lido claimed in an October 2020 document posted to its website that it is “more profitable” than other staking pool providers because of its fee model and the quality of its node operators. 257. From at least February 2023 to June 2024, another “Help” article on Lido’s website claims to allocate investors’ staked ETH across multiple, high-quality validator node operators (that is, participants in the Ethereum network consensus mechanism), minimizing the risks associated with staking ETH. 258. In the same Help article, Lido states that it elects “professional and reputable node operators” and that the penalty and slashing risks are reduced “given the quality of the Lido validator set and its proven track record.” 259. In short, Lido purportedly offers investors a “simplified participation in staking”— deploying its resources and expertise to achieve staking rewards that individual investors typically would not be able to achieve on their own. 260. The holder of any stETH—whether issued directly from Lido or purchased in the secondary market—has the right to deliver the stETH to Lido to get back the pro-rata staked ETH plus accrued rewards. 261. Lido treats all investors’ deposited ETH as fungible. It does not purport to segregate investor funds. 262. In light of the above, Lido offered and sold its staking program as an investment contract. ii. The Rocket Pool Staking Program Is An Investment Contract ii. The Rocket Pool Staking Program Is An Investment Contract 263. Rocket Pool launched its platform in October 2021. 264. To participate, investors deposit ETH with Rocket Pool. 265. In return, Rocket Pool issues another crypto asset, “rETH,” representing the investor’s pro rata interest in Rocket Pool’s staking program, including the investor’s original deposit of ETH plus any accumulated returns. 266. Rocket Pool then uses investors’ deposited ETH in the Ethereum consensus mechanism to earn staking rewards—the financial returns for investors. 267. Specifically, Rocket Pool pools the ETH deposited by investors into a Rocket Pool smart contract, which initiates the creation of a validator by depositing a 32-ETH bundle to the Ethereum validator deposit contract. 268. Rocket Pool takes a 0.05% fee of the staking rewards it earns. 269. The remaining staking rewards accrue, pro-rata, to investors. 270. Rocket Pool also markets its staking program as an investment opportunity. 271. According to Rocket Pool’s website, rETH “accrues value over time.” 272. Rocket Pool also leads investors to reasonably expect that investors’ profits will come from the efforts of Rocket Pool. 273. As of June 2024, Rocket Pool advertised on its website an annual percentage return of approximately 3.11%. 274. In an FAQ available on its website, Rocket Pool notes that its staking service makes staking available to investors who might not otherwise have the technical expertise necessary to interact with smart contracts or keep a node running 24/7. 275. Indeed, according to Rocket Pool’s FAQ, its program “removes several high barriers to entry that exist with Proof of Stake on Ethereum.” 276. In a January 22, 2021, Medium Post, Rocket Pool stated that its program was “an easy and permissionless way to engage in staking without needing to run any staking infrastructure or even have 32 ETH.” 277. The Rocket Pool FAQ states that it will “allow anyone to earn rewards on deposits as small as 0.01 ETH.” 278. On its website, Rocket Pool also attempts to differentiate itself from other staking pool providers, claiming that “Rocket Pool is the only staking platform with a perfect score on ethereum.org.” 279. According to Rocket Pool’s website, its protocol is highly secure and its “smart contracts have been extensively audited, multiple times, by some of the best auditors in the Ethereum ecosystem.” 280. Rocket Pool also touts other reasons for investors to stake their ETH with Rocket Pool. 281. In the January 2021 Medium post, Rocket Pool notes that the value of rETH is “protected against node slashing and downtime by several built in insurance mechanisms.” 282. Specifically, Rocket Pool requires individuals that run Rocket Pool validator nodes to put up collateral to protect against losses that may result from penalties and slashing. 283. Rocket Pool’s website states that “every rETH token is exactly the same, you will automatically receive the benefits of staking just by holding the token!” (Emphasis in original.) automatically receive the benefits of staking just by holding the token!” 284. In light of the above, Rocket Pool offered and sold its staking program as an investment contract. 285. Neither Lido nor Rocket Pool have ever filed registration statements with the SEC for the offer and sale of their respective staking program investment contracts. Continue Reading Here. Continue Reading Here . Here About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved on June 28, 2024, storage.courtlistener.com is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved on June 28, 2024, storage.courtlistener.com is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. storage.courtlistener.com

Crypto Giants Lido and Rocket Pool Face SEC Scrutiny Over Staking Programs

SEC v. Consensys Software Inc. Court Filing, retrieved on June 28, 2024, is part of HackerNoon’s Legal PDF Series. You can jump to any part in this filing here. This part is 14 of 26. B. MANA 162. “MANA” is the digital token minted by Decentraland. Decentraland is a virtual reality platform that began development in June 2015 but was not made available to the public until its launch in February 2020. Decentraland was launched through an entity named Metaverse Holdings by a team of core individual developers: Ariel Meilich, Esteban Ordano, Manual Araoz, and Yemel Jardi. Decentraland operates on the Ethereum blockchain. According to Decentraland’s website, www.decentraland.org, Decentraland is a three-dimensional virtual reality platform, where users can create, experience, and monetize their content and applications. 163. According to Decentraland’s website, MANA serves as the crypto asset involved in all transactions in the Decentraland virtual reality ecosystem. On August 18, 2017, Decentraland held an initial coin offering in which MANA tokens were exchanged for ETH tokens, raising approximately $24.1 million. Currently, there is a total supply of approximately 2.19 billion MANA tokens. 164. Decentraland offered early contributors to the Decentraland ecosystem a discounted price when purchasing MANA. 165. From the time of its offering, MANA was offered and sold as an investment contract and therefore a security. 166. The price of all MANA tokens goes up or down together. 167. MANA has been available for buying and selling through MetaMask Swaps since at least October 2020. 168. The information Decentraland publicly disseminated would lead a reasonable investor, including those who have purchased MANA since October 2020, to view MANA as an investment. Specifically, MANA holders would reasonably expect to profit from Decentraland’s efforts to grow the Decentraland protocol because this growth would in turn increase the demand for and value of MANA. 169. Investor proceeds raised during the MANA ICO were pooled to fund the marketing, business expenses, and completion of the Decentraland platform. For instance, on July 5, 2017—a few weeks before the MANA ICO—Jardi published a blog post detailing Decentraland’s intended use of revenue from the token sale as follows: The blog post further explained that the “top priority“for use of the revenue was to develop a virtual world and that even after Decentraland was created, “the development budget will focus on the continued improvement of the end-user experience within the world browser“. Indeed, Meilich explained in a separate blog post that after the ICO, Decentraland would implement a “Continuous Token Model,“ where it would increase the MANA supply by 8 percent in the first year, followed by a lower rate in subsequent years, to allow Decentraland to “regularly expand while accommodating new users … The proceeds of the tokens sold by [the Continuous token Model] will finance Decentraland over the long haul, perpetually aligning it with the prosperity of the network.“ In April 2020, the Decentraland Team announced the creation of the Decentraland Foundation (the “Foundation“), which today holds the intellectual property rights over and makes available the products and services, including virtual environment and tools, offered on the Decentraland platform. Meilich publicly stated that the distribution of the initial supply of MANA tokens issued at the time of the ICO would be as follows: 20 percent to the founding team, advisors, and early contributors: 20 percent to the Foundation; 40 percent to be available for purchase by the public; and 20 percent reserved to “incentivize early users, developers, and partners who want to build within Decentraland.” 173. As Meilich explained in his public blog post, “To incentivize value creation within Decentraland, extra tokens will be allocated to the [development team], organization, and a reserve to accelerate Community and Partner engagement.” 174. For example, Decentraland publicly issued a whitepaper (“Decentraland Whitepaper”) describing the architecture that would be built in the virtual reality platform and steps that would be taken to support Decentraland’s growth. It further made clear that the development of the platform was only beginning, and listed a number of “Challenges” that would need to be addressed in the development process in order for the platform to succeed. 175. Decentraland has continued to invest efforts in new developments and tools for the platform. According to Melich, even after the ICO, Decentraland was still “preparing a land allocation policy to ensure fair distribution, as well as a method for groups to purchase larger contiguous plots of land.” Since the ICO, Decentraland has developed tools for purported use on its platform (e.g., the “Marketplace” and “Builder” tools). In a public blog post published on March 19, 2018, the Decentraland team described the marketplace tool as the “first … in what will be a series of tools.” 176. Additionally, the Decentraland Whitepaper explained how the Foundation would “Foster[] the Network” in that it will “hold contests to create art, games, applications, and experiences, with prizes contingent on meeting a set of milestones. At the same time, new users will be assigned allowances, allowing them to participate in the economy immediately.” The Decentraland Whitepaper further claimed, “These financial incentives will help bootstrap the utility value of the network until it independently attracts users and developers.” 177. The Decentraland Whitepaper and website have also marketed that the protocol “burns” (or destroys) MANA tokens when used within the Decentraland ecosystem. 178. The Decentraland Whitepaper is still available on the Decentraland website. Continue Reading Here. About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings.
This court case retrieved on June 28, 2024, storage.courtlistener.com is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. SEC v. Consensys Software Inc. Court Filing, retrieved on June 28, 2024, is part of HackerNoon’s Legal PDF Series. You can jump to any part in this filing here. This part is 14 of 26. SEC v. Consensys Software Inc. Court Filing, retrieved on June 28, 2024, is part of HackerNoon’s Legal PDF Series . You can jump to any part in this filing here . This part is 14 of 26. HackerNoon’s Legal PDF Series here B. MANA 162. “MANA” is the digital token minted by Decentraland. Decentraland is a virtual reality platform that began development in June 2015 but was not made available to the public until its launch in February 2020. Decentraland was launched through an entity named Metaverse Holdings by a team of core individual developers: Ariel Meilich, Esteban Ordano, Manual Araoz, and Yemel Jardi. Decentraland operates on the Ethereum blockchain. According to Decentraland’s website, www.decentraland.org, Decentraland is a three-dimensional virtual reality platform, where users can create, experience, and monetize their content and applications. 163. According to Decentraland’s website, MANA serves as the crypto asset involved in all transactions in the Decentraland virtual reality ecosystem. On August 18, 2017, Decentraland held an initial coin offering in which MANA tokens were exchanged for ETH tokens, raising approximately $24.1 million. Currently, there is a total supply of approximately 2.19 billion MANA tokens. 164. Decentraland offered early contributors to the Decentraland ecosystem a discounted price when purchasing MANA. 165. From the time of its offering, MANA was offered and sold as an investment contract and therefore a security. 166. The price of all MANA tokens goes up or down together. 167. MANA has been available for buying and selling through MetaMask Swaps since at least October 2020. 168. The information Decentraland publicly disseminated would lead a reasonable investor, including those who have purchased MANA since October 2020, to view MANA as an investment. Specifically, MANA holders would reasonably expect to profit from Decentraland’s efforts to grow the Decentraland protocol because this growth would in turn increase the demand for and value of MANA. 169. Investor proceeds raised during the MANA ICO were pooled to fund the marketing, business expenses, and completion of the Decentraland platform. For instance, on July 5, 2017—a few weeks before the MANA ICO—Jardi published a blog post detailing Decentraland’s intended use of revenue from the token sale as follows: The blog post further explained that the “top priority“for use of the revenue was to develop a virtual world and that even after Decentraland was created, “the development budget will focus on the continued improvement of the end-user experience within the world browser“. The blog post further explained that the “top priority“for use of the revenue was to develop a virtual world and that even after Decentraland was created, “the development budget will focus on the continued improvement of the end-user experience within the world browser“. Indeed, Meilich explained in a separate blog post that after the ICO, Decentraland would implement a “Continuous Token Model,“ where it would increase the MANA supply by 8 percent in the first year, followed by a lower rate in subsequent years, to allow Decentraland to “regularly expand while accommodating new users … The proceeds of the tokens sold by [the Continuous token Model] will finance Decentraland over the long haul, perpetually aligning it with the prosperity of the network.“ Indeed, Meilich explained in a separate blog post that after the ICO, Decentraland would implement a “Continuous Token Model,“ where it would increase the MANA supply by 8 percent in the first year, followed by a lower rate in subsequent years, to allow Decentraland to “regularly expand while accommodating new users … The proceeds of the tokens sold by [the Continuous token Model] will finance Decentraland over the long haul, perpetually aligning it with the prosperity of the network.“ In April 2020, the Decentraland Team announced the creation of the Decentraland Foundation (the “Foundation“), which today holds the intellectual property rights over and makes available the products and services, including virtual environment and tools, offered on the Decentraland platform. Meilich publicly stated that the distribution of the initial supply of MANA tokens issued at the time of the ICO would be as follows: 20 percent to the founding team, advisors, and early contributors: 20 percent to the Foundation; 40 percent to be available for purchase by the public; and 20 percent reserved to “incentivize early users, developers, and partners who want to build within Decentraland.” In April 2020, the Decentraland Team announced the creation of the Decentraland Foundation (the “Foundation“), which today holds the intellectual property rights over and makes available the products and services, including virtual environment and tools, offered on the Decentraland platform. Meilich publicly stated that the distribution of the initial supply of MANA tokens issued at the time of the ICO would be as follows: 20 percent to the founding team, advisors, and early contributors: 20 percent to the Foundation; 40 percent to be available for purchase by the public; and 20 percent reserved to “incentivize early users, developers, and partners who want to build within Decentraland.” 173. As Meilich explained in his public blog post, “To incentivize value creation within Decentraland, extra tokens will be allocated to the [development team], organization, and a reserve to accelerate Community and Partner engagement.” 174. For example, Decentraland publicly issued a whitepaper (“Decentraland Whitepaper”) describing the architecture that would be built in the virtual reality platform and steps that would be taken to support Decentraland’s growth. It further made clear that the development of the platform was only beginning, and listed a number of “Challenges” that would need to be addressed in the development process in order for the platform to succeed. 175. Decentraland has continued to invest efforts in new developments and tools for the platform. According to Melich, even after the ICO, Decentraland was still “preparing a land allocation policy to ensure fair distribution, as well as a method for groups to purchase larger contiguous plots of land.” Since the ICO, Decentraland has developed tools for purported use on its platform (e.g., the “Marketplace” and “Builder” tools). In a public blog post published on March 19, 2018, the Decentraland team described the marketplace tool as the “first … in what will be a series of tools.” 176. Additionally, the Decentraland Whitepaper explained how the Foundation would “Foster[] the Network” in that it will “hold contests to create art, games, applications, and experiences, with prizes contingent on meeting a set of milestones. At the same time, new users will be assigned allowances, allowing them to participate in the economy immediately.” The Decentraland Whitepaper further claimed, “These financial incentives will help bootstrap the utility value of the network until it independently attracts users and developers.” 177. The Decentraland Whitepaper and website have also marketed that the protocol “burns” (or destroys) MANA tokens when used within the Decentraland ecosystem. 178. The Decentraland Whitepaper is still available on the Decentraland website. Continue Reading Here. Continue Reading Here . Here About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved on June 28, 2024, storage.courtlistener.com is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved on June 28, 2024, storage.courtlistener.com is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. storage.courtlistener.com

Decentraland's MANA Token Under SEC Scrutiny: Implications for Virtual Reality Investments

SEC v. Consensys Software Inc. Court Filing, retrieved on June 28, 2024, is part of HackerNoon’s Legal PDF Series. You can jump to any part in this filing here. This part is 5 of 26. DEFENDANTS 21. Consensys was founded in 2014. In June 2020, Consensys was incorporated in Delaware. OTHER RELEVANT ENTITIES 22. Lido Finance (“Lido”) is a Cayman Islands company. Lido operates a program for staking on the Ethereum blockchain. Lido launched its staking program in December 2020. 23. Rocket Pool is headquartered in Australia. Rocket Pool also operates a program for staking on the Ethereum blockchain. Rocket Pool launched its staking program in October 2021. Continue Reading Here. About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings.
This court case retrieved on June 28, 2024, storage.courtlistener.com is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. SEC v. Consensys Software Inc. Court Filing, retrieved on June 28, 2024, is part of HackerNoon’s Legal PDF Series. You can jump to any part in this filing here. This part is 5 of 26. SEC v. Consensys Software Inc. Court Filing, retrieved on June 28, 2024, is part of HackerNoon’s Legal PDF Series . You can jump to any part in this filing here . This part is 5 of 26. HackerNoon’s Legal PDF Series here DEFENDANTS 21. Consensys was founded in 2014. In June 2020, Consensys was incorporated in Delaware. OTHER RELEVANT ENTITIES 22. Lido Finance (“Lido”) is a Cayman Islands company. Lido operates a program for staking on the Ethereum blockchain. Lido launched its staking program in December 2020. Lido Finance (“Lido”) 23. Rocket Pool is headquartered in Australia. Rocket Pool also operates a program for staking on the Ethereum blockchain. Rocket Pool launched its staking program in October 2021. Rocket Pool Continue Reading Here. Continue Reading Here . Here About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved on June 28, 2024, storage.courtlistener.com is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved on June 28, 2024, storage.courtlistener.com is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. storage.courtlistener.com

Major Crypto Players Consensys, Lido, and Rocket Pool Under SEC Scrutiny

USA v. Samuel Bankman-Fried Court Filing, retrieved on March 15, 2024 is part of . You can jump to any part in this filing . This part is 10 of 33. HackerNoon’s Legal PDF Series here A. Use of Signal to Auto-Delete Messages At trial, the evidence established that the defendant instructed employees to use Signal, an end-to-end encrypted messaging application, with an auto-delete feature enabled so as to prevent regulators from reviewing communications. Specifically, Adam Yedidia testified that the defendant instructed employees to use Signal with a feature enabled that would automatically delete each message after a certain amount of time had elapsed since the message was sent. (Tr. 175). Bankman-Fried stated that “it was all downside for messages to be kept around” because “if regulators found something they didn’t like in those messages, that could be bad for the company.” (Tr. 176). Similarly, Ellison testified that the defendant “directed [them] to use the disappearing messaging setting on [their] Signal, meaning that all messages [they] sent in these conversations would disappear after seven days.” (Tr. 825). Bankman-Fried said that FTX and Alameda employees “should be very careful about what [they] put in writing” because “putting things in writing was one of the primary ways that financial firms got in legal trouble.” (Id.). After those directives, FTX and Alameda employees increasingly used Signal messages for “sensitive” communications. (Tr. 825-26). Government Exhibit 1083 is a chart of all of the Signal chats on Wang’s device that were set to auto-delete. The chart shows that many of the chats’ auto-delete function was set by the defendant. Continue Reading . Here About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved on March 15, 2024, from is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. storage.courtlistener

SBF Directed Employees to Use the Auto-Delete Signal App Future to Avoid Regulatory Scrutiny

Dependency Injection in is a lifesaver when organizing dependencies — especially in more complex ASP.NET Core applications. And if you’re already or just want to stick as close as possible to the already provided DI offerings, is a great enhancement. C# familiar with IServiceCollection Scrutor in C# In this article, I’ll provide you with a high-level overview of Dependency Injection and Scrutor in C#. But from there, we’re jumping right into 3 tips that you can use with Scrutor that could prove to be very helpful in your application! What is Scrutor in C#? Scrutor is a powerful NuGet package in C# that enhances dependency injection. It simplifies the registration and resolution of dependencies, making it easier for you to manage and organize your code. Dependency injection is a popular approach to configuring applications that promotes loose coupling and improves testability and maintainability. It involves injecting dependencies into a class rather than directly creating them within the class. This means that the responsibility of creating the dependency is not owned by the class requiring it, but instead, owned by someone up the call stack. Eventually, this pushes nearly all dependency creation to the entry point of an application, making it unwieldy. However,  dependency injection frameworks help . clean up and organize all of this logic Scrutor takes this concept a step further by providing a simple and intuitive way to register and resolve dependencies. With Scrutor, you no longer need to manually register each dependency one by one. Instead, you can use conventions and attributes to automate the process. 1 – Using Scrutor for Registration and Resolution To illustrate how to use Scrutor in C# for registration and resolution, let’s consider a simple scenario. Imagine we have an application that requires the use of different data repositories, such as UserRepository and ProductRepostiory. First, we need to install the Scrutor NuGet package in our project. Open the Package Manager Console and run the following command: Install-Package Scrutor Next, we need to define our repositories and their corresponding interfaces. This example is essentially empty, but we’ll be referring to these in a moment: public interface IUserRepository
{
    // Interface methods
}
public class UserRepository : IUserRepository 
{
    // Implementation
}

public interface IProductRepository
{
    // Interface methods
}

public class ProductRepository : IProductRepository
{
    // Implementation
} Now, let’s wire up our dependencies using Scrutor. In your startup code (such as in the ConfigureServices method in ASP.NET Core), add the following code: services.Scan(scan => scan
    .FromAssemblyOf<Startup>()
    .AddClasses(classes => classes.AssignableToAny(
        typeof(IUserRepository),
        typeof(IProductRepository)))
    .AsImplementedInterfaces()
    .WithScopedLifetime()); This code uses the Scan method from Scrutor to scan the assembly that contains the Startup class. It then filters out the classes that are assignable to IUserRepository or IProductRepository interfaces. Finally, it maps the implementations of these interfaces and registers them with their respective interfaces. Now, we can inject these dependencies into our classes. For example, let’s say we have a UserService class that requires IUserRepository: public class UserService 
{
    private readonly IUserRepository _userRepository; 
    
    public UserService(IUserRepository userRepository) 
    { 
        _userRepository = userRepository;
    }

    // Rest of the class implementation
} By declaring IUserRepository as a dependency in the constructor, Scrutor along with IServiceCollection will automatically resolve and inject the UserRepository instance for us. 2 – The Decorator Pattern – Example of Logging for Services Imagine you have a service interface and an implementation . You want to log the entry and exit of each method call in without polluting its business logic with logging concerns. IService MyService MyService First, define the interface and its implementation: IService public interface IService
{
    void DoWork();
}

public class MyService : IService
{
    public void DoWork()
    {
        // Business logic here
    }
} Next, create a decorator class that implements . This class will wrap the actual service and add logging around the delegated method calls: LoggingDecorator IService public class LoggingDecorator : IService
{
    private readonly IService _decorated;
    private readonly ILogger<LoggingDecorator> _logger;

    public LoggingDecorator(IService decorated, ILogger<LoggingDecorator> logger)
    {
        _decorated = decorated;
        _logger = logger;
    }

    public void DoWork()
    {
        _logger.LogInformation("Starting work.");
        _decorated.DoWork();
        _logger.LogInformation("Finished work.");
    }
} Now, use Scrutor to register your service and its decorator in the or wherever you configure your services: Startup.cs public void ConfigureServices(IServiceCollection services)
{
    // Register the base service
    services.AddScoped<IService, MyService>();

    // Use Scrutor to apply the decorator
    services.Decorate<IService, LoggingDecorator>();

    // Make sure to register the ILogger or ILogger<T> dependencies if not already done

} This setup uses Scrutor to wrap the registration with the . When resolving , the DI container will provide an instance of , which in turn wraps an instance of . This approach achieves the separation of concerns by keeping the logging logic outside of your business logic. IService LoggingDecorator IService LoggingDecorator MyService 3 – Feature Toggle for Service Implementations When we’re building complex systems, there are often cases where we want to introduce something like feature flags. These allow us to take different code paths based on configuration and not have to recompile and deploy an entire application. In some situations, it’s not just about picking a different code path, it’s about swapping an entire implementation of something! Let’s try out an example together! Assume you have an interface with multiple implementations: (a new, experimental feature) and (the current, stable feature). You want to switch between these implementations at runtime based on a configuration flag. IFeatureService NewFeatureService StandardFeatureService First, define the interface and its implementations: IFeatureService public interface IFeatureService
{
    void ExecuteFeature();
}

public class NewFeatureService : IFeatureService
{
    public void ExecuteFeature()
    {
        // New feature logic
    }
}

public class StandardFeatureService : IFeatureService
{
    public void ExecuteFeature()
    {
        // Standard feature logic
    }
} Next, you need a way to determine which implementation to use based on a feature toggle setting. This could be a value in , a database setting, or any other configuration source. appsettings.json Now, use Scrutor to dynamically register the appropriate service implementation based on the feature toggle: public void ConfigureServices(IServiceCollection services)
{
    // Assume GetFeatureToggleValue() retrieves the current feature toggle setting
    var useNewFeature = GetFeatureToggleValue("UseNewFeature");

    // Dynamically register the appropriate implementation based on the feature toggle
    if (useNewFeature)
    {
        services.AddScoped<IFeatureService, NewFeatureService>();
    }
    else
    {
        services.AddScoped<IFeatureService, StandardFeatureService>();
    }

    // Optional: You could combine this with the previous example
    // to use the decorator pattern too!
    // services.Decorate<IFeatureService, FeatureServiceProxy>();
}

private bool GetFeatureToggleValue(string featureName)
{
    // This method would typically check your
    // configuration source to determine if the feature is enabled
    // For simplicity, this is just a placeholder
    return false; // or true based on actual configuration
} Taking an approach like this can help us with: : Allows the application to switch between feature implementations without needing to redeploy. You can enable or disable features with just a configuration change. Flexibility : You can test new features in a production environment with a limited set of users by toggling the feature on for those users. Testing in Production : Helps in rolling out features gradually to monitor the impact and ensure stability before a wider release. Gradual Rollouts : Quickly revert to the old implementation if issues arise with the new feature, minimizing downtime and impact on users. Risk Mitigation Wrapping Up Scrutor in C# In this article, I provided you with 3 simple tips for dependency injection with Scrutor in C#. After a brief overview of what dependency injection is and how Scrutor fits into it, we jumped right into our examples. We got to see assembly scanning, how to decorate dependencies, and even how to consider feature flagging entire implementations! Dependency injection is something that can greatly simplify your applications as they grow in complexity, and Scrutor can be a huge help if you want to stick to the . If you found this useful and you’re looking for more learning opportunities, consider and check out my ! Join me and the ! built-in IServiceCollection offering from Microsoft subscribing to my free weekly software engineering newsletter free videos on YouTube other community members on Discord Also published here.

3 Simple Tips For Dependency Injection Using Scrutor in C#

C# এ স্ক্রুটার ব্যবহার করে নির্ভরতা ইনজেকশনের জন্য 3 টি সহজ টিপস

3 einfache Tipps für die Abhängigkeitsinjektion mit Scrutor in C#

Tres consejos sencillos para la inyección de dependencias utilizando Scrutor en C#

3 conseils simples pour l'injection de dépendances à l'aide de Scrutor en C#

C# में स्क्रूटर का उपयोग करके निर्भरता इंजेक्शन के लिए 3 सरल युक्तियाँ

C# で Scrutor を使用した依存関係の注入に関する 3 つの簡単なヒント

C#에서 Scrutor를 사용하여 종속성 주입을 위한 3가지 간단한 팁

3 dicas simples para injeção de dependência usando Scrutor em C#

3 простых совета по внедрению зависимостей с помощью Scrutor в C#

C#'ta Scrutor Kullanarak Bağımlılık Enjeksiyonu İçin 3 Basit İpucu

3 mẹo đơn giản để chèn phụ thuộc bằng Scrutor trong C#

在 C# 中使用 Scrutor 进行依赖注入的 3 个简单技巧

Let’s explore two popular dependency injection frameworks for dotnet as we compare Scrutor vs Autofac in C#! Dependency injection becomes (almost) a necessity as your application grows in size and complexity, and having the right dependency injection framework to use can make a world of difference. Starting with a brief explanation of what dependency injection is in C#: Dependency injection is a design approach that allows objects to be loosely coupled and promotes the concept of passing in (or “injecting”) dependencies rather than directly creating them within a class. This promotes modularity, testability, and flexibility in your codebase. So why is it important to choose the right framework for your C# projects? Well, the right framework can greatly simplify your codebase, improve maintainability, and enhance the overall performance of your application. Scrutor and Autofac are two popular options to consider, and in this article, we’ll compare and analyze them in detail. dependency injection Overview of Scrutor and Autofac Scrutor and Autofac are both popular dependency injection frameworks in the C# ecosystem. They provide developers with the tools to effectively manage dependencies and promote modular and extensible software architectures (and we love that kind of stuff around here!). In this section, I’ll provide a brief introduction to both Scrutor and Autofac to kick us off in our comparison. Scrutor in C# Scrutor is a lightweight, convention-based assembly scanning extension for . It simplifies the registration of services by allowing developers to use attribute-based conventions rather than explicit registrations. With Scrutor, you can define rules and patterns that automatically discover and register types based on specific attributes or naming conventions. the default .NET Core DI container Some key advantages of Scrutor include: Simplicity: Scrutor offers a simple and intuitive API that makes it easy to configure and use. It simplifies the process of registering services by leveraging conventions, reducing the need for manual registrations. Flexibility: Scrutor allows for dynamic composition and discovery of services based on conventions. This flexibility enables developers to easily extend and modify their software architecture without the need to rewrite or modify existing code. Performance: Scrutor is designed to be highly performant, with minimal impact on the overall application performance. By leveraging fast assembly scanning techniques, it ensures efficient service registration and resolution. Autofac in C# Autofac is a powerful and feature-rich DI container for .NET applications, and historically, this has been my go-to for dependency injection. It provides advanced capabilities and extensive configurability, making it suitable for complex projects. Autofac offers a ton of features and extensions that enable developers to achieve fine-grained control over dependency injection, but that might also make it overly complicated for many use-cases. Some key advantages of Autofac include: Extensibility: Autofac provides a modular and extensible architecture, allowing developers to customize and extend its behavior to meet specific requirements. It offers a wide range of extension points and integration options, making it highly adaptable to different project needs. Lifetime Management: Autofac offers various options for managing the lifetime of registered services, including singleton, per request, and per dependency. This flexibility allows for efficient resource utilization and enables developers to control the lifespan of dependencies. Interoperability: Autofac seamlessly integrates with other popular frameworks and technologies in the .NET ecosystem. Whether you are developing ASP.NET Core applications or working with third-party libraries, Autofac provides seamless integration capabilities, ensuring a smooth development experience. Scrutor and Autofac are both great options for dependency injection in C# applications. Scrutor offers a lightweight and convention-based approach, simplifying service registration, while Autofac provides extensive configurability and advanced features for complex projects. Depending on the specific needs and complexity of your project, you can choose the framework that best suits your requirements — there is no universal “best” here. Key Differences of Scrutor vs Autofac in C# When comparing Scrutor and Autofac for dependency injection in C#, there are several key differences to consider. In this section, we’ll explore these differences in terms of key features, syntax, and usage, as well as their approach to registration and resolving dependencies. Key Features of these Frameworks Generally speaking, Scrutor is a lightweight library that offers a simple and intuitive way to scan assemblies and apply conventions for dependency registration. It provides powerful filtering capabilities, allowing developers to easily specify which types should be included or excluded during the scanning process. But the real benefit, in my opinion, is in the simplicity and the fact it works with IServiceCollection seamlessly. On the other hand, Autofac is a more robust and feature-rich dependency injection container. It offers more advanced features such as instance scopes, lifetime management, interception, module system, and integration with other frameworks. That means also the IServiceCollection we get in ASP.NET Core apps — but I admit it feels a bit more clunky. Differences in Syntax and Usage When it comes to syntax and usage, both Scrutor and Autofac provide clean and concise APIs for registering and resolving dependencies. However, they differ in their approach. Scrutor leverages the power of LINQ expressions to define conventions for dependency scanning and registration. It allows developers to specify rules for identifying types based on naming conventions, interfaces implemented, attributes applied, or any custom criteria. This makes it easy to quickly set up and automate the registration process without writing explicit code for each dependency. Autofac, on the other hand, uses a more traditional and explicit syntax for registration. Developers need to explicitly specify the mapping between interfaces and concrete implementations using its fluent registration API. While this requires more manual setup compared to Scrutor’s convention-based approach, it offers more control and flexibility for complex scenarios. I’ve found that I’ve had to create my own , although they’re very straightforward with some reflection. You can see how I manage dependency scanning for Autofac in this video: dependency scanning solutions for Autofac https://www.youtube.com/watch?v=L8KeFxUWaGM&themeRefresh=1&embedable=true Code Examples: Using Scrutor for Dependency Injection in C# In this section, I’ll provide you with code examples and a step-by-step guide on how to use Scrutor for dependency injection in C#. Of course, this will be a contrived example so you’ll want to tailor the concepts here to be applicable to *your* situation. As much as I want to provide you with copy+paste code, I can’t possibly know everyone’s application structure. You’ve been warned! 🙂 1 – Installing Scrutor in C# To begin, make sure you have Scrutor installed in your project. You can do this by adding the NuGet package to your solution. At the time of writing, 4.2.2 is the latest available version of Scrutor. You can of course find more information about Scrutor in C# before diving too far in by . Scrutor checking out the GitHub for it 2 – Setting Up The Dependency Container for Scrutor in C# First, let’s start by setting up the DI container in your application’s startup class. Here’s an example using the default DI container in ASP.NET Core: using Microsoft.Extensions.DependencyInjection;
using Scrutor;

public class Startup
{
    public void ConfigureServices(IServiceCollection services)
    {
        services.Scan(scan => scan
            .FromAssemblyOf<Startup>()
            .AddClasses()
            .AsMatchingInterface()
            .WithScopedLifetime()
        );

        // Add other services and configurations here
    }
} In the above code, is used to scan the assemblies and register the types with their corresponding interfaces. The method specifies which assembly to scan. The method selects all classes to be registered, and the method specifies that each class should be registered with its matching interface. Finally, the method specifies the lifetime of the services to be scoped. services.Scan FromAssemblyOf<Startup> AddClasses() AsMatchingInterface() WithScopedLifetime() 3 – Example Service in Our Application Let’s continue by creating an example interface and its corresponding implementation. Assuming we have an interface and the class implementing it: IEmailService EmailService public interface IEmailService
{
    void SendEmail(string recipient, string message);
}

public class EmailService : IEmailService
{
    public void SendEmail(string recipient, string message)
    {
        // Code to send email
    }
} 4 – Consuming Registered Services with Scrutor Now, we can consume the registered services using constructor injection. Let’s assume we have a , which requires an : HomeController IEmailService public class HomeController : Controller
{
    private readonly IEmailService _emailService;

    public HomeController(IEmailService emailService)
    {
        _emailService = emailService;
    }

    public IActionResult Index()
    {
        // Use the email service to send emails
        _emailService.SendEmail("[email protected]", "Hello, Scrutor!");

        return View();
    }
} In the above code, the class has a constructor that takes in an dependency. The DI container takes care of injecting the implementation when the is instantiated. HomeController IEmailService EmailService HomeController Code Examples: Using Autofac for Dependency Injection in C# In this section, I’ll provide a step-by-step guide on how to use Autofac for dependency injection in C#. I’ll include code snippets and explanations to help you understand the process. 1 – Installing Autofac Before we can start using Autofac for dependency injection, we need to install the necessary packages. Open your project in Visual Studio and navigate to the NuGet Package Manager. Search for “Autofac” and install the package. 2 – Setting up the Container in Autofac Once the package is installed, we can start setting up the Autofac container. The container is responsible for managing and resolving dependencies in our application. In your project, open the or similar file where you configure your services. Startup.cs First, add the necessary namespaces at the top of the file: using Autofac;
using Autofac.Extensions.DependencyInjection; Next, create a method to configure the Autofac container: public IServiceProvider ConfigureServices(IServiceCollection services)
{
    var builder = new ContainerBuilder();

    // Add your services and dependencies here

    builder.Populate(services);

    var container = builder.Build();

    return new AutofacServiceProvider(container);
} In the method, create an instance of the class. This class will be used to register your services and dependencies. Populate the container with the services from the parameter, and then build the container. ConfigureServices ContainerBuilder services Finally, return a new instance of the class, passing in the container as a parameter. AutofacServiceProvider 3 – Registering Services in Autofac With the container set up, we can now register our services and dependencies. In the method, you can use the instance to register your services. ConfigureServices builder Here’s an example registering a service with a single implementation: builder.RegisterType<MyService>().As<IMyService>(); In this example, we register as the implementation of . This means that whenever is requested, Autofac will provide an instance of . MyService IMyService IMyService MyService You can also register multiple implementations of an interface using the method: RegisterType builder.RegisterType<MyService1>().As<IMyService>();
builder.RegisterType<MyService2>().As<IMyService>(); In this case, there are two implementations of , and . Whenever is requested, Autofac will provide an instance of either or . IMyService MyService1 MyService2 IMyService MyService1 MyService2 4 – Resolving Dependencies in Autofac Now that our services are registered, we can resolve them using the Autofac container. In your classes where you need to use a dependency, you can add a constructor parameter of the dependency type. public class MyController
{
    private readonly IMyService _myService;

    public MyController(IMyService myService)
    {
        _myService = myService;
    }

    // Use _myService in your methods
} In this example, depends on . By adding it as a constructor parameter, Autofac will automatically resolve and provide an instance of when creating a new instance of . MyController IMyService IMyService MyController Modular C# Application with Plugin Support In a modular C# application with plugin support, dependency injection becomes vital for integrating and managing plugins seamlessly. It’s difficult for me to imagine how someone might need to either manually wire these types of things up, or roll their own type of dependency/plugin loading system… especially when these things work so well out-of-the-box! Let’s see how Scrutor and Autofac can be applied to handle this scenario effectively. Code Example: Using Scrutor in C# to Scan With Scrutor, we can use the method to scan and register assemblies dynamically. This enables us to discover and register plugins at runtime. Assemblies.FromPath public void ConfigureServices(IServiceCollection services)
{
    services.Scan(scan => scan
        .FromAssembliesFromPath(
            AppDomain.CurrentDomain.BaseDirectory,
            "SomePluginAssemblies")
        .AddClasses()
        .AsImplementedInterfaces()
        .WithTransientLifetime());
} Code Example: Using Autofac in C# to Scan Autofac provides a similar capability with its class, allowing us to scan and register assemblies dynamically. We can use the method to achieve this. AssemblyFinder RegisterAssemblyTypes public void ConfigureContainer(ContainerBuilder builder)
{
    var assemblyFinder = new AssemblyFinder();
    var pluginAssemblies = assemblyFinder.GetAssembliesInFolder("SomePluginAssemblies");

    builder.RegisterAssemblyTypes(pluginAssemblies)
        .AsImplementedInterfaces()
        .InstancePerLifetimeScope();
} Wrapping Up Scrutor vs Autofac in C# Throughout this article, we looked at a comparison of Scrutor and Autofac in C# with the goal of understanding the differences between these two dependency injection frameworks in C#. We explored their features, advantages, and use cases through code examples to give readers a clear understanding of how they work in practice. When choosing between Scrutor vs Autofac in C#, it is important to consider factors such as project complexity, performance needs, community support, and personal familiarity with the frameworks. Scrutor’s simplicity and flexibility make it a good choice for small to medium-sized projects or situations where rapid development and convention-based registration are preferred. Autofac, with its advanced features and mature ecosystem, is well-suited for complex enterprise-level applications that require extensive customization and fine-grained control over the dependency injection process. In the end, you’ll want to work with your team to decide what’s a better fit. But either of these two options is likely going to be better than no dependency injection at all! If you found this useful and you’re looking for more learning opportunities, consider and check out my ! subscribing to my free weekly software engineering newsletter free videos on YouTube Also published here.

Everything You Need To Know About Scrutor vs Autofac in C#

The United States v Meta Platforms Court Filing October 24, 2023 is part of . You can jump to any part in this filing . This is part 43 of 100. HackerNoon’s Legal PDF Series here X. META CONTINUES TO EXPAND AND INTRODUCE NEW PLATFORMS 836. Meta has indicated [Redacted] that it plans to expand its presence in the Virtual Reality (VR) arena. 837. Virtual Reality is a new way to interact with computers wherein a user’s body is virtually placed into a 3D digital world that they can control by moving their body as though in the real world. 838. Meta first ventured into virtual reality when, in 2014, it purchased VR headset manufacturer Oculus. Meta has since developed a flagship VR Social Media Platform called “Horizon Worlds.” 839. In May 2022, the organization SumOfUs (now called Eko), released a report documenting the harms it found on Horizon Worlds, including harassment and abuse. 840. On March 8, 2023, the Center for Countering Digital Hate published a report about bullying, sexual harassment of minors, and harmful content on Horizon Worlds. 841. As of April 2023, Meta made Horizon Worlds available to young users between the ages of 13 to 17. 842. The Filing States have attempted to investigate Meta’s actions in the VR space, specifically by issuing Civil Investigative Demands on June 7, 2023, requesting information about minors on Horizon Worlds, including users under age 13. 843. To date, Meta has not responded to the Filing States’ requests for information and documents on this topic. 844. Upon information and belief, Meta is developing and deploying new features on its nascent virtual reality Platforms such as Horizon Worlds, which users may link to their accounts on Facebook and Instagram. 845. Upon information and belief, Meta’s conduct in the VR space may create harm to minors such that it constitutes violations of states’ consumer protection laws and yield further violations under COPPA. Continue Reading . Here About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case 4:23-cv-05448 retrieved on October 25, 2023, from is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. Washingtonpost.com

On Virtual Harassment: Meta's VR Expansion Faces Regulatory Scrutiny 

SEC v. Binance Court Filing, retrieved on June 5, 2023 is part of . You can jump to any part in this filing . This is part 21 of 69. HackerNoon’s Legal PDF Series here FACTS III. UNDER ZHAO’S CONTROL, BINANCE PROVIDED EXCHANGE, BROKERDEALER, AND CLEARING AGENCY SERVICES TO U.S. INVESTORS THROUGH THE BINANCE.COM PLATFORM. E. Zhao and Binance Actively Solicited Investors in the United States to Trade Crypto Assets on the Binance.com Platform. i. Binance Marketed its Services Worldwide, Including Specifically to U.S. Customers. 104. At least since the launch of the Binance.com Platform in 2017, Binance has regularly solicited customers in the United States—at first overtly and later furtively—to transact in crypto asset securities. Throughout, it has held itself out as being in the business of effecting transactions in many different crypto assets offered and sold as securities. It has engaged in this solicitation on a worldwide basis, including through its website, blog posts, and social media. 105. Among other things, Binance’s website has solicited “investors” and “traders” to “buy and sell crypto in minutes,” inviting them to “Trade. Anywhere.” Binance advertises the Binance.com Platform on its social media accounts, including on Facebook, Twitter, and Reddit, where it collectively has over 12 million followers, many of whom reside in the United States. 106. From the Binance.com Platform’s launch until at least September 2019, Binance overtly marketed its services to all customers and imposed no restrictions whatsoever on the ability of U.S. persons to buy, sell, and trade crypto assets on the Binance.com Platform. During this period, Binance opened tens of thousands of accounts for customers who submitted “Know Your Customer” (“KYC”) identity verification information that indicated they were based in the United States or who accessed the platform via Internet Protocol (“IP”) addresses indicating that they were physically located in the United States. Binance, and Zhao as its control person, knew that U.S. persons transacted on the Binance.com Platform. 107. In addition, until at least August 2021, Binance did not require customers whose accounts were limited to withdrawing two bitcoin per day to submit any KYC information, allowing those investors to bypass well-recognized international anti-money laundering restrictions and disclosures when seeking to open accounts on the Binance.com Platform. 108. Zhao and Binance regularly tracked customer activity on the Binance.com Platform and were thus aware that U.S. customers made up a substantial portion of Binance’s business. For example, in an August 2019 internal presentation, Binance estimated that the Binance.com Platform had over 1.47 million customers in the United States. 109. Moreover, by 2019, Binance had over 3,500 U.S. customers who were largevolume traders that Binance referred to as “VIPs.” These U.S. customers were important to Binance not only because they directly produced substantial revenues, but also because they provided substantial liquidity on the Binance.com Platform, which in turn encouraged other investors to trade on the platform. ii. Zhao and Binance Developed a Plan to Evade U.S. Legal Scrutiny While Continuing to Profit from U.S. Investors. 110. Zhao and Binance understood that they were operating the Binance.com Platform in violation of numerous U.S. laws, including the federal securities laws, and that these ongoing violations presented existential risks to their business. 111. As Binance’s CCO bluntly admitted to another Binance compliance officer in December 2018, (Emphasis added.) “we are operating as a fking unlicensed securities exchange in the USA bro.” 112. In 2018, Zhao and Binance hired several advisors to advise them on managing their U.S. legal exposure. One of these advisors was a consultant who operated a crypto asset trading firm in the United States (“Binance Consultant”). In November 2018, the Binance Consultant proposed a plan to Zhao and Binance that involved the creation of a U.S. entity, which the Binance Consultant at the time dubbed the “Tai Chi” entity (“Tai Chi Plan”). 113. In presentations shared with Zhao and other Binance senior officials in November 2018, the Binance Consultant warned against Binance continuing the “status quo” of unrestricted U.S. customer access to the Binance.com Platform, dubbing this a “high” risk due to potential U.S. “regulatory actions,” including actions by the SEC with respect to the “[i]ssuance of BNB to US Persons” and “for [operating an] unregistered securities brokerage.” 114. The Binance Consultant then discussed two alternative approaches for Zhao and Binance to consider. First, he discussed what he described as a “low” risk approach of “[a]ctive outreach to regulators and resolve all potential issues,” but ultimately advised against this approach because, among other things, “settlement costs can be substantial” and could result in the “complete loss of the US market during the settlement process.” 115. Second, the Binance Consultant described a “moderate” risk approach in which Binance would establish a U.S. entity—the Tai Chi entity—that “will become the target of all built-up enforcement tensions,” “ , and built-up enforcement tensions,” and The Binance Consultant recommended that Zhao and Binance adopt this approach, known as the Tai Chi Plan. reveal, retard resolve “[i]nsulate Binance from legacy and future liabilities.” 116. To implement the Tai Chi Plan, the Binance Consultant recommended that Binance brand a U.S. entity a Binance entity through a “franchise model” that would rely on Binance’s technology “by visualizing Binance as a technology vendor.” 117. He further recommended that Binance provide liquidity and market access from the Binance.com Platform to the proposed U.S. crypto asset platform established by the Tai Chi entity “through either affiliated . . . or contracted market makers.” 118. The Binance Consultant touted this approach as both “maintaining functional access to the US market,” and providing “[l]icense and services fees paid by the US Service Company to Binance” that “are functionally US-sourced trading fees.” 119. As another benefit to Binance, the Binance Consultant further recommended that Binance use the Tai Chi entity’s OTC trading services to provide “functional fiat capacity” – i.e., Binance could serve as an OTC counterparty on the U.S. platform to sell crypto assets for fiat currency, thereby giving Binance ready access to fiat currency without having to separately establish a bank account. 120. In addition, the Binance Consultant recommended steps to “insulate Binance from US Enforcement.” Those steps included having “[k]ey Binance personnel continue to operate from non-US locations to avoid enforcement risk” and ensuring that “[c]ryptocurrency wallets and key servers continue to be hosted at non-US locations to avoid asset forfeiture.” 121. As to the SEC, the Binance Consultant also recommended that, ” the Tai Chi entity should “release a long and detailed Howey Test Asset-Evaluation Framework … to show Howey test sophistication” and then engage with the SEC to discuss the “formation or acquisition of a broker/dealer or alternative trading system (ATS), (Emphasis added.) “just for publicity, with no expectation of success and solely to pause potential enforcement efforts.” 122. The Binance Consultant also recommended that Binance take steps to “reduce the attractiveness of enforcement” by U.S. regulators concerning the Binance.com Platform. This included publicly “restrict[ing] US persons’ access to the main Binance site” while privately encouraging U.S. customers to bypass these restrictions through the “strategic treatment” of virtual private networks (“VPNs”) that would disguise their locations and thereby “minimize [the] economic impact” of Binance’s public proclamations that it was prohibiting U.S investors on the platform. 123. Longer term, the Binance Consultant recommended the “[e]ventual integration with Binance” by “acquir[ing] the US operation at a nominal price and re-arrang[ing] its leadership when it has served its purposes.” 124. After considering the Tai Chi Plan, Zhao informed the Binance Consultant that Binance had also talked to U.S. law firms that proposed “a more conservative approach” that was “probably safer for now.” But Zhao made clear that he would “still very much like to continue to work with” the Binance Consultant, explaining, “There are elements from both of your proposals[] we may combine.” Zhao further noted that “having [a U.S. law firm] behind us reduces the personal exposure you take on as well.” Finally, Zhao emphasized to the Binance Consultant that they “should work together as a team.” iii. Consistent with the Tai Chi Plan, Binance Encouraged and Assisted U.S. Customers to Circumvent Binance’s Supposed Restrictions. 125. In fact, Binance implemented much of the Tai Chi Plan. In addition to creating BAM Trading and the Binance.US Platform, Zhao and Binance implemented policies and controls to give the impression that the Binance.com Platform was blocking U.S. customers while at the same time secretly subverting those controls. 126. On June 14, 2019, Binance updated the Binance.com Platform’s “Terms of Use” to provide—for the first time—that U.S. customers were not permitted to trade on the Binance.com Platform. Binance further announced that it would begin implementing measures to block U.S. customers from trading or depositing assets on the platform after 90 days. Zhao and Binance timed this announcement to coincide with its announcement that an ostensibly independent U.S. entity, BAM Trading, would soon launch the Binance.US Platform. 127. But Zhao and Binance were unwilling to risk losing all of Binance’s U.S business—particularly its VIP U.S. customers—on the well-established and more liquid Binance.com Platform. And so Zhao and Binance engaged in widespread covert efforts to permit U.S. customers to continue to trade on the platform. 128. First, Zhao directed Binance to implement a plan to encourage customers to circumvent Binance’s geographic blocking of U.S.-based IP addresses by using a VPN service to conceal their U.S. location. Second, Zhao directed Binance to encourage certain U.S.-based VIP customers to circumvent the new KYC restrictions by submitting updated KYC information that omitted any U.S. nexus. 129. As Zhao explained in a June 9, 2019 weekly meeting of senior Binance officials: We don’t want to lose all the VIPs which actually contribute to quite a large number of volume. So ideally we would help them facilitate registering companies or moving the trading volume offshore in some way—in a way that we can accept without them being labeled completely U.S. to us. 130. Binance implemented Zhao’s instructions. On or about June 13, 2019, a Binance employee who belonged to a team that managed VIP customers messaged Zhao and other senior Binance officials, “We contacted 16 US top clients so far, some [of] them already have offshore entity, they said they can underst[and] and they are happy that we can get ahead of that.” A few days later, Binance’s Chief Marketing Officer reported that the team had reached out to the top 22 U.S. VIP customers and that 19 had “already agreed to change KYC, or change their IP.” 131. With respect to its thousands of other VIP U.S. customers, Zhao explained in a June 24, 2019 meeting with other Binance senior officials: We do need to let users know that they can change their KYC on Binance.com and continue to use it. But the message, the message needs to be finessed very carefully because whatever we send will be public. We cannot be held accountable for it. 132. The following day, Zhao met with other senior Binance officials to discuss their VIP U.S. customers, and Zhao provided further instructions on crafting the message to customers about changing IP addresses or KYC documentation. During the meeting, the Binance CCO noted that Binance would engage in “the international circumvention of KYC,” and Zhao affirmed that his “goal” was “to reduce the losses to ourselves, and at the same time to make the U.S. regulatory authorities not trouble us.” 133. To that end, the Binance CCO drafted a “VIP Handling” document, dated June 26, 2019, which included draft emails to send to VIP customers who were identified as having U.S. KYC documents or U.S. IP addresses, along with instructions to Binance employees about messaging to customers. For customers with U.S. KYC documents, the “VIP Handling” document instructed Binance employees to make sure the U.S. customers opened new accounts “with no US documents allowed” and to inform the customer “to keep this confidential.” 134. For customers with U.S. IP addresses, the “VIP Handling” document instructed Binance employees to “[i]nform [the] user that the reason why he/she can’t use our www.binance.com is because his/her IP is detected as US IP; if user doesn’t get the hint, indicate that IP is the sole reason why he/she can’t use .com.” The document further instructed Binance employees not to “explicitly instruct user to use different IP. We cannot teach users how to circumvent controls. If they figure it out on their own, it[’]s fine.” 135. Binance continued to circumvent these controls for several years. On February 12, 2020, for example, a Binance employee asked the Binance CCO whether it was still a “hard requirement” for Binance to block U.S. customers, and the Binance CCO replied: 136. Similarly, on July 15, 2020, a Binance VIP customer team member asked the Binance CCO how they could onboard a large U.S. customer. The Binance CCO replied, “[T]he best way I can think of is to onboard with US exchange … but we let them trade on .com through a special arrangement.” He further explained, “[W]e ask them to onboard with US, and then if their volume is really very big … we will push hard on .com side to accept it on an exceptional basis … we always have a way for whales … either we do it, or [a competitor crypto trading platform] does it.” (“Whales” is a market term referring to large volume investors.) 137. The Binance CCO further admitted, “CZ will definitely agree to this lol … I have been briefed by top management to always find a way to support biz.” 138. Moreover, despite statements about its compliance efforts, Binance did not even require all customers to submit KYC documents until after August 2021. Around that time, Binance had over 62 million worldwide customers, but only approximately 25 million had submitted KYC documentation. Thereafter, more Binance.com Platform customers began submitting KYC documentation, but Binance continued to have large numbers of customers that still had not done so at least through mid-2022. 139. Binance’s plan to retain lucrative U.S. investors while pretending to restrict them was a success. For example, a March 2020 internal Binance presentation reported that the Binance.com Platform still had approximately 159 U.S. VIP customers, representing almost 70 percent of all global VIP trading volume. Similarly, in May 2021—two years after the launch of the Binance.US Platform—an internal Binance presentation reported that U.S. VIP customers still accounted for over 63 percent of the Binance.com Platform’s VIP customer trading volume. 140. U.S. customer trading volume on the Binance.com Platform included substantial activity trading in crypto asset securities. For example, between January 2019 and September 2021, over 47,000 U.S. investors traded in BNB on the Binance.com Platform. Continue Reading . Here About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case 1:23-cv-01599 retrieved on September 6, 2023, from is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. docdroid.net

How CZ and Binance Solicited U.S. Investors while Evading Regulatory Scrutiny 

রেগুলেটরি স্ক্রুটিনি এড়ানোর সময় কীভাবে CZ এবং Binance মার্কিন বিনিয়োগকারীদের অনুরোধ করেছিল

Wie CZ und Binance US-Investoren anwarben und sich gleichzeitig der behördlichen Kontrolle entzogen

Cómo CZ y Binance solicitaron inversores estadounidenses mientras evadían el escrutinio regulatorio

Comment CZ et Binance ont sollicité des investisseurs américains tout en évitant le contrôle réglementaire

विनियामक जांच से बचते हुए सीजेड और बिनेंस ने अमेरिकी निवेशकों से कैसे आग्रह किया

CZとバイナンスはどのようにして規制当局の監視を回避しながら米国の投資家を勧誘したのか

CZ와 바이낸스가 규제 조사를 피하면서 미국 투자자를 모집한 방법

Como CZ e Binance solicitaram investidores dos EUA enquanto evitavam o escrutínio regulatório

Как CZ и Binance привлекли инвесторов из США, уклоняясь от контроля со стороны регулирующих органов

CZ ve Binance Düzenleyici İncelemelerden Kaçarken ABD'li Yatırımcılara Nasıl Talepte Bulundu?

Cách CZ và Binance thu hút các nhà đầu tư Hoa Kỳ trong khi trốn tránh sự giám sát của cơ quan quản lý

CZ 和币安如何在逃避监管审查的同时招揽美国投资者

DOE vs. Github (amended complaint) Court Filing (Redacted), June 8, 2023 is part of . You can jump to any part in this filing . This is part 13 of 38. HackerNoon’s Legal PDF Series here VII. FACTUAL ALLEGATIONS A. Introduction 47. This class action against Defendants concerns an OpenAI product called Codex and a GitHub product called Copilot. 48. OpenAI began development of Codex sometime after OpenAI was founded in December 2015 and released Codex on a limited basis in August 2021. 49. GitHub began development of Copilot sometime in 2019, released it on a limited basis in June 2021, and released it as a paid subscription service in June 2022. 50. Codex and Copilot are assistive AI-based systems offered to software programmers. These AI systems are each trained on a large corpus of publicly accessible software code and other materials, including all the Licensed Materials. Defendants describe these products as making coding easier by accepting a code “prompt” from a programmer and emitting a possible completion of that code, which is referred to herein as Output, as set forth above. Defendants claim Codex and Copilot do not retain copies of the materials they are trained on. In practice, however, the Output is often a near-identical reproduction of code from the training data. 51. Codex and Copilot are related. Copilot is a joint venture between GitHub and OpenAI. Codex is a standalone product released by OpenAI that also “powers GitHub Copilot, which [OpenAI] built and launched in partnership with GitHub.”[5] “GitHub Copilot uses the OpenAI Codex to suggest code and entire functions in real-time, right from your editor.”[6] The version of Codex used to power Copilot is modified from OpenAI’s standalone version. Defendants have kept secret the details of Codex’s modifications and its integration into or interaction with Copilot. [5] See . https://openai.com/blog/openai-codex/ [6] See . https://github.com/features/copilot/ Continue Reading . Here About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case 4:22-cv-06823-JST retrieved on August 26, 2023, from is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. Storage Courtlistener

Factual Allegations: Open AI's Codex and Copilot Under Scrutiny 

There are mixed feelings about the US Economy currently. On one hand, the US dollar terrain against six major currencies, marking a three-week high. These positive gains came against the backdrop of relatively strong data on the US manufacturing and construction sectors. gained On the other hand, Fitch decided to the US Government credit rating from AAA to AA+, citing probable fiscal challenges over the next three years. The decision was (not surprisingly) met with criticism from the US Government, with Treasury Secretary Janet Yellen terming it ”'arbitrary and based on outdated data”. downgrade SEC Back on the Heels of Crypto In earlier letters, we've again and again the likelihood of the SEC's crusade against crypto to continue and this the SEC allegedly communicated to Coinbase that all other assets than were to be considered securities. stated BTC The story does not appear all too credible although Brian Armstrong made comments to the . Financial Times Amidst this development, the SEC has also Richard Heart and 'three unincorporated entities that he controls, Hex, PulseChain, and PulseX,' for raising over $1 billion by offering unregistered crypto asset securities. sued DeFi Security in Question The security of the DeFi ecosystem has once again come into question following the exploit of Curve Finance, one of the pioneer DeFi protocols, resulting in an $47 million in losses withdrawn from several stablepools. estimated While the damage has since been contained, there is still a looming arising from Curve's founder, Michael Egorov's $100 million CRV-backed loan that could potentially be liquidated should the underlying collateral fall significantly in value. risk Noteworthy Mentions Crypto VC Behavior Of 2023: Weathering The Winter The crypto VC landscape has continued to face headwinds this year, with more investors shying away from the digital asset industry. In our latest research piece, we highlight some of the major trends, including where VCs are investing funds and which projects are attracting capital, among other behaviors. For more context, check out the full article . here Industry Shakers Tether Reports $850 Million Q2 Profit Tether Holdings Limited, the issuer of the , reported a Q2 profit of $850 million, resulting in total excess reserves of $3.3 billion. According to a spokesperson for Tether, "The $850 million represents the retained profits of this quarter, which have contributed to increasing Tether's excess reserves. It's basically additional capital sitting in the company to further strengthen Tether.” USDT stablecoin Sequoia slashes its crypto fund by 66% after industry collapses Sequoia Capital recently made adjustments to its cryptocurrency fund, reducing its size from $585 million to $200 million. This decision comes amidst a liquidity crunch and a strategic pivot towards smaller players in the crypto market. The move was aimed at better reflecting the changing market conditions and aligning the fund's strategy with the evolving landscape of the cryptocurrency industry. FTX Plans to Restart Crypto Exchange for International Customers Defunct crypto exchange FTX has put forth a proposal to categorize its creditors into distinct classes of claimants, while also presenting an option for one class of claimants to potentially relaunch the FTX exchange with the involvement of third-party investors, provided the group reaches an agreement. Also published here.

Sideways Crypto Trading Persists Amid US Economy Scrutiny

We all have been observing the immense rise of a new token, a new meme token, to be precise. Yes, the Pepe coin, a meme that is supposed to make the time of Doge-themed meme coins end. Let me recall how it all started though. On April 14th, Pepe went live with a Twitter post. Source: https://twitter.com/pepecoineth/status/1646978289267769345 A couple of days later, the number of PEPE holders surpassed 1,000, and the market capitalization skyrocketed. The token price started growing, too. Source: https://coinmarketcap.com/currencies/pepe/ New tweets appear in mass, all of them are provocative, angry, and claim to end the time of Doge-themed meme coins. Pepe is celebrating, and everybody is counting how much those investors earned who bought Pepe when it was launched. But indeed, who were those people? The First Red Flag Here, the first red flags appear to me. Source: https://etherscan.io/token/0x6982508145454ce325ddbe47a25d4ec3d2311933?a=0x4a2c786651229175407d3a2d405d1998bcf40614 The very first wallet involved in the Pepe transactions purchased PEPE as soon as it went live, the guy bought billions of Pepe. Now, it still holds a lot of tokens. Source: https://etherscan.io/token/0x6982508145454ce325ddbe47a25d4ec3d2311933?a=0x4a2c786651229175407d3a2d405d1998bcf40614 Now, let us think: a meme token with almost no value, no team, and even no popularity: how much one needs to buy to pump its price? It looks like a well thought scheme to me. Somebody from the team or somebody involved in the scheme purchased this immense amount of Pepe tokens to pump its price as soon as the famous Tweet appeared. The token is not listed anywhere yet, but its price has started growing, and it is not surprising considering the immense purchase. (By the way, this wallet is not the only one that purchased billions of Pepe immediately when the token was launched). Pepe Popularity Is Growing but Claiming Profits Is Impossible Meanwhile, Twitter also does its job, and I shall admit that this job is great indeed. More people get to know about a new meme coin (meanwhile, there are plenty of new meme projects being launched but they are left without attention), and start buying. Pepe continues growing in value, new billionaires are supposedly made with the new meme coin. But while users are counting the profits of those who have bought Pepe, they forget about one major detail: liquidity. Yep, the price of a new coin can surge as high as one can imagine, but if there is no liquidity, investors cannot cash out their profits. So does Pepe ensure enough liquidity to allow investors to cash out their earnings? It looks like no. While the Pepe market capitalization reached over $150 mln, the . It means that at that time (5 days after the token launch), those who have supposedly earned millions could not cash them out. coin liquidity pool on Uniswap was just slightly over $3 mln Now, the token is being listed on major exchanges such as Huobi, Binance, etc., so eventually, the liquidity issue may be solved. However, those who didn’t manage to cash their earnings out will have to deal with lower returns than they expected. The Contract Looks Suspicious Meanwhile, another red flag appears. When checking the contract address on the website, it was detected that there are some details that normally would alarm investors. GoPuls Labs Source: https://gopluslabs.io/token-security/1/0x6982508145454Ce325dDbE47a25d4ec3d2311933 Coinmarketcap where the token was listed already publishes a warning for investors. And the Pepe team reacts immediately, by pointing out that the contract has been fixed, and the coin rank provided by Coinmakretcap is incorrect. Source: https://twitter.com/pepecoineth/status/1649915486493200385 And indeed, if you check the contract address on the GoPlus Labs website, the tax issue doesn’t appear anymore. However, the blacklisting function is there, as well as other issues. Even though Coinmarketcap removed the warning, to me, it still remains unclear who is lying here and why everybody suddenly got silent about it. Eventually, are the main token holders going to dump the token in a well-prepared honeypot scam? Time will show, and for now, just have a look at how the transactions are performed by the wallet that bought a huge number of Pepe when the token was launched: Source: https://etherscan.io/token/0x6982508145454ce325ddbe47a25d4ec3d2311933?a=0x4a2c786651229175407d3a2d405d1998bcf40614#tokenAnalytics And see how the token price is moving. Try to imagine what will happen if other major token holders start dumping the token. Here, another question arises: how many wallets are among the major Pepe holders? Let’s have a look at this data, too. Major Pepe Holders So, how many wallets are the major Pepe holders? Source: https://www.coincarp.com/currencies/pepe/richlist/ More details are provided by Etherscan, as usual. Here, we can see that the major holders are the biggest exchanges. Indeed, Pepe has been listed on many of them recently. Source: https://etherscan.io/token/0x6982508145454ce325ddbe47a25d4ec3d2311933#balances However, if you check addresses that do not belong to the exchanges, suspicions arise again. Have a look at the addresses that do not belong to exchanges. Source: https://etherscan.io/token/0x6982508145454ce325ddbe47a25d4ec3d2311933?a=0x339b07af597a2c6128d067633611baf3f0725b1a Source: https://etherscan.io/token/0x6982508145454ce325ddbe47a25d4ec3d2311933?a=0x339b07af597a2c6128d067633611baf3f0725b1a They have bought immense numbers of Pepe asap after the token launch and are either inactive or very moderately active. What Does the Future Hold for Pepe? What will happen if they dump the coin? I believe that the major event is coming now when Pepe was listed on the main exchanges. Normally, the token price shall surge, and thus, the perfect point for a big dump is approaching if only the major holders decide, for some reason, to keep the token alive or if the community support appears to be strong enough for the token to survive. What will happen? Observing for now. But with all the controversies, one thing is clear: the power of Twitter in the contemporary world is immense. Even though there are plenty of red flags, Pepe continues to attract attention. Sincerely, Pepe looks cool, and whoever is responsible for Twitter shilling is doing a great job, so I hope this meme will survive.

Twitter and Red Flags - Will the Pepe Coin Survive Scrutiny?

I began to scrutinize the man closely

It seems like the Initial Coin Offering (ICO) mania of 2017 (and early 2018) is beginning to skitter to a halt. While it may have been possible to raise millions for a cryptocurrency based on damn near anything last year, the landscape is changing. Both retail investors and regulators are smartening up. Retail investors are more weary, and regulators are coming down on ICOs that are obviously taking advantage of an unregulated fundraising mechanism. The increased scrutiny that ICOs undergo helps weed out projects that shouldn’t be launching in the first place, and as an unexpected byproduct: sets a higher standard of quality for future blockchain projects. As regulation tightens its grip, founders find use cases that hit larger demographics, and token utilities with, well, more utility. A new breed of token sales I believe we’re starting to see a positive trend in the quality of token sales in 2018. It’s harder to run a token generation event now, so only the companies that genuinely need blockchain for their product/service to work are considering it. Not to long ago, it was easy to just throw “Crypto” or “Blockchain” in the name of your company and launch a token sale. It’s my belief, and my hope, that this time is over. Kik, the messaging application, raised $100 million in an ICO last year. Now, their CEO Ted Livingston is warning other would be token offerers that implementing Blockchain into a business is harder than it looks. So difficult in fact that the company issued a statement saying that they will no longer be tying dates to the development milestones they plan to hit- they’d rather not create expectations over the possibility of failing to meet them. “We decided within the company that there are so many unknowns within crypto, we don’t put out dates anymore, but, as soon as possible,” — Ted Livingston, CEO of Kik The only intention Kik has is to create a token that can be used as a virtual currency within its application, there’s nothing innovative there. The CEO practically said that launching their token was a cash grab. Something they needed to do to compete with larger companies like Facebook and Google. It’s not surprising that they bit off more than they can chew. Companies like Kik may be realizing that blockchain isn’t as alluring as it seemed, but there is still a genuine use case for blockchain in improving processes. So, where are the killer blockchain applications we’ve all been waiting for? The biggest roadblock to industry-wide innovation.. The ICOs I’ve seen successfully raise money in the past few months seem to be taking a different approach than their predecessors. More and more companies are asking for a reasonable amount of capital in their token sales, and the use cases are getting more realistic. 2017 saw a lot of ICOs that made large claims, stating use cases that required participation (from more organizations than was feasible) to succeed. I’m excited to see what the futures holds for the ICO environment, I genuinely believe the next wave of blockchain projects will leave a more lasting impression on the niches they’re targeting than the last. To succeed in this environment, you have to convince investors who, at this point, have already been burned by the ICO craze. Some even several times over. Almost any process or industry that is filled with middlemen and intermediaries can be improved. Any use case where there is an organization or individual who requires trust from both sides of a transaction. This is especially the case in antiquated industries. I received a Lean Six Sigma certification in 2014. As a part of my studies, I had to find a company and examine their processes, to find one that I could make more efficient. Once identified, I had to craft a plan to improve the process, and present it to the company. The company I worked with was an oil refinery in Arizona. They put me in the most exciting department of the company, accounting. It was my job to look at how they managed accounting, and find ways to cut costs. I looked into their flow of information: how accounting gathered all the information they needed to do their job. What I found was pretty surprising, and was the conceptual of a valuable lesson I learned. first lecture The oil refinery managed the entire process on paper. . Everything Photo by on Sear Greyson Unsplash I can’t remember the exact details, but they had a ridiculous amount of employees on salary whose only job was to collect and validate the data, that was gathered by another person — whose only job was, you guessed it, gathering data. Maybe it was naive, but I was stoked. I thought I had found overlooked flaws that I could easily address with some automated programs. This certification is going to be a breeze, I thought. I wrote up a proposal on how to automate their data aggregation and parts of the accounting process. It could have saved them millions over the following years and cost a fraction of that to implement. When I submitted the proposal, they were excited, to my face. Fast forward a few months, however, and nothing about their process had changed. They didn’t do anything, I outlined every step necessary and how to do it in a damn binder. I even put those little plastic colored tabs to mark the different sections, it was glorious. At the time, it was my magnum opus. The lesson I ended up taking away from that experience, but not really comprehending until later in my life, was this: If a process sucks and has sucked for a long time, but the key stakeholders are making money, they’re not going to care about improving it. Aka, the “If it ain’t broke don’t fix it” approach. The biggest roadblock for industry-wide innovation — or even innovation within a process as specific as accounting in an oil refinery — isn’t technology. It’s people, people who by nature resist change, even when it benefits them. Ripe for Disruption: industries on the brink of change These antiquated industries/processes are precisely where I believe blockchain should be implemented. Let’s take a look at some processes and industries that need improving, and some that are in process of improving already. Supply Chain Supply chain management requires cooperation between several different parties, to ensure that products get from point A to point B. In any given supply chain, inventory is likely to change hands several times, each transfer requiring signing off on paper documents to confirm each party has done their part. The ocean freight industry for example accounts for 90% of global trade, and is still managed almost entirely with paper documents. The industry has been around for so long, and is profitable enough for the current stakeholders — for there to be no need to innovate. IBM recently announced that they’ve implemented blockchain to handle all of their supply chain management. This is a near perfect example of a real-world application of blockchain to improve processes. IBM clearly has a strong understanding of blockchain and where it’s best suited for use. The infographic below was taken from a recent study they published on the inefficiencies still evident in supply chain management. Infographic courtesy of IBM, “The Paper Trail of a Supply Container” Let’s hope that IBM is the first of many established companies to start utilizing distributed ledgers where they can bring impact. Mortgage Processing The mortgage application process has to be one of the most paper-heavy, tedious, and time consuming processes I’ve ever come across. It’s borderline insane. Another classic case of key stakeholders not being incentivized enough to improve the process.Which is shocking seeing as this is a process that almost everyone living in most first world countries has to go through at some point in their life. Buying a home is a cultural milestone, a new chapter in a persons life, a coming of age ceremony — it’s something you update your Facebook status about. It hits a pretty gargantuan demographic in the U.S. and Canada alone, The amount of new mortgage debt to be taken out in 2018 is estimated to be around $37 trillion USD. I didn’t even know mortgages were global until I started reading about . To be honest, the mortgage industry research I tout as if I did it myself was just pulled from their white paper. globally Block66 A mortgage application can take anywhere from 24–45 days to process. In that time, the individual applying for the loan fills out paperwork with sensitive personal data — which is then passed on to several different underwriters who verify the information provided. Then it goes to banks, a few more different stakeholders, and finally back to the mortgage broker who shares the results with his or her client. Block66 completely automates this process, and claim to be able to cut the time needed to complete it to 48 hours. Going back to my Lean Six Sigma days, I got really excited by process improvement applied the mortgage industry, it seems like a no brainer. I hopped in their and managed to speak directly with the CEO. They’ve already locked in some pretty insane partnerships including Ethos and Civic, along with the partnerships they’re bringing on Shingo Lavine (CEO of Ethos) as an advisor. This is one of those projects that gets me excited, because it checks all of my boxes. The development team comes from other blockchain projects in similar fields, the utility is strong, and the advisors/partnerships they’re starting to form are going to put them in a great position. official telegram channel The other blockchain companes in the space are addressing the problem from a different angle. Some companies will allow you to purchase homes with crypto, sure, but you have to put the entire payment down upfront. What percentage of the global population can afford to put a $1million USD + down payment upfront? Block66 has the potential to partner up with the platforms that facilitate crypto real estate purchases, and create a reasonable and cost effective way for everyday people to purchase homes with cryptocurrency. Digital Marketing I found my humble beginnings as a digital marketer running a boutique digital agency in Los Angeles. I’m well aware of the inefficiencies prevalent in digital advertising, and the frustrations they cause. The metrics we use for tracking Return on Investment of digital advertising campaigns are inefficient at tracking results. Cost per click can be misleading, and who the hell decided that cost per thousand clicks was a valuable metric? As a company, I don’t care about clicks, I care about conversions. Adding more metrics into the fold just gives marketing managers more to talk about when they’re called to meetings, many of the metrics currently used don’t bring a large amount of value. Don’t get me wrong, there are age-old classics that still reflect the efficacy of marketing campaigns (love that conversion rate). But most metrics just add a layer of confusion for those not adept with the terminology, and give bad actors more room to manipulate these metrics. One company attempting to address this issue is (BAT), but they concluded their ICO in 2017 so they don’t count for the sake of this article. A more recent player attempting to disrupt the digital marketing industry is . While BAT attempts to directly address the problem at hand, Plentix provides an alternative to the current inefficient methods. They’ve created a completely decentralized referral program, similar to what Uber users to acquire new customers. They’ve created a system for referral marketing, and decentralized it- opening it up to the public for users to see all the possible referrals they can use, and opening it up to the businesses so that they can develop their own referral programs with whatever parameters they like. One of the benefits of blockchain in improving processes is cost reduction, I have no idea how much they’ll charge clients, but I’d imagine it’ll be less than traditional competitors. They’re starting their private sale pretty soon and have started building out a , I’ll be paying close attention. Basic Attention Token Plentix whitelist Data Acquisition This is one of those processes that no one really thinks about except for the people whose job it is to think about it. I personally didn’t really think about it until I heard about , who finished their ICO earlier this year. They caught my attention because out of all the ICOs that have launched in 2018, they’ve brought their investors one of the largest return on investments. When I saw the success its’ had, I took a dive into the industry to see what about their solution is so disruptive. Nucleus Vision Nucleus Vision automatically gathers customer data to benefit both consumers and businesses. Consumers benefit from getting a more custom-tailored solution to their retail needs, and businesses benefit by being able to provide this solution at all. Customer data acquisition usually involves a tedious surveying process, sent out over email or even done in person with paper forms. We give out a lot of data to social media platforms we use, but those platforms don’t speak to consumer brands about how to use that data to benefit us. At the moment that data is only used to benefit the advertiser with increased targeting capabilities. Takeaways The increase in scrutiny and regulation may make the lives of would-be founders more difficult, but it also helps weed out the bad projects. If we keep seeing projects like the ones above, projects that are addressing real-world, feasible, and impactful use cases, I think the future is brighter than current sentiment would lead you to believe. The inefficient industries or processes these companies are addressing have a lot of room for improvement, and its likely that stakeholders involved will have that , “If it ain’t broke, don’t fix it”, mentality. But, you can only try and hold the floodgates of change shut for so long. Eventually, they break and take you along for the ride.

Why Increased Scrutiny is Good for ICOs & the Industries they Disrupt

I caught up with a friend yesterday who is an up-and-coming in the Austin area and it turns out we are facing a lot of the same challenges in launching a new venture. We both are working to optimize processes in order to spend the most time possible on the core aspects of our firms. architect During a 2016 shareholders meeting, Elon Musk said “We’ve realized that the true problem, the true difficulty and where the greatest potential is, is building the machine that builds the machine. In other words, building the factory.” Similarly, Homebrew’s Hunter Walk has been quoted as saying “the company is the first product, and you have to be really intentional about how you build it before it’s ready to scale.” This highlights an important reality of building a great company or product: the processes and frameworks put into place will often decide the level of success achieved and those operational components should be designed with the end-goal in mind. , the best of the best almost always “perform the common uncommonly well.” As my partner Jonathan recently wrote The larger a company grows, the more difficult it becomes to put processes in place. This one is straightforward, as a begins to scale it becomes exponentially harder to move everyone in the same direction. Getting a group of 10 engineers to agree on a product development methodology is easier than asking 40 to do the same and infinitely easier than asking a team of 100 or more. This isn’t just an engineering or product problem, the same rules apply to marketing, finance, and sales. Bonus: it will make cross-functional execution that much easier. 1) Start Early: startup The best early-stage companies have an innate ability to focus when it is most difficult to do so. Early-on, startups are vulnerable to chasing shiny objects as everything feels like a big opportunity. Instead, avoid temptation and focus on executing toward one core product or market. Example tactics to accomplish this include: shorter meetings (i.e. standups), picking 2–3 metrics that are core to success (ex. contribution margin and conversion), and selecting 1–2 strategic priorities per timeframe. 2) Overly-Simplify: Be honest with yourself. One of the most effective practices I’ve seen teams use is the agile concept of a retrospective. This gives teams the chance to discuss what’s working, what isn’t and ideas for improvement. The most crucial element to this step is accountability, without it, these meetings don’t help move the company forward but instead become chances to be overly critical without inspiring action. Begin each “retro” with a review of how well the team executed on previous takeaways and keep score. 3) Scrutinize: Operations within early-stage companies often get overlooked as there are more exciting challenges to tackle. When processes are in place, no one notices because things are running smoothly and challenges do not begin to surface until later in the game. However, neglecting them is akin to puncturing a boat while it is still in port; it may leave the dock, but it won’t make the entire trip. Enjoy this post? Please share! Originally published at kevindstevens.com on September 1, 2017.

SOS: Start-Early, Overly-Simplify, Scrutinize

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Logging is essential for successful DevSecOps teams. Logs are filled with the information needed to monitor and understand systems. Tracking down a defect? Trying to understand a sudden burst in questionable logins from a new region? Need to figure out why an app is crawling? Logs are that single source of truth for understanding what’s really happening. But there’s a problem that comes along with logs: the sheer amount of data. The information logged by services and applications just keeps on growing. And growing. It doesn’t take long for it to become more — much more — than can be managed. The data becomes overwhelming. Alert fatigue sets in. Data keeps growing. Human resources can’t. But there’s hope on the horizon. Innovations in AI have revolutionized the process of continuous log monitoring. AI algorithms can analyze and detect patterns within vast datasets, translate raw logs into actionable insights, and proactively alert teams to problems — all at a scale and at higher precision to assist humans. Let’s look at 8 ways that AI can maximize the value of logs. #1: Handling massive amounts of data First, the most obvious. Cloud-native environments, with their dozens (or hundreds) of distributed components, emit a massive volume of log data. In turn, this data requires high levels of expertise to sift through and analyze it all. But most organizations already face a shortage of people with the skills needed to tease out the insights from this data. Companies could train more people — but training is slow. And the growing complexity of the data tends to outpace any new skills. Here is where AI shines: It’s a scalable way to handle log data, no matter the volume and no matter the time. Humans need breaks; they clock out for the day, get sick, take PTO, and play Galaga when bosses aren’t looking. But log data still arrives in massive volumes, regardless of the time of the day or day of the week. An AI-based system with analysis, detection, and alerting is always on. #2: Automated security and access control When dealing with logs, it’s important to protect any sensitive user information and ensure that the data is only accessible to authorized team members. SecOps managers often implement fine-grained access control to ensure that the approved team members have access to (and only to) the data or metrics intended for use. AI systems can automatically identify and redact sensitive information — such as personal identifiers, financial details, or confidential business information — from log data before it’s accessed by humans. Or, as part of automated preprocessing, AI can de-identify or mask sensitive parts of data. #3: Collating data from disparate sources Merging data from various sources is a complex task. But it’s essential for effective security and operations. When logs are properly aggregated and correlated, the resulting data and metrics can give the context needed for better visibility and better troubleshooting. But this is a menial and time-consuming task … which makes it perfect for AI. AI can automatically gather information from various sources and identify patterns within the data, making its analysis easier. AI correlates data from different sources far more efficiently than a human. Modern log analytics tools leverage AI to gather log data from cloud services and on-premises environments. Log analysis and issue resolution become proactive, preventing negative impacts on the health of applications and systems. #4: Transforming raw log data Organizations depend on skilled professionals to handle and analyze log data, yet they often face overwhelming resource constraints. This is where AI can contribute significantly, by automating repetitive tasks and enhancing human capabilities. Before analysis, log data often required cleaning and preprocessing to remove errors, duplicates, or irrelevant information. AI can automate this process, ensuring the accuracy and standardization of all the data. AI can also organize log data into clusters based on similarities or classify them into predefined categories. This helps manage data more efficiently, making it easier for humans to understand and act upon the insights derived. #5: Analyzing log data A clear use case for AI within a DevSecOps strategy is the automation of repetitive and time-consuming tasks — such as data cleaning, feature selection, and model training. With AI taking on these tasks, developers can focus on other tasks. AI can sift through a mountain of data to spot duplication and anomalies — like subtle signs of a cyberattack or unusual traffic patterns — that might easily slip past human scrutiny. This yields enhanced security and operational insights. It’s more than just about handling the volume; AI is adept at detecting patterns that are too complex or too faint for the human eye to catch. For example, let’s consider logging and monitoring for a network to catch signs of data exfiltration. This kind of anomaly might manifest as an unusually high volume of data being sent to an unfamiliar external IP address during off-hours; that’s a pattern that might not immediately raise flags for a human amid thousands of legitimate data transfers happening every day. On the other hand, an AI-based system that’s trained on vast datasets of normal and malicious network behavior can identify this subtle pattern by correlating different indicators: The timing of the data transfer
The volume of data
The destination IP address
The type of data being transferred For a human, recognizing such a complex pattern requires painstaking analysis and might be missed entirely due to the sheer volume of log data. But an AI system can continuously monitor for these patterns across the entire network, detecting potential threats with precision and speed that far surpasses human capability. #6: Reducing alert fatigue Traditional infrastructure and service monitoring solutions are notoriously noisy, often generating alerts for events that don’t signify a genuine threat. Excessive unactionable alerts lead to alert fatigue. AI-based alerting intelligently filters alerts and reduces the noise, ensuring that the alerts generated are relevant and actionable. For example, traditional monitoring can’t adjust for seasonality — so a crossed threshold in the middle of a high-season weekday afternoon gets as much attention as one in the middle of the night during what should be a slow week. AI-based alerting uses historical data to continually train its models, factoring seasonality into its baselines. The result is fewer false positives and no more alert fatigue. Of course, organizations using AI-driven alerting need to rigorously test results in order to tune specificity and sensitivity. This ensures that critical events are captured effectively. #7: Proactive monitoring Given the large amounts of data an organization generates, teams often struggle to monitor all the organization’s resources proactively. AI is well-equipped to address this issue at scale. By continuously monitoring and aggregating logs from across entire environments, an AI-based tool can identify anomalies before they become widespread, allowing teams to detect potential threats in their initial stages. For example, the threat detection and investigation from Sumo Logic provides the visibility to address advanced threats before they affect operations. AI features such as this enable real-time monitoring, alerting, and data analysis across security tools, cloud infrastructures, and SaaS applications. This enables a DevSecOps team to investigate and respond to cyber threats swiftly. #8: Efficient incident response AI-driven alerting improves incident response by facilitating automatic resource allocation and gathering contextual information about an incident. This helps identify potential security threats faster, which in turn helps organizations respond more quickly. When AI-powered logging and observability platforms provide automated remediation features, teams can connect the dots: from continuously monitored logs to incident detection to remediation playbooks. Automated playbook execution means near-immediate response to an incident, whether that’s eliminating the root cause or alerting an engineer to begin an investigation. Remember, with every delay in responding to a security incident, the window for impact widens. Minimizing that delay with AI directly minimizes the impact of an incident. Privacy concerns related to AI adoption One last note: as we’ve seen, AI shows great promise as a tool for improving logging. But remember that it’s still an emerging technology. As a recent GitLab report makes clear, there are serious privacy concerns around AI adoption. While 83% of the teams surveyed said implementing AI in their development process was essential, 79% said they were highly concerned about privacy and IP when dealing with AI. But in many business contexts, AI tools need access to that private data for analysis. So take advantage of AI, but be aware and guard against any privacy concerns. Drowning in log data? AI is here to help. Logs are crucial. They’re a rich source of data for monitoring applications and infrastructure. But the multiple data sources and volume of log data — along with the sensitivity of some of that data in the logs — lead to some big challenges in managing log data, security, and privacy. AI is here to help. Modern log management and SIEM solutions are leveraging AI to automate analysis, enhance monitoring, and improve incident response. AI is making DevSecOps more efficient. And as AI solutions evolve, their role in log analysis will only grow, offering smarter, faster insights into logs. Logging is essential for successful DevSecOps teams. Logs are filled with the information needed to monitor and understand systems. Tracking down a defect? Trying to understand a sudden burst in questionable logins from a new region? Need to figure out why an app is crawling? Logs are that single source of truth for understanding what’s really happening. filled But there’s a problem that comes along with logs: the sheer amount of data. The information logged by services and applications just keeps on growing. And growing. It doesn’t take long for it to become more — much more — than can be managed. The data becomes overwhelming. Alert fatigue sets in. Data keeps growing. Human resources can’t. But there’s hope on the horizon. Innovations in AI have revolutionized the process of continuous log monitoring . AI algorithms can analyze and detect patterns within vast datasets, translate raw logs into actionable insights, and proactively alert teams to problems — all at a scale and at higher precision to assist humans. continuous log monitoring Let’s look at 8 ways that AI can maximize the value of logs. #1: Handling massive amounts of data First, the most obvious. Cloud-native environments, with their dozens (or hundreds) of distributed components, emit a massive volume of log data. In turn, this data requires high levels of expertise to sift through and analyze it all. massive But most organizations already face a shortage of people with the skills needed to tease out the insights from this data. Companies could train more people — but training is slow. And the growing complexity of the data tends to outpace any new skills. could Here is where AI shines: It’s a scalable way to handle log data, no matter the volume and no matter the time. Humans need breaks; they clock out for the day, get sick, take PTO, and play Galaga when bosses aren’t looking . But log data still arrives in massive volumes, regardless of the time of the day or day of the week. An AI-based system with analysis, detection, and alerting is always on. play Galaga when bosses aren’t looking #2: Automated security and access control When dealing with logs, it’s important to protect any sensitive user information and ensure that the data is only accessible to authorized team members. SecOps managers often implement fine-grained access control to ensure that the approved team members have access to (and only to) the data or metrics intended for use. AI systems can automatically identify and redact sensitive information — such as personal identifiers, financial details, or confidential business information — from log data before it’s accessed by humans. Or, as part of automated preprocessing, AI can de-identify or mask sensitive parts of data. #3: Collating data from disparate sources Merging data from various sources is a complex task. But it’s essential for effective security and operations. When logs are properly aggregated and correlated, the resulting data and metrics can give the context needed for better visibility and better troubleshooting. But this is a menial and time-consuming task … which makes it perfect for AI. AI can automatically gather information from various sources and identify patterns within the data, making its analysis easier. AI correlates data from different sources far more efficiently than a human. Modern log analytics tools leverage AI to gather log data from cloud services and on-premises environments. Log analysis and issue resolution become proactive, preventing negative impacts on the health of applications and systems. #4: Transforming raw log data Organizations depend on skilled professionals to handle and analyze log data, yet they often face overwhelming resource constraints. This is where AI can contribute significantly, by automating repetitive tasks and enhancing human capabilities. Before analysis, log data often required cleaning and preprocessing to remove errors, duplicates, or irrelevant information. AI can automate this process, ensuring the accuracy and standardization of all the data. AI can also organize log data into clusters based on similarities or classify them into predefined categories. This helps manage data more efficiently, making it easier for humans to understand and act upon the insights derived. #5: Analyzing log data A clear use case for AI within a DevSecOps strategy is the automation of repetitive and time-consuming tasks — such as data cleaning, feature selection, and model training. With AI taking on these tasks, developers can focus on other tasks. AI can sift through a mountain of data to spot duplication and anomalies — like subtle signs of a cyberattack or unusual traffic patterns — that might easily slip past human scrutiny. This yields enhanced security and operational insights. duplication It’s more than just about handling the volume; AI is adept at detecting patterns that are too complex or too faint for the human eye to catch. For example, let’s consider logging and monitoring for a network to catch signs of data exfiltration. This kind of anomaly might manifest as an unusually high volume of data being sent to an unfamiliar external IP address during off-hours; that’s a pattern that might not immediately raise flags for a human amid thousands of legitimate data transfers happening every day. On the other hand, an AI-based system that’s trained on vast datasets of normal and malicious network behavior can identify this subtle pattern by correlating different indicators: The timing of the data transfer The volume of data The destination IP address The type of data being transferred The timing of the data transfer The volume of data The destination IP address The type of data being transferred For a human, recognizing such a complex pattern requires painstaking analysis and might be missed entirely due to the sheer volume of log data. But an AI system can continuously monitor for these patterns across the entire network, detecting potential threats with precision and speed that far surpasses human capability. #6: Reducing alert fatigue Traditional infrastructure and service monitoring solutions are notoriously noisy, often generating alerts for events that don’t signify a genuine threat. Excessive unactionable alerts lead to alert fatigue. AI-based alerting intelligently filters alerts and reduces the noise, ensuring that the alerts generated are relevant and actionable. For example, traditional monitoring can’t adjust for seasonality — so a crossed threshold in the middle of a high-season weekday afternoon gets as much attention as one in the middle of the night during what should be a slow week. AI-based alerting uses historical data to continually train its models, factoring seasonality into its baselines. The result is fewer false positives and no more alert fatigue. Of course, organizations using AI-driven alerting need to rigorously test results in order to tune specificity and sensitivity. This ensures that critical events are captured effectively. #7: Proactive monitoring Given the large amounts of data an organization generates, teams often struggle to monitor all the organization’s resources proactively. AI is well-equipped to address this issue at scale. By continuously monitoring and aggregating logs from across entire environments, an AI-based tool can identify anomalies before they become widespread, allowing teams to detect potential threats in their initial stages. For example, the threat detection and investigation from Sumo Logic provides the visibility to address advanced threats before they affect operations. AI features such as this enable real-time monitoring, alerting, and data analysis across security tools, cloud infrastructures, and SaaS applications. This enables a DevSecOps team to investigate and respond to cyber threats swiftly. threat detection and investigation #8: Efficient incident response AI-driven alerting improves incident response by facilitating automatic resource allocation and gathering contextual information about an incident. This helps identify potential security threats faster, which in turn helps organizations respond more quickly. When AI-powered logging and observability platforms provide automated remediation features, teams can connect the dots: from continuously monitored logs to incident detection to remediation playbooks. Automated playbook execution means near-immediate response to an incident, whether that’s eliminating the root cause or alerting an engineer to begin an investigation. Remember, with every delay in responding to a security incident, the window for impact widens. Minimizing that delay with AI directly minimizes the impact of an incident. Privacy concerns related to AI adoption One last note: as we’ve seen, AI shows great promise as a tool for improving logging. But remember that it’s still an emerging technology. As a recent GitLab report makes clear, there are serious privacy concerns around AI adoption. While 83% of the teams surveyed said implementing AI in their development process was essential, 79% said they were highly concerned about privacy and IP when dealing with AI. But in many business contexts, AI tools need access to that private data for analysis. GitLab report privacy and IP So take advantage of AI, but be aware and guard against any privacy concerns. Drowning in log data? AI is here to help. Logs are crucial. They’re a rich source of data for monitoring applications and infrastructure. But the multiple data sources and volume of log data — along with the sensitivity of some of that data in the logs — lead to some big challenges in managing log data, security, and privacy. AI is here to help. Modern log management and SIEM solutions are leveraging AI to automate analysis, enhance monitoring, and improve incident response. AI is making DevSecOps more efficient. And as AI solutions evolve, their role in log analysis will only grow, offering smarter, faster insights into logs.

Maximizing Log Value with AI: 8 Ways to Revolutionize DevSecOps Monitoring

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