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A few weeks ago wrote a very interesting in which he compared the proxy based NX-framework with . That blog is not only interesting because it proves the viability of proxies, but even more because it touches some very fundamental concepts in MobX and transparent reactivity (automatic reactivity) in general. Concepts I probably did not elaborate enough on so far. So let me share the mental model behind some of the unique features of MobX. Bertalan Miklos blog MobX Why MobX runs all derivations synchronously The article touches a very remarkable feature (imho) of MobX: in MobX all derivations are run synchronously. Which is quite unusual. Most UI frameworks don’t do this (if any at all). (Reactive stream libraries like RxJS run by default synchronous as well, but they lack transparent tracking so the situation is not entirely comparable). Before starting MobX, I did quite some research on how existing libraries were perceived by developers. Frameworks like Meteor, Knockout, Angular, Ember and Vue all expose reactive behavior similar to MobX. And they exist already for a long time. So why did I built MobX? When digging through the issues and comments of people that were unhappy with these libraries, it occurred to me that there was one recurring theme which caused the chasm between the promise of reactivity and the nasty issues one had to deal with in practice. That recurring theme is “predictability”. If a framework runs your code twice, or with a delay, it becomes hard to debug it. Or to reason about it. Even ‘simple’ abstractions like promises are notoriously hard to debug due to their async nature. I believe unpredictability to be, rightfully, one of the most important reasons for the popularity of Flux patterns and especially Redux: it addresses exactly this issue of predictability when scaling up. There is no magic scheduler at work. MobX however took another approach; instead of leaving behind the whole concept of automatically tracking and running functions, it tries to address the root causes. So that we can still reap the benefits of this model. Transparent reactivity is declarative, high-level and concise. It does this by adding two constraints: Make sure that for any given set of mutations, any affected derivation will run exactly . once Derivations are , and their effects are immediately visible to any observer. never stale Constraint 1. addresses so called “double runs”. It makes sure that if one derived value depends on another derived value, these derivations run in the right order. So that none of them accidentally read a stale value. How that exactly works is described in great detail in an earlier blog post. The second constraint; derivations are never stale; is a lot more interesting. Not only does it prevent so called “glitches” (temporary inconsistencies). It requires a fundamental different approach to scheduling derivations. So far UI libraries have always taken the easy way out when it comes to scheduling derivations: Mark derivations as dirty, and re-run them on the next tick after all the state has been updated. This is simple and straight forward. It is a fine approach if your only concern is updating the DOM. The DOM usually lags a bit ‘behind’ and we hardly read data from it programmatically. So temporary staleness is not really an issue. Yet temporary staleness kills the general applicability of a reactive library. Take for example the following snippet: const user = observable({firstName: “Michel”,lastName: “Weststrate”, // MobX computed attributefullName: computed(function() {return this.firstName + " " + this.lastName})}) user.lastName = “Vaillant”sendLetterToUser(user) The interesting question now is: When the runs, will it see an or a version of the of the user? When using the MobX the answer is always “updated”: Because MobX guarantees that any derivation is updated synchronously. This does not only prevent a lot of nasty surprises, it also makes debugging much simpler as a derivation always has the causing mutation in its stack. sendLetterToUser(user) updated stale fullName So if you are wondering why a derivation is running, simply walking up the stack brings you back to the action that caused the derivation to be invalidated. If MobX would be using async scheduling / processing of derivations these advantages are lost. The library would not be as generally applicable as it is know. When I started on MobX, there was a lot of skepticism on whether this could be done efficiently enough: Ordering the derivation tree and running derivations with each mutation. But here we are, with a system that is out of the box often more efficient than manually optimized code, as reported for example here and here . Transactions & Actions Yes, there is a small payoff to pay; mutations should be grouped in to process multiple changes atomically. Transactions postpone the execution of derivations to the end of the transaction, but still runs them synchronously. Even cooler; if you use a computed value before the transaction has ended, MobX will ensure you get an updated value of that derivation nonetheless! transactions In practice nobody uses transactions explicitly, they are even deprecated in MobX 3. Because apply transaction automatically. Actions are conceptually much nicer; an action indicates a function that will state. They are the inverse of reactions, which to state updates. actions update respond The conceptual relation between actions, state, computed values and reactions Computed values and reactions Another thing MobX focuses strongly on is the separation between values that can be derived ( ), and side effects that should be triggered automatically if state changes ( ). The separation of these concepts is very important and fundamental to MobX. computed values reactions Example derivation graph. Observable state(blue), computed values (green) and reactions (red). Computed values will suspend (light green) if not observed (indirectly) by a reaction. MobX makes sure that each derivation runs only once and in the most optimal order after a mutation. Computed values should always be preferred over reactions. For several reasons: They provide a lot of conceptual clarity. Computed values should always expressed purely in terms of other observable values. This results in a clean derivation graph of computations, rather then an unclear chain of reactions that trigger each other. In other words, reaction that trigger more reactions, or reactions that update state: They are both considered anti patterns in MobX. Chained reactions lead to a hard to follow chain of events and should be avoided. For computed values MobX can be determine whether they are in use somewhere. This means that computed values can automatically be suspended and garbage collected. This saves tons of boilerplate and has a significant positive impact on performance. Computed values are enforced to be side-effect free. Because computed values are not allowed to have side effects, MobX can safely reorder the execution order of computed values to guarantee a minimal amount of re-runs. It can decide to only lazily run the computation if it is not observed. Computed values are cached automatically. This means that reading a computed value will not re-run the computation as long as none of the involved observables did changes. In the end, every software system needs side effects. For the simple reason we always need to bridge from reactive to imperative code. For example to make network requests or flush the DOM. However, often these reactions can be put away in clean abstractions like React components. observer So MobX goes great lengths to make sure stale values can never be observed, and derivations do not run more often then one would expect. In fact, computations are not even run at all if nobody is actively observing. In practice this makes all the difference. There is often some initial resistance to MobX, as the concepts remind people of the unpredictable behavior of MVVM frameworks. However, I believe the semantical clarity of actions, computed values and reactions, the fact that no stale values can be observed, the fact that all derivations run on the same stack as the causing action, makes all the difference here. Proxies & MobX MobX is used heavily in production, and therefor has made a commitment to run on every ES5 environment. This makes it possible to target practical any browser with MobX, but also makes it unacceptable at this moment to rely on Proxies. For this reason MobX has some rough edges, like not fully supporting expando properties and using faux-arrays. It is no secret that the plan always have been to ultimately move to a Proxy based implementation. MobX 3 already has some changes that prepare for proxy usage, and the first opt-in Proxy based features can be expected soon. However the core will remain Proxy free until the vast majority of devices and browsers support them. The case for shallow data structures Regardless the future migration to proxies, the modifiers / shallow observable concept will remain in some form in MobX. The reason for the modifiers mechanism is not performance; it is interoperability. As long as all data in the state of your application is under your control, auto-observability is very convenient. MobX started with just that. But at some point you discover that the world is not as ideal as you want it to be. In each application there are many libraries, each playing their own role, and each making their own assumptions. Modifiers and shallow collections were introduced in MobX to be able to make it clear what data MobX is allowed to manage. For example, sometimes you need to store references to external concepts. However, automatic conversion to observables is often not desirable for objects that are managed by some external library already (for example JSX or DOM elements). It can easily interfere with the internal assumptions of that library. One can find quite some issues in the MobX issue tracker where turning objects unintentionally into observables lead to unexpected behavior. Modifiers are not meant to signal “please make this fast”, but to signal “only observe references to the object, consider the object itself a black box as it is not under our control”. This concept fits working with immutable data structures very nicely as well. It makes it possible to create, for example, an observable map of messages, where the messages themselves are considered immutable data structures. A second problem is that auto-observable collections always create ‘clones’, which is not always acceptable. Proxies always produce a new object and they work only in “one direction”. So if a the original of a proxied object is modified by the library that originally distributed it, proxies won’t detect that change. To illustrate: const target = { x: 3 }const proxy = createObservableProxy(target) observe(() => {console.log(proxy.x)}) target.x = 4// proxy.x is now 4, but no log statement will be written, as the proxy setter hook is not fired! Modifiers provide the necessary flexibility to deal with these situations. For now, since MobX uses property descriptors, it can actually enhance existing objects, so that data mutation can work in two directions if the need really arises. That being said, the way NX produces observable proxies on the fly during reads is super interesting. I’m not sure how it handles referential transparency yet, but so far it seems a very smart thing to do. Avoid modifiers by reading / writing through is a very interesting approach. I’m not sure if it is cleaner to read or write, but it is definitely saves the introduction of some concepts like shallow which is great. $raw What does untracked do? A small note has to be made on the semantics of , unlike suggested, it doesn’t relate to updates in NX. In MobX there is simply no way to update data without notifying observers. Allowing this deliberately introduces the possibility of stale data in an application. Which goes against the principles of MobX. People sometimes think they need such a mechanism, but I never encountered a real life use case where there was not a conceptually cleaner solution. untracked $raw works the other way around: It is not about undetectable Instead, it just causes to be untracked. In other words, it is way of saying that we are not interested in any future updates of the data we use. Like , nobody uses this API in practice, but it is a mechanism baked into because it makes conceptually a lot of sense: Actions run in response to a (user) event, not in response to state changes, so they shouldn’t be tracking which data they consume. That is what are for. untracked writes. reads transaction actions reactions Conclusion MobX is designed to be a generally applicable reactivity library. It’s not just an utility to re-render the UI at the right moment. Instead, it generalizes the concept of efficiently working (both in terms of performance and effort) with data that is just the project of some other data. At for example MobX is used in backend processes as well. Running derivations synchronously and the separation between computed values and reactions is very fundamental to MobX. It leads to a much clearer mental picture of the application state. Mendix Finally, nx-observe proves that proxies are very viable foundation for a transparent reactive library. Both conceptually and performance wise. programming

The fundamental principles behind MobX

Developers need to understand the difference between and in Solidity. These two global variables often need clarification with each other despite their fundamental differences. While they may appear similar at first glance, and represent distinct addresses in the context of a transaction. tx.origin msg.sender tx.origin msg.sender In this blog post, we will delve deeper into the meanings of each of these variables. What Is ? tx.origin In Solidity, identifies the original sender of a transaction. It points to the external account initiating the transaction and remains constant throughout subsequent smart contract interactions (full call chain). tx.origin When a transaction is initiated through the MetaMask wallet, the address of the user's MetaMask wallet is stored in . This address remains the same, even if the transaction passes through multiple contracts. The consistency of this address is essential for tracing the initial sender of the transaction. tx.origin What Is ? msg.sender In smart contract development, identifies the sender of the current call. This variable is dynamic and can change throughout the transaction process. msg.sender When a transaction moves through several smart contracts, the value changes to indicate the most recent contract address in the call chain. For example, if Contract A calls Contract B, then the value within Contract B will be recognized as Contract A. msg.sender msg.sender Coding It Up To demonstrate how the and change between smart contract calls, we will create an smart contract that references the contract. tx.origin msg.sender EntryContract UnderlyingContract Let's add a function that prints each address. printTxOriginAndMsgSender Here, we have the smart contract: Entry contract EntryContract {
  IUnderlyingContract private underlyingContract;

  constructor(IUnderlyingContract _underlyingContract) {
    underlyingContract = _underlyingContract;
  }

  function printTxOriginAndMsgSender() public view {
    console.log("tx.origin", tx.origin);
    console.log("msg.sender", msg.sender);
  }

  function callUnderlyingContract() external {
    underlyingContract.printTxOriginAndMsgSender();
  }
} Now, let's define the and its interface: UnderlyingContract interface IUnderlyingContract {
  function printTxOriginAndMsgSender() external ;
}

contract UnderlyingContract is IUnderlyingContract {
  function printTxOriginAndMsgSender() external view {
    console.log("tx.origin", tx.origin);
    console.log("msg.sender", msg.sender);
  }
} To execute the test, we must first deploy the , and use its address when deploying the . UnderlyingContract EntryContract When we call the function of the contract, we see that both addresses are the same. printTxOriginAndMsgSender EntryContract Let's call the function on the contract. We can see that and are different now. is the original caller's address and is the smart contract’s address. callUnderlyingContract EntryContract tx.origin msg.sender tx.origin msg.sender EntryContract TL;DR In Solidity, and are two variables that serve different but crucial purposes. always refers to the address that initially initiated the transaction and remains constant throughout the transaction chain. tx.origin msg.sender tx.origin On the other hand, represents the sender of the current message or contract interaction and changes with each call. msg.sender It is crucial to be cautious when using as it may not always represent the initial caller of the transaction. msg.sender Links Demo code Solidity documentation: Special Variables and Functions Solidity documentation: Block and Transaction Properties Unraveling Solidity Mysteries: Demystifying tx.origin and msg.sender

How to Understand tx.origin and msg.sender in Solidity

Popular mailbox providers, Google and Yahoo, pioneering the safe email movement, recently put forth new email authentication mandates for email senders. The latest requirements are not only aimed at providing their users with a spam-free inbox but also significantly reducing the risks of direct domain spoofing and email phishing attacks. Email-based cyberattacks have been relentlessly plaguing inboxes, despite various controls enforced by mailbox providers due to the ever-evolving and sophisticated nature of the attacks. Cybercriminals are often successful at bypassing spam filters and creeping their way into the user’s inbox, often impersonating legitimate organizations and individuals. This not only poses an imminent threat to the recipient of these malicious emails but also causes serious damage to the reputation and credibility of the impersonated company. Your Checklist for the New Google and Yahoo Email Sender Requirements Starting early next year (2024), bulk message senders would be expected to adhere to the following requirements: Gmail and Yahoo Email Senders Need to Authenticate Their Emails Message senders often send emails that are not authenticated making it very easy for attackers to impersonate their brand or alter their messages in transit. The renowned mailbox providers recognize that validating email sources is a crucial aspect of email security that will restrict unauthorized messages from reaching their users, and subsequently scamming them. Google and Yahoo have announced the need for bulk senders to authenticate messages using standard email authentication protocols like SPF, DKIM, and . DMARC These industry-acclaimed best practices go a long way in distinguishing between genuine messages and fake ones by verifying the message’s source and content. Businesses are often impersonated in phishing campaigns, wherein their legitimate domain name is forged to send emails on their behalf. These attackers use social engineering to launch highly targeted attacks that have a high success rate. Email authentication, along with other security measures have been proven to be effective strategies in reducing and mitigating a wide range of email-based threats. Emails Should be Easy to Unsubscribe In their latest requirements, Google and Yahoo have stressed the importance of making emails easy to unsubscribe, preferably with a one-click unsubscribe option for recipients. This ensures their users only read emails that they are interested in and filters out those that may be considered spam or unnecessary. While email senders are free to send bulk messages for commercial purposes, an unsubscribe button gives recipients the ability to choose which emails they want to keep receiving and which they don’t. The primary purpose of this stance is to ensure an optimal emailing experience for Gmail and Yahoo users, encouraging them to keep their inboxes spam-free and decluttered. A clean and organized inbox with emails that add value to the users, promotes an active commitment toward customer satisfaction. Emails Should Be Interesting to Receivers Finally, with regard to the last requirement, senders should consider their recipient’s interests while curating the emails they want to send. A two-way approach towards spam reduction wherein on one hand, the recipient is able to easily unsubscribe from your emails, while you curate emails that may actually be of value to your readers - together work in unison to provide an enhanced communication experience that is also effective and beneficial to both parties. The Need for Email Authentication Enforcement: Why Now? Spam is an inbox villain that everyone wants to get rid of. While spam may cause some discomfort and inconvenience, phishing emails are not so merciful. These malicious emails often creep into mailboxes in the garb of a genuine company and spread malware, ransomware or initiate wire transfers. They inflict financial harm upon the victims, while also causing reputational damage to organizations without their knowledge. This is why email authentication is truly the need of the hour with major email service providers extending their support and encouraging adoption with immediate effect. Email Authentication is also taking precedence in other sectors, as the PCI Security Standards Council recently announced DMARC as a mandate for version 4 compliance. To comply, organizations must implement a of at least p=quarantine/reject. DMARC policy While it is a future-dated requirement, organizations are expected to adhere to these latest requirements by March 2025. Get Ready for the Upcoming Google & Yahoo Email Policy Changes - Summary of Requirements To summarize Google and Yahoo’s upcoming email sender requirements, here is a quick checklist that you can refer to: Authenticate your emails against SPF, DKIM, and DMARC Add one-click unsubscription to your emails Send emails that interest your recipients When Does Enforcement Begin? As mentioned by Google and Yahoo, enforcement is projected to begin in February 2024. The Google and Yahoo email policy changes will apply to bulk message senders sending messages to Gmail and/or Yahoo users. You will qualify to fall under the “bulk message sender” category if you send out more than 5000 emails per day. This is a common practice for organizations that frequently send out sales or marketing emails, and the new requirements are aimed at restricting these organizations from spamming the inboxes of recipients with unwanted messages while also protecting them from phishing attacks. Configuring DMARC to Meet Google & Yahoo’s Compliance Mandates From the top level, configuring DMARC and email authentication for your emails may seem like a cakewalk as it simply requires you to publish a DNS TXT record. However, that is just the tip of the iceberg. Technical protocols such as these require granular knowledge of technologies and are easy to get wrong - leading to configuration, syntactical, or other errors. This is why leading organizations fall back on PowerDMARC’s and email authentication services, for an effortless and hassle-free experience. hosted DMARC PowerDMARC Helps You: Meet faster, with automated record generation and setup Google and Yahoo’s email security requirements Monitor and optimize your configurations on a centralized dashboard. Make a smooth transition from DMARC monitoring to enforcement and protect your emails and domain name against spoofing attacks - without compromising on deliverability. Examine detailed insights on your email’s behavior and domain activity with the help of simplified reports, to troubleshoot errors. Mitigate SPF errors 10x more effectively with . SPF Macros Get round-the-clock dedicated assistance from an experienced domain and email security expert. PowerDMARC has helped thousands of customers meet compliance requirements for Google and Yahoo. Complete your checklist before 2024 - sign up for our today! DMARC analyzer

Google & Yahoo Email Senders Must Authenticate Emails by Feb 2024

Google এবং Yahoo ইমেল প্রেরকদের অবশ্যই 2024 সালের ফেব্রুয়ারির মধ্যে ইমেল প্রমাণীকরণ করতে হবে

E-Mail-Absender von Google und Yahoo müssen ihre E-Mails bis Februar 2024 authentifizieren

Los remitentes de correo electrónico de Google y Yahoo deben autenticar los correos electrónicos antes de febrero de 2024

Les expéditeurs d'e-mails Google et Yahoo doivent authentifier leurs e-mails d'ici février 2024

Google और Yahoo ईमेल भेजने वालों को फरवरी 2024 तक ईमेल प्रमाणित करना होगा

Google と Yahoo のメール送信者は 2024 年 2 月までにメールを認証する必要がある

Google 및 Yahoo 이메일 발신자는 2024년 2월까지 이메일을 인증해야 합니다.

Remetentes de e-mail do Google e Yahoo devem autenticar e-mails até fevereiro de 2024

Отправители электронной почты Google и Yahoo должны проверять электронную почту к февралю 2024 г.

Google ve Yahoo E-posta Gönderenlerin Şubat 2024'e Kadar E-postaların Kimlik Doğrulamasını Gerçekleştirmesi Gerekiyor

Người gửi email Google & Yahoo phải xác thực email trước tháng 2 năm 2024

Google 和 Yahoo 电子邮件发件人必须在 2024 年 2 月之前对电子邮件进行身份验证

Satoshi Nakamoto and Bitcoin weren’t exactly popular in the early days, not even among their peers. Privacy-inclined people, who were also experts in programming, and were looking for an alternative to banks and traditional money, were the first ones to read the Bitcoin whitepaper —and most of them didn’t think highly of it. Gregory Maxwell, a self-declared cypherpunk, was one of them. Maxwell is an American programmer well-known for his deep involvement in Bitcoin, to the point of being one of the most important developers of Bitcoin Core (its main implementation) for years. It wasn’t like that since the beginning, though. He first got involved in other open-source and collaborative systems, being an early contributor to Wikipedia and later an employee at the Mozilla Foundation. However, he believed that decentralized consensus wasn’t possible. “When Bitcoin first came out, I was on the cryptography mailing list. When it happened, I sort of laughed. Because I had already proven that decentralized consensus was impossible.” Before really paying enough attention to the Bitcoin code, he was helping to develop the now widely-used Opus Audio Codec. This is an audio format specially designed to compress and transmit audio over the Internet. It offers high-quality sound while using less data, making it ideal for applications like voice calls, video conferencing, and streaming music. Household names like YouTube, Spotify, Netflix, Discord, and Skype use this technology today. Maxwell on Bitcoin Even before Bitcoin, Maxwell was involved in the Reusable Proof-of-Work (RPOW) project created by Hal Finney —who would also turn to Bitcoin later. This system created RPOW tokens that could be transferred between users and exchanged for new units, but it wasn’t exactly like decentralized money. Maxwell was aiming to create conditional transfers (similar to smart contracts) in the platform, but the adoption of it wasn’t high. He came back to Bitcoin in late 2010, as a miner first, just trying to use his GPUs in something useful. Soon after, he paid closer attention to the whitepaper and the source code and changed his mind about the project. He then started to collaborate at a technical level, and he’s been doing it since 2011. In those early days, he focused on protocol design, incentives, and cryptographic review. ** ** In 2014, he also co-founded Blockstream, a company mainly created to boost and fund Bitcoin development. While there, Maxwell helped to create the two-way peg, which makes sidechains possible. These are separate chains connected to a parent distributed ledger, like Bitcoin, enabling experimentation with new features and functionalities without risking the main chain's security. The two-way peg would allow assets to move between chains without losing their value. As a Bitcoin Core developer, Maxwell also helped to build the homomorphic key derivation in Bitcoin Improvement Proposal (BIP) #32, which allows for the generation of multiple public and private key pairs from a single master key. Additionally, he co-authored the BIP-9 to establish a standard for light updates (softforks), and the BIP-173 to define a new type of address for SegWit —another improvement update to increase efficiency. He left Blockstream in 2018 and focused on the creation of smart contract features for Bitcoin. That way, he became the author of a new important improvement for Bitcoin, the Taproot update. This technique combines multiple spending conditions into a single signature, enhancing privacy and reducing transaction costs —which encourages the creation of complex smart contracts. Some Concerns, and Time As much as other fellow cypherpunks, Maxwell has also expressed some concerns about Bitcoin's internal functionality. This is the system that really spread the idea of decentralized money, but it’s not perfect. For starters, Maxwell told the story about his early days as a miner, and how the overheating caused by the machines even drew the police to his home. Mining is, indeed, worrisome, given the great amount of electric energy that it needs. Privacy is another issue in the Bitcoin ledger. People tend to believe that Bitcoin is anonymous, but that’s quite far from the truth. Bitcoin is actually pseudonymous, which means instead of names and ID documents it uses cryptographic addresses. However, that doesn’t mean you can’t be tracked, especially because every transaction is publicly available in a blockchain explorer. And they include data like amount, date, and connected addresses (senders and recipients). Maxwell is also trying to fix this issue in the first cryptocurrency, as he commented in an interview. “Obviously privacy is a big area where Bitcoin needs improvement and I've tried to come up with fancy technology to improve the situation, but it's always a balancing act. Privacy is the one area where if Bitcoin doesn't get better at it... it might leave the world a worse off place than if Bitcoin hadn't existed. The worst case for Bitcoin privacy is pretty bad.  There has been a lot of progress but more is needed.” Despite current flaws, Maxwell also thinks that mass adoption of cryptocurrencies is just a matter of time. Impediments like insecure hardware, buggy software, tax barriers, or self-custody risks will find a solution over the years, and we’re on our way to it. Obyte as a Step into the Future Obyte has emerged as a compelling alternative to Bitcoin, addressing concerns regarding privacy, and decentralization. Unlike Bitcoin, which requires miners as inevitable intermediaries to approve transactions, Obyte employs a Directed Acyclic Graph (DAG) structure where transactions don’t need any approval. This approach eliminates the need for blocks and their creators, making Obyte fully decentralized. Moreover, Obyte offers enhanced privacy features, such as the integration of the privacy coin Blackbytes and in-wallet encrypted chat functionality. These options provide users with greater confidentiality in their transactions and communications, addressing the privacy concerns prevalent in Bitcoin's ledger. By prioritizing decentralization and privacy, Obyte ensures that users can freely conduct transactions on their own and have the option to do so without compromising their sensitive information to public scrutiny, distinguishing it as a more privacy-focused and decentralized option in the cryptocurrency landscape. This ecosystem is really the next step into the future, as many cypherpunks have dreamed of. Read more from Cypherpunks Write Code series: Tim May & Crypto-anarchism Wei Dai & B-money Nick Szabo & Smart Contracts Adam Back & Hashcash Eric Hughes & Remailer St Jude & Community Memory Hal Finney & RPOW John Gilmore & EFF Satoshi Nakamoto & Bitcoin Featured Vector Image by Garry Killian / Freepik Photograph of Gregory Maxwell by Blockstream Satoshi Nakamoto and Bitcoin weren’t exactly popular in the early days, not even among their peers. Privacy-inclined people, who were also experts in programming, and were looking for an alternative to banks and traditional money, were the first ones to read the Bitcoin whitepaper —and most of them didn’t think highly of it. Gregory Maxwell, a self-declared cypherpunk, was one of them. Maxwell is an American programmer well-known for his deep involvement in Bitcoin, to the point of being one of the most important developers of Bitcoin Core (its main implementation) for years. It wasn’t like that since the beginning, though. He first got involved in other open-source and collaborative systems, being an early contributor to Wikipedia and later an employee at the Mozilla Foundation. However, he believed that decentralized consensus wasn’t possible. Maxwell is an American programmer well-known for his deep involvement in Bitcoin, to the point of being one of the most important developers of Bitcoin Core (its main implementation) for years. Maxwell Maxwell he believed he believed “When Bitcoin first came out, I was on the cryptography mailing list. When it happened, I sort of laughed. Because I had already proven that decentralized consensus was impossible.” “When Bitcoin first came out, I was on the cryptography mailing list. When it happened, I sort of laughed. Because I had already proven that decentralized consensus was impossible.” Before really paying enough attention to the Bitcoin code, he was helping to develop the now widely-used Opus Audio Codec. This is an audio format specially designed to compress and transmit audio over the Internet. It offers high-quality sound while using less data, making it ideal for applications like voice calls, video conferencing, and streaming music. Household names like YouTube, Spotify, Netflix, Discord, and Skype use this technology today. Maxwell on Bitcoin Even before Bitcoin, Maxwell was involved in the Reusable Proof-of-Work (RPOW) project created by Hal Finney —who would also turn to Bitcoin later. This system created RPOW tokens that could be transferred between users and exchanged for new units, but it wasn’t exactly like decentralized money. Maxwell was aiming to create conditional transfers (similar to smart contracts) in the platform, but the adoption of it wasn’t high. He came back to Bitcoin in late 2010, as a miner first, just trying to use his GPUs in something useful. Soon after, he paid closer attention to the whitepaper and the source code and changed his mind about the project. He then started to collaborate at a technical level, and he’s been doing it since 2011. In those early days, he focused on protocol design, incentives, and cryptographic review. He then started to collaborate at a technical level, and he’s been doing it since 2011. he focused he focused ** ** In 2014, he also co-founded Blockstream, a company mainly created to boost and fund Bitcoin development. While there, Maxwell helped to create the two-way peg, which makes sidechains possible. These are separate chains connected to a parent distributed ledger, like Bitcoin, enabling experimentation with new features and functionalities without risking the main chain's security. The two-way peg would allow assets to move between chains without losing their value. As a Bitcoin Core developer, Maxwell also helped to build the homomorphic key derivation in Bitcoin Improvement Proposal (BIP) #32 , which allows for the generation of multiple public and private key pairs from a single master key. Additionally, he co-authored the BIP-9 to establish a standard for light updates (softforks), and the BIP-173 to define a new type of address for SegWit —another improvement update to increase efficiency. Maxwell also helped to build the homomorphic key derivation in Bitcoin Improvement Proposal ( BIP ) #32 BIP BIP He left Blockstream in 2018 and focused on the creation of smart contract features for Bitcoin. That way, he became the author of a new important improvement for Bitcoin, the Taproot update . This technique combines multiple spending conditions into a single signature, enhancing privacy and reducing transaction costs —which encourages the creation of complex smart contracts. Taproot update Taproot update Some Concerns, and Time As much as other fellow cypherpunks , Maxwell has also expressed some concerns about Bitcoin's internal functionality. This is the system that really spread the idea of decentralized money, but it’s not perfect. For starters, Maxwell told the story about his early days as a miner, and how the overheating caused by the machines even drew the police to his home. Mining is, indeed, worrisome, given the great amount of electric energy that it needs. cypherpunks cypherpunks Privacy is another issue in the Bitcoin ledger. People tend to believe that Bitcoin is anonymous, but that’s quite far from the truth. Bitcoin is actually pseudonymous, which means instead of names and ID documents it uses cryptographic addresses. However, that doesn’t mean you can’t be tracked, especially because every transaction is publicly available in a blockchain explorer. And they include data like amount, date, and connected addresses (senders and recipients). Privacy is another issue in the Bitcoin ledger. Maxwell is also trying to fix this issue in the first cryptocurrency, as he commented in an interview. an interview. an interview. “Obviously privacy is a big area where Bitcoin needs improvement and I've tried to come up with fancy technology to improve the situation, but it's always a balancing act. Privacy is the one area where if Bitcoin doesn't get better at it... it might leave the world a worse off place than if Bitcoin hadn't existed. The worst case for Bitcoin privacy is pretty bad.  There has been a lot of progress but more is needed.” “Obviously privacy is a big area where Bitcoin needs improvement and I've tried to come up with fancy technology to improve the situation, but it's always a balancing act. Privacy is the one area where if Bitcoin doesn't get better at it... it might leave the world a worse off place than if Bitcoin hadn't existed. The worst case for Bitcoin privacy is pretty bad.  There has been a lot of progress but more is needed.” Despite current flaws, Maxwell also thinks that mass adoption of cryptocurrencies is just a matter of time. Impediments like insecure hardware, buggy software, tax barriers, or self-custody risks will find a solution over the years, and we’re on our way to it. Obyte as a Step into the Future Obyte has emerged as a compelling alternative to Bitcoin, addressing concerns regarding privacy, and decentralization. Unlike Bitcoin, which requires miners as inevitable intermediaries to approve transactions, Obyte employs a Directed Acyclic Graph (DAG) structure where transactions don’t need any approval. This approach eliminates the need for blocks and their creators, making Obyte fully decentralized. Obyte Obyte Obyte employs a Directed Acyclic Graph (DAG) structure where transactions don’t need any approval. Moreover, Obyte offers enhanced privacy features, such as the integration of the privacy coin Blackbytes and in-wallet encrypted chat functionality . These options provide users with greater confidentiality in their transactions and communications, addressing the privacy concerns prevalent in Bitcoin's ledger. Blackbytes Blackbytes chat functionality chat functionality By prioritizing decentralization and privacy, Obyte ensures that users can freely conduct transactions on their own and have the option to do so without compromising their sensitive information to public scrutiny, distinguishing it as a more privacy-focused and decentralized option in the cryptocurrency landscape. This ecosystem is really the next step into the future, as many cypherpunks have dreamed of. Read more from Cypherpunks Write Code series: Read more from Cypherpunks Write Code series: Tim May & Crypto-anarchism Tim May & Crypto-anarchism Tim May & Crypto-anarchism Tim May & Crypto-anarchism Wei Dai & B-money Wei Dai & B-money Wei Dai & B-money Wei Dai & B-money Nick Szabo & Smart Contracts Nick Szabo & Smart Contracts Nick Szabo & Smart Contracts Nick Szabo & Smart Contracts Adam Back & Hashcash Adam Back & Hashcash Adam Back & Hashcash Adam Back & Hashcash Eric Hughes & Remailer Eric Hughes & Remailer Eric Hughes & Remailer Eric Hughes & Remailer St Jude & Community Memory St Jude & Community Memory St Jude & Community Memory St Jude & Community Memory Hal Finney & RPOW Hal Finney & RPOW Hal Finney & RPOW Hal Finney & RPOW John Gilmore & EFF John Gilmore & EFF John Gilmore & EFF John Gilmore & EFF Satoshi Nakamoto & Bitcoin Satoshi Nakamoto & Bitcoin Satoshi Nakamoto & Bitcoin Satoshi Nakamoto & Bitcoin Featured Vector Image by Garry Killian / Freepik Featured Vector Image by Garry Killian / Freepik Freepik Freepik Photograph of Gregory Maxwell by Blockstream Photograph of Gregory Maxwell by Blockstream Blockstream Blockstream

Cypherpunks Write Code: Gregory Maxwell and Bitcoin Core

সাইফারপাঙ্কস কোড লিখুন: গ্রেগরি ম্যাক্সওয়েল এবং বিটকয়েন কোর

Cypherpunks schreiben Code: Gregory Maxwell und Bitcoin Core

Código de escritura de Cypherpunks: Gregory Maxwell y Bitcoin Core

Cypherpunks écrit du code : Gregory Maxwell et Bitcoin Core

साइफरपंक्स ने कोड लिखा: ग्रेगरी मैक्सवेल और बिटकॉइन कोर

サイファーパンクがコードを書く: グレゴリー・マクスウェルとビットコイン・コア

Cypherpunks의 코드 작성: Gregory Maxwell 및 Bitcoin Core

Código de gravação Cypherpunks: Gregory Maxwell e Bitcoin Core

Шифропанки пишут код: Грегори Максвелл и Bitcoin Core

Şifrepunklar Kod Yazıyor: Gregory Maxwell ve Bitcoin Core

Cypherpunks viết mã: Gregory Maxwell và Bitcoin Core

密码朋克编写代码：Gregory Maxwell 和比特币核心

While hackers don’t differentiate between the size of their victims, certain attacks, like social engineering attacks, are most common in SMBs and SMEs. This blog specifically addresses the unique challenges and threats you may face as a small and medium-sized business or enterprise (SMB/SME) owner. Not for nothing, social engineering attacks are termed – unseen perils, silent threats to your small business and enterprise. Social Engineering Attacks: The Stats and The Reports Picture this: 📌 Per the report by Barracuda, small businesses witness 350% more social engineering attacks than larger enterprises. 📌 More than 30% of small businesses in the US have weak points that threat actors can exploit. 📌 Per the recent Verizon Data Breach Investigation Report, social engineering attacks, system intrusion, and privilege misuse incidents account for 92% of breaches in small businesses. It is essential to understand what a social engineering attack is and how it impacts your small business to understand how it affects you. What Is Social Engineering? As Cisco puts it, social engineering is not a cyberattack at its heart. It is the art of persuasion and human psychology. The modus operandi here is to target the minds of the victims like conmen and gain their trust. With the victims’ trust gained, the attackers go in for the kill by encouraging them to 📍Divulge personal information 📍Click on malicious web links 📍Open malware-infected attachments So, what is Social Engineering? Let’s look at the definition. Social Engineering: The Definition Any manipulation technique that exploits human errors to gain personal information, access, or valuables is a social engineering attack. In technical terms, social engineering is the psychological manipulation of people into divulging confidential information or performing unsafe actions. In layman’s terms, social engineering is an assault on your emotions and feelings to extract sensitive and personal information for malicious purposes. In the world of cybercrime, scams related to human hacking are on the rise. These scams target unsuspecting users, playing tricks with their minds and luring them into revealing sensitive data and confidential information. Social engineering attacks can happen 👉 Online 👉 In-person 👉 Other interactions How Does Social Engineering Work? Social engineering works in four steps. But essentially, it works on your cognitive biases, where a threat actor impersonates either an authoritative person or a trustworthy individual and cons you into trusting them. They work in four steps. Preparation This is where a threat actor collects information about your business, and this may include your business emails, messaging apps, and other sensitive information related to your business. Infiltration This is where a bad actor will approach you or your employees. They usually imitate a reliable resource and use the previously gathered information to validate themselves. Exploitation Here, a threat actor will use persuasion tricks to obtain more sensitive information from your employees or even you. The threat actor plays on the human mind and tricks you into revealing some sensitive information. Disengagement Once an attacker has the information they sought, they will cut off all ties with you, deploy malware in your office network, and disappear in thin air. Why are SMBs and SMEs Prime Targets? Whether you have a small business or a small enterprise, you are at risk of social engineering attacks. Here are the prime reasons threat actors love your small business or your small enterprise. 📍Lack of resources is one of the primary reasons threat actors target your small business or small enterprise. 📍Trusting Culture of SMBs/SMEs is an important reason for threat actors to love small businesses and enterprises. 📍Your overworked and overburdened employees who juggle multiple responsibilities are the prime targets of threat actors. So, how do you counter these attacks on your business? Top Ways To Protect Your Small Business From Social Engineering Social Engineering attacks can be devastating for your small business, and your business may suffer: 📍Significant financial losses 📍Downtime 📍Reputational damage 📍Loss of Stakeholder and customers’ trust You can counter social engineering attacks on your small business with these methods. 📌Train your employees to recognize 📍Phishing emails 📍Suspicious phone calls 📍Unsolicited requests for sensitive data 📌 Verify each email for sender addresses and the legitimacy of the data requests. 📌 Deploy two-factor authentication or multi-factor authentication on all your accounts for better security. 📌 Data encryption is your ally; embrace it with both hands. Encrypt your data at rest and in transition. When you follow these steps, you can ensure that your small business is protected from social engineering attacks. While you are at it, here are some common scams to watch out for. Common Scams to Watch Out For While practicing the four ways you can mitigate the threat of social engineering attacks, keeping an eye on some of the most common scams prevalent is essential. 📌 Phishing 📌 Tech Support Scams 📌 Pretexting 📌 Baiting 📌 Malware 📌 CEO Fraud Each of these scams is also an individual scam, but they can be deployed for sophisticated social engineering attacks. The best method to prevent social engineering attacks is to create awareness about the various tactics used by threat actors. Final Words Social engineering is becoming dangerous because attacks have become sophisticated with tech evolution. Threat actors indulging in social engineering are master con artists who know how to trick you into revealing sensitive information by invoking extreme emotions in you and your employees. So, the best way to protect your small business from social engineering is to educate your employees. While hackers don’t differentiate between the size of their victims, certain attacks, like social engineering attacks, are most common in SMBs and SMEs. This blog specifically addresses the unique challenges and threats you may face as a small and medium-sized business or enterprise (SMB/SME) owner. Not for nothing, social engineering attacks are termed – unseen perils, silent threats to your small business and enterprise. Social Engineering Attacks: The Stats and The Reports Picture this: 📌 Per the report by Barracuda, small businesses witness 350% more social engineering attacks than larger enterprises. 350% more social engineering attacks than larger enterprises. 350% more social engineering attacks than larger enterprises. 📌 More than 30% of small businesses in the US have weak points that threat actors can exploit. 30% of small businesses 30% of small businesses 📌 Per the recent Verizon Data Breach Investigation Report, social engineering attacks, system intrusion, and privilege misuse incidents account for 92% of breaches in small businesses . 92% of breaches in small businesses 92% of breaches in small businesses It is essential to understand what a social engineering attack is and how it impacts your small business to understand how it affects you. What Is Social Engineering? As Cisco puts it, social engineering is not a cyberattack at its heart. It is the art of persuasion and human psychology. Cisco Cisco The modus operandi here is to target the minds of the victims like conmen and gain their trust. With the victims’ trust gained, the attackers go in for the kill by encouraging them to 📍Divulge personal information 📍Click on malicious web links 📍Open malware-infected attachments So, what is Social Engineering? Let’s look at the definition. Social Engineering: The Definition Any manipulation technique that exploits human errors to gain personal information, access, or valuables is a social engineering attack. In technical terms, social engineering is the psychological manipulation of people into divulging confidential information or performing unsafe actions. In layman’s terms, social engineering is an assault on your emotions and feelings to extract sensitive and personal information for malicious purposes. In the world of cybercrime, scams related to human hacking are on the rise. These scams target unsuspecting users, playing tricks with their minds and luring them into revealing sensitive data and confidential information. Social engineering attacks can happen 👉 Online 👉 In-person 👉 Other interactions How Does Social Engineering Work? Social engineering works in four steps. But essentially, it works on your cognitive biases, where a threat actor impersonates either an authoritative person or a trustworthy individual and cons you into trusting them. They work in four steps. Preparation This is where a threat actor collects information about your business, and this may include your business emails, messaging apps, and other sensitive information related to your business. Infiltration This is where a bad actor will approach you or your employees. They usually imitate a reliable resource and use the previously gathered information to validate themselves. Exploitation Here, a threat actor will use persuasion tricks to obtain more sensitive information from your employees or even you. The threat actor plays on the human mind and tricks you into revealing some sensitive information. Disengagement Once an attacker has the information they sought, they will cut off all ties with you, deploy malware in your office network, and disappear in thin air. Why are SMBs and SMEs Prime Targets? Whether you have a small business or a small enterprise, you are at risk of social engineering attacks. Here are the prime reasons threat actors love your small business or your small enterprise. 📍Lack of resources is one of the primary reasons threat actors target your small business or small enterprise. 📍Trusting Culture of SMBs/SMEs is an important reason for threat actors to love small businesses and enterprises. 📍Your overworked and overburdened employees who juggle multiple responsibilities are the prime targets of threat actors. So, how do you counter these attacks on your business? Top Ways To Protect Your Small Business From Social Engineering Social Engineering attacks can be devastating for your small business, and your business may suffer: 📍Significant financial losses 📍Downtime 📍Reputational damage 📍Loss of Stakeholder and customers’ trust You can counter social engineering attacks on your small business with these methods. 📌Train your employees to recognize 📍Phishing emails 📍Suspicious phone calls 📍Unsolicited requests for sensitive data 📌 Verify each email for sender addresses and the legitimacy of the data requests. 📌 Deploy two-factor authentication or multi-factor authentication on all your accounts for better security. 📌 Data encryption is your ally; embrace it with both hands. Encrypt your data at rest and in transition. When you follow these steps, you can ensure that your small business is protected from social engineering attacks. While you are at it, here are some common scams to watch out for. Common Scams to Watch Out For While practicing the four ways you can mitigate the threat of social engineering attacks, keeping an eye on some of the most common scams prevalent is essential. 📌 Phishing 📌 Tech Support Scams 📌 Pretexting 📌 Baiting 📌 Malware 📌 CEO Fraud Each of these scams is also an individual scam, but they can be deployed for sophisticated social engineering attacks. The best method to prevent social engineering attacks is to create awareness about the various tactics used by threat actors. Final Words Social engineering is becoming dangerous because attacks have become sophisticated with tech evolution. Threat actors indulging in social engineering are master con artists who know how to trick you into revealing sensitive information by invoking extreme emotions in you and your employees. So, the best way to protect your small business from social engineering is to educate your employees.

Social Engineering Attacks: One of the Biggest and Quietest Threats to Your Business

Building a User-Friendly Interface for Central Bank Digital Currency Applications: A Case Study 

Invisible Online: A Family Guide to Private and Secure Online Living

What are Pub/Sub Systems

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