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Qichacha ()

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Image via LaptrinhX The Yakuza series has found a new level of success over the past few years. As of 2021, it was the franchise hit 17 million total sales. This success begs the question of just how the series managed to reach such numbers, a question that can be answered by looking at the sales of each game. reported Rather, that would be the case. But the Yakuza franchise only gained recent popularity in English-speaking countries, and sales data on the series is scarce at best. It’s hard to say which games even broke a million. Image via Polygon This list will be a little different as a result. Using data from and reports across the series’s lifetime, each game’s placement on this list will be estimated. As a result, this list might not be accurate - the numbers certainly won’t add up to 17 million - but it will still offer valuable insight on more successful titles in the franchise. steamspy Disclaimer: Remakes and remasters, like the “Kiwami” games, will be merged with the original titles due to the lack of official sales data on them. Spinoffs like Judgement and Ishin will be considered in the ranking as well, but not Lost Judgement due to its very recent release. The Best Yakuza Games Ranked by Approximate Copies Sold 10. Ryu ga Gotoku Ishin! - ~400,000 Copies Sold As a Japan-only spinoff, Ryu ga Gotoku Ishin! barely makes it into the top 10. It’s possible this spot might belong to another spinoff, Yakuza: Dead Souls, but that game has even less sales data, only covering the first week. Ishin features major Yakuza characters in Japan’s Edo period, reenacting history in creative and over-the-top ways. It’s been rumored that this game might get a remake, with , but it’s hard to say whether this game about the past truly has any future. the series director expressing interest in making one 9. Yakuza 4 - ~500,000 Copies Sold Yakuza 4 was the first game in the series to have multiple playable characters. It brought a new level of variety to the gameplay, allowing the player to use different techniques depending on who they played as. It also introduced fan-favorite characters like Akiyama and Saejima to the franchise. The systems introduced by this title would still require further refinement, something that would be achieved by its sequel. 8. Yakuza 5 - ~700,000 Copies Sold Yakuza 5 takes the multiple characters from Yakuza 4 and gives them countless new additions, with each one even getting their own major sidequest. Combine that with a far more intricate story and a gameplay flow that rivals the best games in the series, and you have a true gem in the Yakuza franchise. It might not have been the most successful title, but it laid many of the foundations that would allow the games to achieve true popularity in western markets. 7. Yakuza: Like a Dragon - ~700,000+ Copies Sold It is the belief of this writer that Yakuza: Like a Dragon definitely sold more than what this list states. The number of around 700,000 comes from official reports and data collected from steamspy. Despite how low this number seems, the series grew from to 17 million after this title was released. It’s no wonder this game garnered so much attention - Like a Dragon featured brand-new characters and a new turn-based combat system. The protagonist of this game, Ichiban, is , surely bringing a great deal of joy to fans of this new style. 14 million total sales confirmed to return in the next main Yakuza installment 6. Yakuza 3 - ~800,000 Copies Sold Riding off the successful coattails of the previous games, Yakuza 3 managed very high sales numbers. It acts as more of a slice of life than other entries, having players enjoy day-to-day life at an orphanage owned by the protagonist. It received high reviews when it first came out, but its gameplay is noticeably lacking - especially after the release of the Kiwami remakes for Yakuza and Yakuza 2. It might be too late for a similar remake, but fans of the series will likely still enjoy playing through Yakuza 3 for its ever-emotional story. 5. Yakuza 6: The Song of Life - ~1,000,000 Copies Sold As a game meant to wrap up the saga of the main protagonist, Kazuma Kiryu, Yakuza 6: The Song of Life delivered some of the most emotional stories the franchise has seen. Being created in a brand-new engine, The Song of Life comes with better graphics and more fluid action than ever. Based on what limited data it has, it might have even surpassed Judgement’s sales...but it also might have just fallen short. 4. Judgement - ~1,000,000+ Copies Sold Judgement, while only truly related to Yakuza in setting and gameplay, is one of the few titles to have been reported as selling a million copies. Featuring unique detective work and numerous fighting styles used by the protagonist, Judgement provided a deep story alongside varied and fun gameplay. Unfortunately, the possibility of future games might be less certain than ever, according to reports by . The success of this title can’t be denied, though, and it makes one wonder whether future Judgement titles will never truly see the light of day. Kotaku 3. Yakuza 2 (and Kiwami 2) - ~1,300,000 Copies Sold As the second title to ever be released, and the only game besides the original to get a Kiwami remake, Yakuza 2 takes firm hold of this list’s number 3 spot. It brought new locales and villains that would have prominent roles in future games, and its remake added massive new features and even minigames. It’s a fantastic addition to the series, and a must-play for anyone that loved the original or the prequel. 2. Yakuza (and Kiwami) - ~1,500,000 Copies Sold Of course, the original Yakuza had to be here somewhere. Yakuza and its eventual remake, Yakuza Kiwami, introduced thousands of new fans to the series. Featuring the unique heat action system and a large-scale city with hundreds of inhabitants, the original Yakuza was groundbreaking for its time. Combine that with Kiwami’s enhanced gameplay and additional challenges, and you have one of the best story-heavy action games out there. 1. Yakuza 0 - ~2,000,000 Copies Sold Quite possibly the best-selling title of the franchise, Yakuza 0 acts as a prequel to the rest of the series. Players control series protagonist Kazuma Kiryu and the fan-favorite rival Goro Majima as they uncover monetary mysteries and high-stakes plots. Featuring refinements of systems from previous titles, as well as droves of side content and heart-wrenching storytelling, Yakuza 0 deserves its spot at number 1. As mentioned, these sales numbers are most likely inaccurate - especially with the release of remastered titles and the newfound success of the franchise. Still, it’s plain to see why certain games are where they are. One can only wonder where the series might go from here, and whether a new title will overtake 0’s success. Sources: 2009.02.04| Nakoshi Minoru-ying official blog "Cheers for the time being"by Ameba (archive.org) 「龍が如く 極」合計16万3000本。「ゼルダ無双 ハイラルオールスターズ」「ジャストコーズ3」もランクインの「ゲームソフト週間販売ランキング＋」 (4gamer.net) GrID S565 - PS2 2006 releases - Garaph GID 2690 - Yakuza 2 (PlayStation 2 the Best) - PS2 - Garaph yakuza 3 in a sentence - yakuza 3 sentence (ichacha.net) Yakuza 4 For PS3 Debuts With 384,000 Sold In Japan (gamedeveloper.com) http://www.eurogamer.net/articles/2013-05-10-aliens-colonial-marines-managed-1-31-million-sales Yakuza 6 Sales Nears 1 Million Mark Worldwide (playstationlifestyle.net) https://www.segasammy.co.jp/english/ir/library/pdf/stockholder/2020/202003_4q_kabutsu_e_final.pdf Yakuza 0 shipments top 500,000 - Gematsu Judgment shipments and digital sales top one million - Gematsu http://www.eurogamer.net/articles/2014-05-09-how-are-segas-video-games-selling More in gaming: 1. Top 10 Kirby Series Games Ranked by Sales | Hacker Noon 2. 10 Best Zelda Games of All Time Ranked by Sales | Hacker Noon 3. The Ace Attorney Timeline: All Phoenix Wright Games in Chronological Order | Hacker Noon

10 Best Yakuza Games of All Time Ranked by Sales

Los 10 mejores juegos de Yakuza de todos los tiempos clasificados por ventas

Author:
(1) David S. Hardin, Cedar Rapids, IA USA david.s.hardin@gmail.com. Table of Links Abstract and Introduction
Dancing Links
The Rust Programming Language
RAC: Hardware/Software Co-Assurance at Scale
Rust and RAR
Dancing Links in Rust
Related Work
Conclusion, Acknowledgments, and References 3 The Rust Programming Language The Rust programming language has garnered significant interest and use as a modern, type-safe, memorysafe, and potentially formally analyzable programming language. Google [29] and Amazon [25] are major Rust adopters, and Linus Torvalds has commented positively on the near-term ability of the Rust toolchain to be used in Linux kernel development [1]. And after spending decades dealing with a never-ending parade of security vulnerabilities due to C/C++, which continue to manifest at a high rate [24] despite their use of sophisticated C/C++ analysis tools, Microsoft announced at its BlueHat 2023 developer conference that is was beginning to rewrite core Windows libraries in Rust [6]. Our interest in Rust stems from its potential as a hardware/software co-assurance language. This interest is motivated in part by emerging application areas, such as autonomous and semi-autonomous platforms for land, sea, air, and space, that require sophisticated algorithms and data structures, are subject to stringent accreditation/certification, and encourage hardware/software co-design approaches. (For an unmanned aerial vehicle use case illustrating a formal methods-based systems engineering environment, please consult [7] [23].) In this paper, we explore the use of Rust as a High-Level Synthesis (HLS) language [26]. HLS developers specify the high-level abstract behavior of a digital system in a manner that omits hardware design details such as clocking; the HLS toolchain is then responsible for “filling in the details” to produce a Register Transfer Level (RTL) structure that can be used to realize the design in hardware. HLS development is thus closer to software development than traditional hardware design in Hardware Description Languages (HDLs) such as Verilog or VHDL. Most incumbent HLS languages are a subset of C, e.g. Mentor Graphics’ Algorithmic C [21], or Vivado HLS by Xilinx [31], although other languages have also been used, e.g. OCaml [15]. A Rust-based HLS would bring a single modern, type-safe, and memory-safe expression language for both hardware and software realizations, with very high assurance. For formal methods researchers, Rust presents the opportunity to reason about application-level logic written in the imperative style favored by industry, but without the snarls of the unrestricted pointers of C/C++. Much progress has been made to this end in recent years, to the point that developers can verify the correctness of common algorithm and data structure code that utilizes common idioms such as records, loops, modular integers, and the like, and verified compilers can guarantee that such code is compiled correctly to binary [18]. Particular progress has been made in the area of hardware/software co-design algorithms, where array-backed data structures are common [10, 11]. (NB: This style of programming also addresses one of the shortcomings of Rust, namely its lack of support for cyclic data structures.) As a study of the suitability of Rust as an HLS, we have crafted a Rust subset, inspired by Russinoff’s Restricted Algorithmic C (RAC) [27], which we have imaginatively named Restricted Algorithmic Rust, or RAR [13]. In fact, in our first implementation of a RAR toolchain, we merely “transpile” (perform a source-to-source translation of) the RAR source into RAC. By so doing, we leverage a number of existing hardware/software co-assurance tools with a minimum investment of time and effort. By transpiling RAR to RAC, we gain access to existing HLS compilers (with the help of some simple C preprocessor directives, we are able to generate code for either the Algorithmic C or Vivado HLS toolchains). But most importantly for our research, we leverage the RAC-to-ACL2 translator that Russinoff and colleagues at Arm have successfully utilized in industrial-strength floating point hardware verification. We have implemented several representative algorithms and data structures in RAR, including: • a suite of array-backed algebraic data types, previously implemented in RAC (as reported in [10]); • a significant subset of the Monocypher [30] modern cryptography suite, including XChacha20 and Poly1305 (RFC 8439) encryption/decryption, BLAKE2b hashing, and X25519 public key cryptography [12]; and • a DFA-based JSON lexer, coupled with an LL(1) JSON parser. The JSON parser has also been implemented using Greibach Normal Form (previously implemented in RAC, as described in [14]). The RAR examples created to date are similar to their RAC counterparts in terms of expressiveness, and we deem the RAR versions somewhat superior in terms of readability (granted, this is a very subjective evaluation). In this paper, we will describe the development and formal verification of an array-based circular doubly-linked list (CDLL) data structure in RAR, including the Dancing Links optimization. Along the way, we will introduce the RAR subset of Rust, the RAR toolchain, the CDLL example, and detail our ACL2-based verification techniques, as well as the ACL2 books that we brought to bear on this example. It is hoped that this explication will convince the reader of the practicality of RAR as a high-assurance hardware/software co-design language, as well as the feasibility of the performing full functional correctness proofs of RAR code. We will then conclude with related and future work. This paper is available on arxiv under CC 4.0 license. Author: (1) David S. Hardin, Cedar Rapids, IA USA david.s.hardin@gmail.com. Author: Author: (1) David S. Hardin, Cedar Rapids, IA USA david.s.hardin@gmail.com. Table of Links Abstract and Introduction Dancing Links The Rust Programming Language RAC: Hardware/Software Co-Assurance at Scale Rust and RAR Dancing Links in Rust Related Work Conclusion, Acknowledgments, and References Abstract and Introduction Abstract and Introduction Dancing Links Dancing Links The Rust Programming Language The Rust Programming Language RAC: Hardware/Software Co-Assurance at Scale RAC: Hardware/Software Co-Assurance at Scale Rust and RAR Rust and RAR Dancing Links in Rust Dancing Links in Rust Related Work Related Work Conclusion, Acknowledgments, and References Conclusion, Acknowledgments, and References 3 The Rust Programming Language The Rust programming language has garnered significant interest and use as a modern, type-safe, memorysafe, and potentially formally analyzable programming language. Google [29] and Amazon [25] are major Rust adopters, and Linus Torvalds has commented positively on the near-term ability of the Rust toolchain to be used in Linux kernel development [1]. And after spending decades dealing with a never-ending parade of security vulnerabilities due to C/C++, which continue to manifest at a high rate [24] despite their use of sophisticated C/C++ analysis tools, Microsoft announced at its BlueHat 2023 developer conference that is was beginning to rewrite core Windows libraries in Rust [6]. Our interest in Rust stems from its potential as a hardware/software co-assurance language. This interest is motivated in part by emerging application areas, such as autonomous and semi-autonomous platforms for land, sea, air, and space, that require sophisticated algorithms and data structures, are subject to stringent accreditation/certification, and encourage hardware/software co-design approaches. (For an unmanned aerial vehicle use case illustrating a formal methods-based systems engineering environment, please consult [7] [23].) In this paper, we explore the use of Rust as a High-Level Synthesis (HLS) language [26]. HLS developers specify the high-level abstract behavior of a digital system in a manner that omits hardware design details such as clocking; the HLS toolchain is then responsible for “filling in the details” to produce a Register Transfer Level (RTL) structure that can be used to realize the design in hardware. HLS development is thus closer to software development than traditional hardware design in Hardware Description Languages (HDLs) such as Verilog or VHDL. Most incumbent HLS languages are a subset of C, e.g. Mentor Graphics’ Algorithmic C [21], or Vivado HLS by Xilinx [31], although other languages have also been used, e.g. OCaml [15]. A Rust-based HLS would bring a single modern, type-safe, and memory-safe expression language for both hardware and software realizations, with very high assurance. For formal methods researchers, Rust presents the opportunity to reason about application-level logic written in the imperative style favored by industry, but without the snarls of the unrestricted pointers of C/C++. Much progress has been made to this end in recent years, to the point that developers can verify the correctness of common algorithm and data structure code that utilizes common idioms such as records, loops, modular integers, and the like, and verified compilers can guarantee that such code is compiled correctly to binary [18]. Particular progress has been made in the area of hardware/software co-design algorithms, where array-backed data structures are common [10, 11]. (NB: This style of programming also addresses one of the shortcomings of Rust, namely its lack of support for cyclic data structures.) As a study of the suitability of Rust as an HLS, we have crafted a Rust subset, inspired by Russinoff’s Restricted Algorithmic C (RAC) [27], which we have imaginatively named Restricted Algorithmic Rust, or RAR [13]. In fact, in our first implementation of a RAR toolchain, we merely “transpile” (perform a source-to-source translation of) the RAR source into RAC. By so doing, we leverage a number of existing hardware/software co-assurance tools with a minimum investment of time and effort. By transpiling RAR to RAC, we gain access to existing HLS compilers (with the help of some simple C preprocessor directives, we are able to generate code for either the Algorithmic C or Vivado HLS toolchains). But most importantly for our research, we leverage the RAC-to-ACL2 translator that Russinoff and colleagues at Arm have successfully utilized in industrial-strength floating point hardware verification. We have implemented several representative algorithms and data structures in RAR, including: • a suite of array-backed algebraic data types, previously implemented in RAC (as reported in [10]); • a significant subset of the Monocypher [30] modern cryptography suite, including XChacha20 and Poly1305 (RFC 8439) encryption/decryption, BLAKE2b hashing, and X25519 public key cryptography [12]; and • a DFA-based JSON lexer, coupled with an LL(1) JSON parser. The JSON parser has also been implemented using Greibach Normal Form (previously implemented in RAC, as described in [14]). The RAR examples created to date are similar to their RAC counterparts in terms of expressiveness, and we deem the RAR versions somewhat superior in terms of readability (granted, this is a very subjective evaluation). In this paper, we will describe the development and formal verification of an array-based circular doubly-linked list (CDLL) data structure in RAR, including the Dancing Links optimization. Along the way, we will introduce the RAR subset of Rust, the RAR toolchain, the CDLL example, and detail our ACL2-based verification techniques, as well as the ACL2 books that we brought to bear on this example. It is hoped that this explication will convince the reader of the practicality of RAR as a high-assurance hardware/software co-design language, as well as the feasibility of the performing full functional correctness proofs of RAR code. We will then conclude with related and future work. This paper is available on arxiv under CC 4.0 license. This paper is available on arxiv under CC 4.0 license. available on arxiv

Rust Implementation of Knuth's Dancing Links: The Rust Programming Language

ENGLISH AS SHE IS TAUGHT

Several years ago, a casual Internet user asked about VPNs would most likely scratch his or her head in uncertainty. Sure, VPNs have been around since Microsoft developed the PPTP protocol in 1996 and granted employees a somewhat safe remote access to confidential business resources on distant databases. But in 1996 there was a total amount of , and cybersecurity was an oblique idea for most of them. 36 million Internet users Jumping to 2010 we have nearly 2 billion Internet users, first commercial VPNs are appearing for public use, PPTP is an outdated protocol, and those who decide to use a VPN struggle with unacceptable connection speeds. By the way, cybersecurity is not an oblique idea anymore, but a problem nobody knows how to deal with yet. And only on the verge of 2020 netizens that value their online privacy woke up to see their VPNs blazing high-speeds and cheered in unison - WireGuard has arrived. And we at NordVPN hastened to adapt it to our service with NordLynx as the end product in mind. WireGuard is a VPN protocol, and VPN protocols are a mysterious technical thing, but it doesn't need to be. Those interested in why your VPN got a lot faster recently - let's overview what WireGuard VPN protocol is. And why commercial VPN service providers were quick to implement it. What is a VPN protocol? The first protocols were developed way back in 1969 when the Internet was called ARPANET and was primarily a military project. However, soon ARPANET grew in size, and two networks - ARPANET and MILNET - were separated for research and military purposes respectfully. A set of rules and principles governed communication between these two separate networks called protocols. Protocols are sets of rules developed to govern the exchange of information packets over an extensive network of interconnected computers. It defines what information is and how information travels from one network to another. For example, Internet Protocol governs information exchange, and Transfer Control Protocol defines how data is divided into packets, forming TCP/IP or Internet Protocol Suite. At its very core, VPN protocols are the same. However, since VPNs have been created for business and, more recently, public Internet safety, VPN protocols also include encryption standards, which vary significantly per protocol. To put it shortly, VPN protocols are sets of rules that govern how a secure connection tunnel between the users' device and the VPN server is established, how packets travel through the tunnel, and what encryption is applied to secure that tunnel. What is WireGuard protocol? WireGuard is a VPN protocol that was developed by security researcher Jason A. Donenfeld, starting in 2016 and still actively in development. However, WireGuard provides a practical, innovative, and deployable solution to a lot of problems that VPNs struggle with: security, efficiency (speeds), and auditing. The latter is especially important for commercial VPN providers that strive to maintain their reputation by employing third-party auditors to test the steel of their service. First of all, WireGuard consists of only 4000 lines of code approximately. The number reveals the difference way better in comparison - OpenVPN consists of nearly 600 thousand lines of code and IPSec 400 thousand. Not only does it make WireGuard easier to deploy, but it also makes it way faster, some reporting four times the speed when compared to the aforementioned VPN protocols. Security also benefits from a dense code, the fewer the lines - the fewer points an attacker can exploit, reducing attack perimeter. Last but not least is easy audits. It will take days for a professional auditing team to review OpenVPN, IPSec, or other VPN protocol to produce accurate results and find vulnerabilities. The same problem does not haunt WireGuard protocol, since This makes work much easier both for auditors and developers alike, and users benefit from a safer, more reliable service. "the code is intended to be easily auditable, with Donenfeld saying it can be read in an afternoon." What are the benefits of WireGuard? For most commercial VPN users speeds are of utmost importance, so let's secure this one first. Because of modern encryption techniques, dense code, and a few other reasons, WireGuard excels at the connection to the server (nearly instantaneous), and data transfer speeds. See the image below for NordVPN speed comparison on , IKEv2, and OpenVPN protocols. NordLynx (our WireGuard implementation) Second, and this might be considered a negative by some, but nevertheless a crucial part of WireGuard is that it leaves behind classic cryptographic solutions and focuses on modern, tested and peer-reviewed encryption implementations. For example, WireGuard utilizes ChaCha20 for encryption solution, instead of using a commonly accepted AES-256 encryption as it's standard. This exchanges cryptographic agility for easier deployability and establishes its own security standard, which users can't modify (sometimes for their own good). We also used XChaCha20 encryption for our other service NordPass password manager. To summarize, WireGuard entered the VPN market at precisely the right time, when ease-of-use, security, reliability, and efficient auditing were problems to be solved. In the very end, more people should use cybersecurity software, but it is less likely to happen if the services they are offered are not comfortable to use. And WireGuard VPN protocol provides a solution to most of these problems - that's why major commercial VPN service providers were fast to implement it. And for those that want to start protecting themselves online, NordVPN now offers NordLynx protocol, which is based on Wireguard® and adapted to maintain our strict no-logs policies. More about Nord Security was developed by Nord Security, a multinational company offering everyday cybersecurity solutions. With a growing global user base of 14 million, NordVPN is a leader among VPN providers. To protect user privacy, NordVPN operates out of Panama — a jurisdiction without data retention laws. NordVPN The company has recently been taking big steps towards becoming “more than just a VPN,” with the launch of several features beyond your regular virtual private network. One such feature is , offering ad and tracker blocking and protection against malware. Threat Protection Nord Security offers several other cybersecurity products: — an encrypted password manager NordPass — file encryption and storage NordLocker — a VPN for businesses NordLayer How much does NordVPN cost? has three pricing plans: 2-year, 1-year, and monthly. The 2-year plan offers the best value at $3.29/month for two years (taken as one payment of $78.96). NordVPN The 1-year plan is the second-best option for value, offering 39% off right now. You’ll pay $59.88, amounting to $4.99 per month. You can also pay monthly, but the cost increases to $11.99/month. NordVPN often has special deals and discounts, especially with the 2-year subscription plans. Right now, NordVPN’s “Back to school” offer will save you 65% and gift you three free months of service. All plans come with a 30-day money-back guarantee that’ll guarantee a full refund if you’re unhappy with the service. Customer Support at NordVPN NordVPN offers 24/7 customer support that helps users solve any issues and make the most of their cybersecurity products. You can reach the support team via chat or email. For more information about NordVPN’s products and services and cybersecurity news, visit . You’ll find answers to your technical questions on how to use NordVPN in the . the NordVPN blog FAQ section Disclaimer: WireGuard® is a registered trademark of Jason A. Donenfeld.

WireGuard Protocol and NordLynx, or why your VPN got a lot faster recently?

This year began in chaos. The chaos brought numerous challenges to both businesses and employees alike. With a significant portion of the population working from home, home network security and online safety's been brought to the forefront of technological challenges. Now that the year is coming to a closer end, 2020 reports are revealing an increase in cyber-attacks and consequential financial losses. At the beginning of last year, that "Hackers Are Passing Around a Megaleak of 2.2 Billion Records." Data leaks have been a problem for over a decade, and several years later they were capitalized by cybercriminals in the form of Credential Stuffing cyber attacks. This February it was reported that Credential Stuffing attacks , making them particularly dangerous for financial institutions. And two weeks ago the FBI (Private Industry Notification) warning about a spike of these kinds of attacks against the US financial sector. a report came out started targeting APIs released a PIN But Credential Stuffing attacks hurt casual Internet users just as much as they do businesses. At the very end, it is their accounts that are being taken over, as many Disney+ early subscribers could confirm, having their accounts stolen and sold for as cheap as $3 on black markets, instead of $6.99 original cost. However, as will be soon explained, Credential Stuffing massively relies on incompetent password use and, more importantly, reuse, and there is a simple solution to the problem - password managers. So let's overview what a Credential Stuffing attack is, and how exactly can password managers help with the issue, with some noteworthy service recommendations at the very end of the read. What is a Credential Stuffing attack? One of the main reasons that Credential Stuffing attacks became so common is the lack of technical skills required to carry out one. The principle is this: 1. A massive amount of username-password combinations, called combolists, leak from some vulnerable services (for example, infamous Marriott hotel data leak); 2. These combolists are being sold or passed around in the black markets and obtained by an interested party; 3. With the help of automatization software and a proxy list or a botnet, the combolist is tried on another service in hopes that the same password was reused; 4. In case of success, account takeover is initiated. The process is straightforward and usually has 0.5%-3% success rate, which is a lot considering combolists may contain as much as 5 million leaked units if not more. A common mistake, as , to notice is that having a complex password makes no difference if the same password is reused twice or more - that's what "Stuffers" hope for in the first place. cybersecurity writers at password manager NordPass inform Earlier this year, American computer and network security company RSA Security drawing attention to the "credential stuffing gold rush." The point to take from the report is an emphasis on the monetization part of Credential Stuffing. There are concrete and easily extractable profits from these undemanding attacks. And that seduces many cybercriminals, hence the "gold rush". Check the image below for possible account types to be exploited for an easy grab. released a threat report Furthermore, according to SplashData, the most common passwords still include "12345", "password", "qwerty", and alike. This way there's not even a need for a username-password part, because cybercriminals can try stuffing these generic, and, unfortunately, still used classics in hopes of success. That's why it's important to use separate and unique passwords for each service you use. that a business user manages 191 passwords on average; needless to say, it's not possible to remember that many different passwords, and writing them down in one place defeats the whole purpose. LastPass reported Luckily, password managers have been there for a long time, some going as early as 2003, and some joining the market as we speak (check the password manager recommendations at the end of this article). However, various researches still inform that password managers aren't implemented as widely as they should be, and standard practices of remembering my passwords fall flat. That's why I'd like to draw attention to the more secure way of protecting your online accounts and recommend a few password managers that excel in particular fields they specialize at. How do password managers work? First of all, password managers allow storing different, unique, complex passwords in one place, without exposing these passwords to the risk of being leaked. Furthermore, most advanced password managers have zero-knowledge architecture, which means that not even they could take a look at your passwords, even if some rogue admin at their company felt like it. So how do they do that? What password managers do is take all your passwords and encrypt them in one place, called the vault. Encryption standards may differ, and so may the place where the vault is stored. In layman's terms, it may be an offline password manager, storing your passwords on your device and nowhere else; or it might be a cloud-based password manager, which holds the vault on the server. Both have pros and only a few cons, however, both methods are considered trustworthy. Instead of remembering all your passwords, you only need to remember one - your master password. The master password is used to decrypt the vault solely by you, and only you do the encryption/decryption, because of zero-knowledge architecture. In a cloud-based solution you send the master-password to the server in multiple times hashed form (a method of encryption) so the server cannot derive the original password from it and unlock the vault. The master password cannot leak or be stolen from the server. This is a simplified explanation, for those interested in digging deeper I'd suggest reading the rest of my cybersecurity articles on Hacker Noon. The key takeaway is that all of your different passwords are encrypted and unattainable to anybody else except you. That's why it's highly advisable to remember the master password by heart, or write it down and put somewhere only you will find because once it's lost nobody will be able to retrieve your passwords. That's why password managers work and are widely recommended by cybersecurity experts. Having in mind that different password managers suit a particular category of users, I'd like to recommend three divergent password managers that excel in specific areas. A user-friendly password manager for comfort, a freemium password manager, and a free password manager for advanced users. But keep in mind, that doesn't mean other services in the market are less suited for your needs and doing your research is a good way to go. NordPass Ease-of-use with advanced encryption. NordPass joined the password manager industry in 2019 from the same company that owns a prominent Virtual Private Network NordVPN. VPNs rely heavily on encryption, and it reflects on this product, because, to my knowledge, NordPass is the only password manager that uses XChaCha20 encryption instead of the commonly used AES-256 algorithm. You can expect this password manager to work slightly faster. However, a stronger argument would be that XChaCha20 is a more innovative way of handling encryption and already is being implemented by Google and Cloudflare. Furthermore, NordPass, alongside his big brother NordVPN, is known for minimalistic easy-to-use App design and responsive customer support. You will be able to easily add-remove passwords, autofill them in web pages instead of tiresome typing, cross-device functionality and secure password generating, among other features. Data breach scanner, which will alert you if your password has been leaked, is scheduled soon - a valuable addition to an already promising service. LastPass Best freemium password manager. LastPass is one of the best-known password managers that was introduced in 2008. It offers a fully functional free service, which can be upgraded to premium or family plans. With browser extension on all major browsers, it allows password autofill, cross-device compatibility, Multi-factor authentication (MFA), and more. Upgrades will enable priority technical support, 1GB encrypted file storage, DarkWeb scanner for password leaks, and password management benefits for family use. Since it's been in the market for a long time, LastPass had a few vulnerabilities, none of them resulting in password leak or compromise. Furthermore, the last serious issue was fixed within 24 hours, strengthening their reputation as a hard-working business that takes security seriously. KeePass Free password manager for advanced users only. KeePass has secured a rock-solid reputation among those willing to put an extra effort into learning to manage a powerful cybersecurity software. Moreover, it's open-source software, which is appreciated by software developers who want to know the intricacies of the service they use or even contribute to fixing the bugs and making improvements. Nevertheless, KeePass has been praised for granting complete control over your data and high customization. If you're a tech-savvy person that likes the challenge of setting things up your way - this service will not leave you wanting more. Summing that up with the availability of various plugins and improvements is what makes KeePass a solid choice for advanced users.

The Anatomy of Credential Stuffing Attacks in 2020 

Here is a workable, reusable way to test an expressjs/mongoose application. What we’re dealing with It assumes the following setup; i.e. what every project could be expected to have: expressjs project
   |- api
       |- app.js
       |- database.js
   |- test
        | test1.test.js
        | test2.test.js
        | ... Stripped down, your app will probably look something like this: app.js bodyParser = ( ) cors = ( ) express = ( ) database = ( ) app = express() app
  .use(cors())
  .use(bodyParser.json())
  .use(bodyParser.urlencoded({ : })) database
  .dbconnect()
  .on( , err => .log( )) app.get( , (req, res) => {
    res.send( )
}) app.listen( , () => .log( )
) .exports = app const require "body-parser" const require "cors" const require "express" const require "./database" let // Pretty standard API app extended true // The article covers this later "error" console "Connection to database failed." // Standard route "/" async "Hello world" // other... better stuff here! 5000 console "Server started at port http://localhost:5000" module Yep! Vanilla expressjs! The bit to focus on is the line - an import which utilises a nice pattern to handle the Mongo connection implementation. Looking at the module imported will make sense of the call above: const database = require(“./database”) database.dbconnect() mongoose = ( ) { MONGODB_URL } = process.env {
  mongoose.connect(MONGODB_URL, { : , : , : , : ,
  }) mongoose.connection
} { mongoose.disconnect()
} .exports = { dbconnect, dbclose } const require "mongoose" const // or some other source of the cnn str ( ) function dbconnect useNewUrlParser true useCreateIndex true useUnifiedTopology true useFindAndModify false return ( ) function dbclose return module So that’s where we are. Nothing special… a simple app running alongside a server using the library. expressjs MongoDB mongoose This article assumes you have an app already; we’re focused on testing it. The cluttered approach to testing an express API Let’s imagine how things might look in your tests right now. could look something like this: test1.test.js describe( , () => {
  before( () => { })
  
  beforeEach( () => { })
  
  after( () => { })

  it( , done => {
    request(app)
      .post( )
      .send({ : })
      .end( {
        res.should.be.tested.thoroughly.here
        done()
      })
  })
}) "testing POST /wizard" async //before stuff like setting up the app and mongoose server. async //beforeEach stuff clearing out the db. async //after stuff like shutting down the app and mongoose server. "tests wizard creation" "/wizard" name "wizard1" ( ) => err, res … not dissimilar, with a lot of repetitive garbage: test2.test.js describe( , () => {
  before( () => { })

  beforeEach( () => { })
  
  after( () => { })

  it( , done => {
    chai
      .request(app)
      .post( )
      .send({ : })
      .end( {
        res.should.be.tested.thoroughly.here
        done()
      })
  })
}) "testing POST /apprentice" async //before stuff like setting up the app and mongoose server. async //beforeEach stuff clearing out the db. async //after stuff like shutting down the app and mongoose server. "tests apprentice creation" "/apprentice" name "apprentice1" ( ) => err, res Repetitive and cluttered: If you agree, the purpose of this article is to look at a way of cleaning that all up. A good deal clearer First, we create a module; a single place we can put the repetitive clutter from all our tests. I will call this a “Test Suite”. To separate it visually from the actual tests, I would put it inside a folder, like so: suites project
   |- api
       |- app.js
       |- database.js
   |- tests
        |- test1.test.js
        |- test2.test.js
        |- suites
             |- mochaTestSuite.js Here is the scaffold of such a suite: .exports = {
  describe(testDescription, () => {
    before( () => { })

    beforeEach( () => { })

    after( () => { })

    testsCallBack()
  })
} module ( ) => testDescription, testsCallBack async //before stuff like setting up the app and mongoose server. async //beforeEach stuff clearing out the db. async //after stuff like shutting down the app and mongoose server. The more eagle-eyed among you will have noticed it isn't much different from the two tests we already have. It has two parameters. A and a . description callback And this is how we intend to use it in, for example, : test1.test.js mochaTestSuite = ( )

mochaTestSuite( , () => {
  it( , done => {
    chai
      .request(app)
      .post( )
      .send({ : })
      .end( {
        res.should.be.tested.thoroughly.here
        done()
      })
  })
}) // usual require stuff we will cover later const require "./suites/mochaTestSuite.js" "the test description" "tests wizard creation" "/wizard" name "wizard1" ( ) => err, res The same eagle-eyes will also have noticed we haven't done anything much more than replace the function (which was originally in test1 and test2) with the new call — then delete all those before/after calls. describe mochaTestSuite In fact, the two parameters - and the for the tests - work in the same way (in the test suite we’re writing) as they do in the bog standard function we normally use. description callback exactly describe A Finished Test Suite Rather than laboriously “then add this” and “then do this”… here is, without further preamble, a finished . mochaTestSuite chai = ( ) chaiHttp = ( ) mongoose = ( ) request = ( ) { MongoMemoryServer } = ( ) app = ( ) mongooseConnect = ( ) should = chai.should()
chai.use(chaiHttp) .exports = {
  describe(testDescription, () => { signUpThenLogIn = {
      chai
        .request(app)
        .post( )
        .send({ : ,
          ...credentials,
        })
        .set( , )
        .set( , )
        .end( {
          chai
            .request(app)
            .post( )
            .send(credentials)
            .set( , )
            .set( , )
            .end( {
              should.not.exist(err)
              res.should.have.status( )
              res.body.token.should.include( )
              testCallBack(res.body.token)
            })
        })
    } clearDB = { ( i mongoose.connection.collections) {
        mongoose.connection.collections[i].deleteMany( {})
      }
    }

    before( () => { mongoServer = MongoMemoryServer() mongoUri = mongoServer.getUri()
      process.env.MONGODB_URL = mongoUri mongooseConnect.dbconnect()
    })

    beforeEach( () => { clearDB()
    })

    after( () => { clearDB() mongooseConnect.dbclose()
    }) testsCallBack(signUpThenLogIn)
  })
} // test/suites/mochaTestSuite.js const require "chai" const require "chai-http" const require "mongoose" const require "supertest" const require "mongodb-memory-server" const require "../../api/app.js" const require "../../api/database" const module ( ) => testDescription, testsCallBack // Bonus utility const ( ) => credentials, testCallBack "/auth/Thing/signup" name "Wizard" "Content-Type" "application/json" "Accept" "application/json" ( ) => err, res "/auth/Thing/login" "Content-Type" "application/json" "Accept" "application/json" ( ) => err, res 200 "Bearer " // Database connector const => () for var in => () async let new const await await async await async await await // Run the tests inside this module. A little unpacking: See how the setup we saw in the intro to this article, really helps us here? api/database.js The before/after is straightforward: Start the mongoServer; connect to it/Stop it; close it. In we clear the database, putting the clearing code into another function we can “await”. beforeEach The important bit is the callback . What happens is this. When you call , your statements are wrapped into the callback function parameter we discussed earlier. first sets up the tests inside its own statement, running the necessary before and after statements, then it (duh) callsback the function you declared with one or more functions. testsCallBack mochaTestSuite it mochaTestSuite describe it I included a function, which I will explain shortly. The point here is to show how all sorts of reusable code can be put into the suite, decluttering your actual tests. signUpThenLogIn Usage Now we can declutter our tests like: chai = ( ) chaiHttp = ( ) request = ( ) mongoose = ( ) app = ( ) mochaSuite = ( ) should = chai.should()
chai.use(chaiHttp)

mochaTestSuite( , signUpThenLogIn => {
  it( , done => {
    chai
      .request(app)
      .post( )
      .send({ : })
      .end( {
        res.body.name.should.equal( )
        res.should.be.thoroughly.tested.in.other.ways
        done()
      })
  })
}) const require "chai" const require "chai-http" const require "supertest" const require "mongoose" const require "../api/app.js" const require "./suites/mochaSuite" const "testing POST /wizard" "creates Wizards" "/wizard" name "wizard1" ( ) => err, res "wizard1" Sweet. With all the before and after setup being handled by the suite, we can focus on testing functionality. The has two parameters, the and the function - which will (duh!) callback to run the actual tests inside itself, having setup the app and mongoose servers for them. mochaTestSuite description callback And that’s it really. But I promised to show you how the would work. Some of your requests may need to be authenticated and it helps to outsource that clutter as well. signUpAndLogInfunction In fact, it works in a similar way, except ’s parameter will be inside one of your it tests. signUpAndLoginIn callback mochaSuite = ( )

mochaTestSuite( , signUpThenLogIn => {
  it( , done => {
    signUpThenLogIn(
      { : , : },
      token => {
        chai
          .request(app)
          .post( )
          .send({ : }) .set( , token)
          .end( {
            res.body.name.should.equal( )
            res.should.be.thoroughly.tested.in.other.ways
            done()
          })
      }
    )
  })
}) // requires as normal const require "./suites/mochaSuite" "testing POST /apprentice" "Logs in Wizard can create Apprentices" username "grandwizard" password "IShallPass" "/apprentice" name "apprentice1" // use the token "Authorization" ( ) => err, res "apprentice1" So… passes into the callback. mochaTestSuite signUpThenLogIn In your tests (which require auth) use the function by passing in two parameters (the and (surprise surprise) the to run the actual test post-login, using the token provided by the callback. credentials callback This would work for other types of login as well, not just token based login. This also shows you how other features can be added to the test suite to “outsource” the laborious, repetitive code that tests need just to get them prepped for actually running. Cleaner tests not only help with debugging but help other developers who might be looking at your tests to understand how to use your code. Core, Thanks! https://expressjs.com/ https://mochajs.org/ https://www.chaijs.com/ Photo by on Sieuwert Otterloo Unsplash

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