The blog post argues that speedrunners possess many of the same skills and mindsets as vulnerability researchers. They both meticulously analyze systems, searching for unusual behavior and edge cases that can be exploited for an advantage, whether that's saving milliseconds in a game or bypassing security measures. Speedrunners develop a deep understanding of a system's inner workings through experimentation and observation, often uncovering unintended functionality. This makes them naturally suited to vulnerability research, where finding and exploiting these hidden flaws is the primary goal. The author suggests that with some targeted training and a shift in focus, speedrunners could easily transition into security research, offering a fresh perspective and valuable skillset to the field.
This blog post explores the challenges of creating a robust test suite for Time-Based One-Time Password (TOTP) algorithms. The author highlights the difficulty in balancing the need for deterministic, repeatable tests with the time-sensitive nature of TOTP codes. They propose using a fixed timestamp and shared secret as a starting point, then exploring variations in time steps and time drift to ensure the algorithm handles edge cases correctly. The post concludes with a call for collaboration and shared test vectors to improve the overall security and reliability of TOTP implementations.
The Hacker News comments discuss the practicality and usefulness of the proposed TOTP test suite. Several commenters point out that existing libraries like oathtool already provide robust implementations and question the need for a new test suite, suggesting that focusing on testing against these established libraries would be more effective. Others highlight the potential value in testing edge cases and different implementations, particularly for less common languages or when implementing TOTP from scratch. The difficulty in obtaining a diverse and representative set of real-world TOTP secrets for testing is also mentioned. Finally, some commenters express concern about the security implications of publishing a comprehensive test suite, fearing it could be misused for malicious purposes.
Roark, a Y Combinator-backed startup, launched a platform to simplify voice AI testing. It addresses the challenges of building and maintaining high-quality voice experiences by providing automated testing tools for conversational flows, natural language understanding (NLU), and speech recognition. Roark allows developers to create test cases, run them across different voice platforms (like Alexa and Google Assistant), and analyze results through a unified dashboard, ultimately reducing manual testing efforts and improving the overall quality and reliability of voice applications.
The Hacker News comments express skepticism and raise practical concerns about Roark's value proposition. Some question whether voice AI testing is a significant enough pain point to warrant a dedicated solution, suggesting existing tools and methods suffice. Others doubt the feasibility of effectively testing the nuances of voice interactions, like intent and emotion, expressing concern about automating such subjective evaluations. The cost and complexity of implementing Roark are also questioned, with some users pointing out the potential overhead and the challenge of integrating it into existing workflows. There's a general sense that while automated testing is valuable, Roark needs to demonstrate more clearly how it addresses the specific challenges of voice AI in a way that justifies its adoption. A few comments offer alternative approaches, like crowdsourced testing, and some ask for clarification on Roark's pricing and features.
Testtrim, a tool designed to reduce the size of test suites while maintaining coverage, ironically struggled to effectively test itself due to its reliance on ptrace for syscall tracing. This limitation prevented Testtrim from analyzing nested calls, leading to incomplete coverage data and hindering its ability to confidently trim its own test suite. A recent update introduces a novel approach using eBPF, enabling Testtrim to accurately trace nested syscalls. This breakthrough allows Testtrim to thoroughly analyze its own behavior and finally optimize its test suite, demonstrating its newfound self-testing capability and reinforcing its effectiveness as a test suite reduction tool.
The Hacker News comments discuss the complexity of testing tools like Testtrim, which aim to provide comprehensive syscall tracing. Several commenters appreciate the author's deep dive into the technical challenges and the clever solution involving a VM and intercepting the vmexit instruction. Some highlight the inherent difficulties in testing tools that operate at such a low level, where the very act of observation can alter the behavior of the system. One commenter questions the practical applications, suggesting that existing tools like strace and ptrace might be sufficient in most scenarios. Others point out that Testtrim's targeted approach, specifically focusing on nested virtualization, addresses a niche but important use case not covered by traditional tools. The discussion also touches on the value of learning obscure assembly instructions and the excitement of low-level debugging.
Matt Keeter describes how an aesthetically pleasing test suite, visualized as colorful 2D and 3D renders, drives development and debugging of his implicit CAD system. He emphasizes the psychological benefit of attractive tests, arguing they encourage more frequent and thorough testing. By visually confirming expected behavior and quickly pinpointing failures through color-coded deviations, the tests guide implementation and accelerate the iterative design process. This approach has proven invaluable in tackling complex geometry problems, allowing him to confidently refactor and extend his system while ensuring correctness.
HN commenters largely praised the author's approach to test-driven development and the resulting elegance of the code. Several appreciated the focus on geometric intuition and visualization, finding the interactive, visual tests particularly compelling. Some pointed out the potential benefits of this approach for education, suggesting it could make learning geometry more engaging. A few questioned the scalability and maintainability of such a system for larger projects, while others noted the inherent limitations of relying solely on visual tests. One commenter suggested exploring formal verification methods like TLA+ to complement the visual approach. There was also a brief discussion on the choice of Python and its suitability for such computationally intensive tasks.
rqlite's testing strategy employs a multi-layered approach. Unit tests cover individual components and functions. Integration tests, leveraging Docker Compose, verify interactions between rqlite nodes in various cluster configurations. Property-based tests, using Hypothesis, automatically generate and run diverse test cases to uncover unexpected edge cases and ensure data integrity. Finally, end-to-end tests simulate real-world scenarios, including node failures and network partitions, focusing on cluster stability and recovery mechanisms. This comprehensive testing regime aims to guarantee rqlite's reliability and robustness across diverse operating environments.
HN commenters generally praised the rqlite testing approach for its simplicity and reliance on real-world SQLite. Several noted the clever use of Docker to orchestrate a realistic distributed environment for testing. Some questioned the level of test coverage, particularly around edge cases and failure scenarios, and suggested adding property-based testing. Others discussed the benefits and drawbacks of integration testing versus unit testing in this context, with some advocating for a more balanced approach. The author of rqlite also participated, responding to questions and clarifying details about the testing strategy and future plans. One commenter highlighted the educational value of the article, appreciating its clear explanation of the testing process.
Rishi Mehta reflects on the key contributions and learnings from AlphaProof, his AI research project focused on automated theorem proving. He highlights the successes of AlphaProof in tackling challenging mathematical problems, particularly in abstract algebra and group theory, emphasizing its unique approach of combining language models with symbolic reasoning engines. The post delves into the specific techniques employed, such as the use of chain-of-thought prompting and iterative refinement, and discusses the limitations encountered. Mehta concludes by emphasizing the significant progress made in bridging the gap between natural language and formal mathematics, while acknowledging the open challenges and future directions for research in automated theorem proving.
Hacker News users discuss AlphaProof's approach to testing, questioning its reliance on property-based testing and mutation testing for catching subtle bugs. Some commenters express skepticism about the effectiveness of these techniques in real-world scenarios, arguing that they might not be as comprehensive as traditional testing methods and could lead to a false sense of security. Others suggest that AlphaProof's methodology might be better suited for specific types of problems, such as concurrency bugs, rather than general software testing. The discussion also touches upon the importance of code review and the potential limitations of automated testing tools. Some commenters found the examples provided in the original article unconvincing, while others praised AlphaProof's innovative approach and the value of exploring different testing strategies.
This paper introduces a new fuzzing technique called Dataflow Fusion (DFusion) specifically designed for complex interpreters like PHP. DFusion addresses the challenge of efficiently exploring deep execution paths within interpreters by strategically combining coverage-guided fuzzing with taint analysis. It identifies critical dataflow paths and generates inputs that maximize the exploration of these paths, leading to the discovery of more bugs. The researchers evaluated DFusion against existing PHP fuzzers and demonstrated its effectiveness in uncovering previously unknown vulnerabilities, including crashes and memory safety issues, within the PHP interpreter. Their results highlight the potential of DFusion for improving the security and reliability of interpreted languages.
Hacker News users discussed the potential impact and novelty of the PHP fuzzer described in the linked paper. Several commenters expressed skepticism about the significance of the discovered vulnerabilities, pointing out that many seemed related to edge cases or functionalities rarely used in real-world PHP applications. Others questioned the fuzzer's ability to uncover truly impactful bugs compared to existing methods. Some discussion revolved around the technical details of the fuzzing technique, "dataflow fusion," with users inquiring about its specific advantages and limitations. There was also debate about the general state of PHP security and whether this research represents a meaningful advancement in securing the language.
Summary of Comments ( 57 )
https://news.ycombinator.com/item?id=43232880
HN commenters largely agree with the premise that speedrunners possess skills applicable to vulnerability research. Several highlighted the meticulous understanding of game mechanics and the ability to manipulate code execution paths as key overlaps. One commenter mentioned the "arbitrary code execution" goal of both speedrunners and security researchers, while another emphasized the creative problem-solving mindset required for both disciplines. A few pointed out that speedrunners already perform a form of vulnerability research when discovering glitches and exploits. Some suggested that formalizing a pathway for speedrunners to transition into security research would be beneficial. The potential for identifying vulnerabilities before game release through speedrunning techniques was also raised.
The Hacker News post titled "Speedrunners are vulnerability researchers, they just don't know it yet" sparked a lively discussion with several compelling comments.
Many commenters agreed with the premise, highlighting the similarities between speedrunning techniques and vulnerability research. One commenter pointed out that speedrunners, like security researchers, deeply understand the systems they're working with, often finding unintended behaviors and exploiting edge cases. They emphasized that both groups rely on meticulous documentation and sharing of findings within their communities.
Another commenter drew a parallel between sequence breaking in speedrunning and exploiting vulnerabilities in software. They explained how both involve understanding the underlying logic of a system to manipulate it in unexpected ways. This commenter also highlighted the iterative nature of both activities, where small optimizations accumulate to create significant overall improvements.
Some comments focused on the potential benefits of recruiting speedrunners for security research roles. One commenter suggested that speedrunners possess a natural curiosity and persistence that would be valuable in this field. They also noted that the competitive nature of speedrunning could translate well to the challenge-driven world of vulnerability research.
A few commenters offered counterpoints, acknowledging the overlap between the two fields but also highlighting key differences. They argued that while speedrunners exploit unintended behavior within the defined rules of a game, security researchers often deal with malicious actors exploiting vulnerabilities outside of any intended use case. This difference in context and motivation, they argued, necessitates a distinct skillset despite the shared analytical approach.
Another dissenting comment emphasized the difference in scope. While speedrunners focus on optimizing for speed within a known and controlled environment, security researchers often have to deal with complex and evolving systems where the full extent of vulnerabilities might be unknown.
One commenter provided a personal anecdote about a friend who transitioned from speedrunning to a career in security, further reinforcing the connection between the two fields. This story offered a practical example of how the skills honed through speedrunning can be directly applicable to security research.
Several commenters also discussed the legal and ethical implications of exploiting vulnerabilities, drawing a distinction between the acceptable practice within the controlled environment of a game versus the potential harm caused by exploiting vulnerabilities in real-world software systems.
Overall, the discussion on Hacker News affirmed the core argument that speedrunners possess skills and traits valuable to vulnerability research. While some commenters nuanced the comparison and highlighted key differences, the general consensus was that the mindset and methodologies employed by speedrunners have significant overlap with those used in security research.