Trail of Bits has published a comprehensive new chapter in their Testing Handbook dedicated to security testing of Rust programs. The chapter covers dynamic analysis (Miri, proptest, coverage, mutation testing), static analysis (Clippy lints), manual review checklists for Rust-specific footguns, memory zeroization techniques, model checking with Kani, and supply chain vetting tools. Additionally, a Claude Code plugin called rust-review was released for automated Rust security reviews.
Static Analysis
5 posts
Rust-proof your code with our new Testing Handbook chapter We hardened zizmor's GitHub Actions static analyzer Trail of Bits collaborated with the maintainers of zizmor, a GitHub Actions static analyzer, to improve its parsing capabilities and robustness. By testing against a massive corpus of real-world workflows, they identified and fixed multiple YAML anchor handling bugs, deserialization edge cases, and expression evaluator flaws, significantly enhancing zizmor's ability to detect CI/CD misconfigurations.
Introducing Reachability for PHP Socket.dev has launched an experimental PHP reachability analysis tool designed to reduce vulnerability alert fatigue. By performing deep static analysis of function-level call graphs, including complex PHP dispatch patterns, the tool determines whether known CVEs in dependencies are actually executable within an application's context.
Trailmark turns code into graphs Trail of Bits has released Trailmark, an open-source library that converts source code into queryable call graphs to enhance AI-assisted security analysis. By integrating with Claude Code, Trailmark enables advanced mutation testing triage, blast radius analysis, and the identification of architectural bottlenecks in cryptographic libraries.
The Cost of Understanding: LLM-Driven Reverse Engineering vs Iterative LLM Obfuscation Elastic Security Labs conducted research on the capabilities of Large Language Models (LLMs), specifically Claude Opus 4.6, to reverse engineer obfuscated binaries. The research demonstrates that while LLMs can defeat traditional obfuscation, novel techniques targeting LLM weaknesses—such as context window limits, budget caps, and shortcut biases—can effectively and cheaply disrupt automated static analysis pipelines.
