Trail of Bits has released gosentry, an enhanced fork of the Go toolchain designed to significantly improve native Go fuzzing capabilities by integrating LibAFL and Nautilus. The tool allows security researchers and developers to perform struct-aware and grammar-based fuzzing, successfully identifying complex vulnerabilities such as integer overflows, data races, and goroutine leaks that standard Go fuzzing often misses.
Vulnerability Discovery
6 posts
Go fuzzing was missing half the toolkit. We forked the toolchain to fix it. Tune In: The Future of AI-Powered Vulnerability Discovery The article discusses the impending 'vuln-pocalypse' driven by AI-accelerated vulnerability discovery and fuzzing. Threat actors, including FANCY BEAR and FAMOUS CHOLLIMA, are increasingly leveraging AI to enhance phishing campaigns and exploit zero-days faster, necessitating a shift toward threat-informed patch prioritization and robust post-exploitation behavioral detection.
The Industrialization of Exploitation: Why Defensive AI Must Outpace Offensive AI The cybersecurity landscape is experiencing a shift towards industrialized exploitation driven by offensive AI and LLMs. These technologies act as orchestrators that rapidly discover vulnerabilities and generate exploits, necessitating defensive AI and behavioral analytics to counter machine-scale attacks.
Why AI-Powered Vulnerability Discovery Strengthens Akamai's Security Mission Anthropic's new AI capabilities, Project Glasswing and Claude Mythos Preview, are accelerating the discovery of zero-day vulnerabilities across major software platforms. Akamai asserts that this rapid discovery will widen the gap between vulnerability identification and patching, thereby increasing the critical need for robust runtime protection and edge security solutions to defend against potential exploits before patches are available.
Master C and C++ with our new Testing Handbook chapter Trail of Bits has published a new C/C++ security checklist in their Testing Handbook, detailing common bug classes, API gotchas, and environment-specific vulnerabilities across Linux and Windows. The guide serves as a foundation for manual code review and highlights specific issues like libc quirks, Windows driver registry flaws, and seccomp/BPF sandbox bypasses.
AI in Vulnerability Discovery: A Call for Human Oversight and Caution The integration of AI in vulnerability research has led to a surge in false-positive bug reports, overwhelming vendors and bug bounty programs. Human oversight remains essential to validate AI findings and maintain the integrity of the CVE ecosystem.
