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The author developed a Datalog-based memory system for LLMs to maintain accurate state during investigations like vulnerability research, automatically updating conclusions when facts change.
Research article from PortSwigger demonstrating new XSS attack vectors using JavaScript properties in HTML tag names, enabling WAF bypasses across browsers.
This article revisits remote Spectre attacks on Cloudflare Workers, demonstrating a successful attack in production despite existing defenses. It details improvements to security mechanisms and announces the publication of a research paper on the findings.
OpenAI highlights the use of GPT-5.6-Cyber in real-world vulnerability research, including discovering previously unknown bugs in open-source software like Chrome's V8 engine.
Security researchers release a DEF CON 34 talk and tooling showing that Windows Plug and Play can silently download and execute vendor code as SYSTEM via attacker-controlled device identities, including through USB emulation and RDP USB redirection.
Security researcher James Kettle presented findings at Black Hat showing that while agentic AI is limited in autonomously devising novel hacks, it becomes a powerful partner when guided by humans, leading to the discovery of a new vulnerability class called Shared-Parser Confusion.
A security researcher discusses how LLM agents cannot distinguish between user instructions and text in documents, introducing AVE, an open standard for naming AI agent vulnerabilities that is cross-referenced with OWASP and MITRE frameworks.
Bugtraq, the historic full-disclosure security mailing list, is being revived. The new owner acquired securityfocus.com and pledges to restore researcher-first vulnerability disclosure and preserve the field's history.
This Unit 42 research discloses three novel attacks against passwordless authentication using Google's synced passkey ecosystem, showing how malware can take over passkey-protected accounts, bypass user verification, and extract private keys.
AI safety guardrails intended to prevent malicious use are also hindering legitimate offensive cybersecurity researchers, who need unrestricted model access to identify and exploit vulnerabilities for defense. Researchers criticize the arbitrary gatekeeping by AI companies like Anthropic and OpenAI.
This article explores using large language models to assist in writing exploits for FreeBSD kernel vulnerabilities, detailing two exploit chains that achieve full jail escape.
This article describes how researchers at Praetorian used Claude Opus (via Claude Code) to discover and exploit vulnerabilities in the FreeBSD kernel, including a stack overflow (CVE-2026-3038) that allows escape from FreeBSD jails. Part one focuses on methodology for finding bugs.
A detailed write-up from ProjectDiscovery detailing how they discovered a critical SQL injection vulnerability in Apple's Book Travel portal via Masa/Mura CMS and achieved Remote Code Execution.
This paper presents the first cross-platform reverse engineering and protocol-aware fuzzing study of Apple AirDrop and Android Quick Share, uncovering six vulnerabilities in these widely used proximity transfer protocols.
A blog post benchmarks four approaches (Semgrep, GLM 5.1 with Strix, cloud SOTA with code review skill, and local AI with a custom harness) for finding a known LFI vulnerability in PHPIPAM, finding that the local AI harness with a tailored approach outperforms the others.
OpenAI announces GPT-5.6 Sol, a model specialized for cybersecurity, improving performance-efficiency on long-horizon security tasks like vulnerability research and exploitation.
Reversecore MCP is an enterprise-grade AI-powered reverse engineering and security analysis tool that integrates with AI assistants via the Model Context Protocol, offering 50+ tools for static/dynamic analysis, malware analysis, vulnerability research, and more.
Anthropic's study demonstrates that large language models can rapidly generate working exploits from security patches, reducing the time from weeks to hours, raising concerns about AI-driven vulnerability exploitation.
The author built a vulnerable React Native app to test if LLMs could exploit a common Firebase misconfiguration, finding that only a few models (GPT 5.5, Deepseek V4 Pro, Claude Sonnet 4.6, Claude Opus 4-8) succeeded, with GPT 5.5 having the highest solve rate.
An AI-assisted security audit of FreeBSD uncovered 15 kernel vulnerabilities, including privilege escalations and a VM escape, and details the collaborative process of reporting and patching bugs with the FreeBSD team.