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12 articles
Learn how to set up and use GLM-5.3, an open-source coding model, for code generation and vulnerability detection tasks.
OpenAI launches GPT-5.6-Cyber, a new AI model designed to help cybersecurity defenders identify vulnerabilities before attackers do.
Learn how to use AI-powered security tools to identify vulnerabilities in code and understand why human expertise remains essential for fixing security issues.
Cisco has unveiled two small, open-source AI models for cybersecurity that detect about 150 times more vulnerabilities per dollar than large AI agents like GPT-5.5.
Microsoft's elite security team has developed an AI-powered pipeline to find vulnerabilities in Windows and get them to engineers to build fixes. This initiative represents a major shift toward proactive threat identification using machine learning.
Explore how automated security testing tools integrate AI and ML to detect vulnerabilities in modern DevSecOps pipelines, ensuring rapid and secure software deployment.
This explainer explores Chainguard's Athena coalition, an AI-driven system that predicts and fixes open-source software vulnerabilities before attackers can exploit them, representing a shift from reactive to proactive cybersecurity.
An AI agent discovered 21 previously unknown vulnerabilities in FFmpeg, a widely used open-source multimedia framework. This development highlights the power of AI in automated cybersecurity and vulnerability detection.
OpenAI introduces Daybreak, a cybersecurity initiative that leverages AI and Codex Security to accelerate vulnerability detection and patch validation.
Learn how AI-assisted vulnerability discovery is revolutionizing software security by automatically identifying 271 vulnerabilities in Firefox 150, using advanced machine learning techniques.
This article explains how AI systems like Claude Mythos are used to find cybersecurity bugs, and how new studies show even smaller, open models can do the same job.
OpenAI's Codex Security tool moves away from traditional SAST methods, using AI-driven constraint reasoning to identify real vulnerabilities with fewer false positives. This approach could redefine how organizations handle code security by focusing on precision over volume.
