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VULNERABILITY-DETECTION

Vulnerability-Detection

2 reports
All LLM Security Agentic AI Industry News Research Supply Chain Prompt Injection First Look: Security Regulatory Jailbreaks Adversarial ML Model Theft Data Poisoning AI Security Tools Security Operations
OpenAI Daybreak Vulnerability Detection Enables LLM Jailbreak

OpenAI Daybreak Vulnerability Detection Enables LLM Jailbreak

ATLAS OWASP MEDIUM Moderate risk · Monitor closely ▲ 7.2 The Hacker News

OpenAI has launched Daybreak, an AI-powered cybersecurity platform combining GPT-5.5 variants and Codex Security to automate vulnerability detection, threat modelling, and patch validation for enterprise codebases. The initiative introduces a tiered model access structure — including a permissive 'GPT-5.5-Cyber' for red teaming — raising questions about dual-use risk and model misuse if access controls are circumvented. The rollout also contextualises a broader industry tension: AI is accelerating vulnerability discovery faster than defenders can remediate, contributing to triage fatigue and hallucinated bug reports.

GPT-5.4-Cyber Jailbreak and Prompt Injection Risks

GPT-5.4-Cyber Jailbreak and Prompt Injection Risks

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 7.2 The Hacker News

OpenAI has launched GPT-5.4-Cyber, a cybersecurity-optimised model variant, alongside an expanded Trusted Access for Cyber (TAC) programme targeting authenticated defenders and security teams. While the initiative is framed as a defensive measure, the dual-use nature of a vulnerability-detection model introduces significant risk of adversarial inversion — where threat actors could exploit the same capabilities to discover and weaponise unpatched vulnerabilities at scale. OpenAI acknowledges this risk and states it is iteratively strengthening safeguards against jailbreaks and adversarial prompt injection as access broadens.

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