Search: “frontier models”

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CategoryAll AI safety & security 98 AI industry 82 AI research 51 Model release 41 AI policy 24 Industry 17 Threat actor 15 Tools 11 Data breach 8 AI tools & infra 6 Research 6 Advisory 3 Exploit / PoC 3 Policy & legal 3

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Hunting Vulnerabilities Using Frontier Models

Okta used frontier AI models GPT-5.5 Cyber and Mythos via OpenAI and Anthropic programs to scan millions of code lines for vulnerabilities.

Okta describes using frontier AI models, including GPT-5.5 Cyber Preview (TAC) and Mythos Preview, through OpenAI's Daybreak Cyber Partner Program and Anthropic's Project Glasswing to hunt vulnerabilities across its product codebase. The team built a custom Python orchestrator with strong isolation, vendor-agnostic model support, and four distinct scanning pipelines executed as isolated Codex or Claude Code sessions with progressive context loading to reduce context bloat. Human experts and AI agents worked both autonomously and in paired hunts, and Okta reports the best results when humans and agents taught each other.

Okta SecuritySep 8, 00:00 UTC · 9d agoResearch

VEX-Bench: Benchmarking LLM Agents for Assessing Exploitability of Software Supply Chain Vulnerabilities

Introduces VEX-Bench, 75 expert-labeled real-world cases testing whether LLM agents can assess supply chain vulnerability exploitability; frontier models reach about 80% F1.

VEX-Bench is the first benchmark evaluating LLM agents on assessing whether upstream dependency vulnerabilities are exploitable in downstream projects, with 75 real-world expert-labeled cases across Python, Java, and Go mined from GitHub. Nine models across three agent harnesses were evaluated; GPT-5.5 and Claude Opus 4.6 reach approximately 80% F1 on binary vulnerability-status classification, but only GPT-5.5 surpasses 70% macro-F1 on fine-grained justification classification. The gap highlights the difficulty of moving beyond binary exploitability calls to explaining exploitability reasons, unlike prior benchmarks targeting zero-day settings.

arXiv cs.CRSep 7, 22:52 UTC · 9d agoResearch1

Re: Retrospective by 'gpg.fail' authors

oss-security thread on the gpg.fail retrospective discusses legacy code removal and flaws surfaced by frontier AI models in open-source projects.

In a reply to Soatok Dreamseeker's gpg.fail retrospective thread on the oss-security mailing list, cryptographer Peter Gutmann argues it is often unclear which legacy code is obsolete or can be safely removed. He recounts a discussion with another well-known open-source project developer estimating, unscientifically, that around half of issues in such projects were found by frontier AI models. The exchange reflects on lessons from documenting weaknesses in GnuPG/OpenPGP implementations.

oss-security03:19 UTC · 8h agoResearch 9 sources

Why The Vulnerability Backlog Is About To Get Worse

Recorded Future analysis says AI-driven vulnerability discovery and faster weaponization will grow the triage backlog while shrinking defenders' response windows.

Disclosed vulnerabilities rose from roughly 21,000 in 2021 to nearly 50,000 in 2025, while Recorded Future assessed only 446 as actively exploited in 2025. VulnCheck found nearly 29% of 2025 KEV entries were exploited on or before CVE publication. The authors argue AI-assisted discovery and automated exploit development will multiply credible reports, cut disclosure-to-exploit time toward minutes, and force re-evaluation of medium-severity flaws as exploit-chain components.

Recorded FutureAug 26, 00:00 UTC · 22d agoResearch

Code review used to be the only way to catch these bugs

Palo Alto Networks' Unit 42 says its NOVA system found 14,090 vulnerabilities in 3,915 open-source projects, mostly non-crashing bugs like access control flaws.

Unit 42's NOVA system analyzed 3,915 open-source projects over two months and reported 14,090 validated vulnerabilities, only 85 of which matched previously documented findings. 92% of findings fell outside fuzzing-friendly categories, clustering instead in access control, path traversal, injection, prototype pollution, and SSRF; language ecosystems showed distinct weakness profiles. Of 5,421 supply-chain findings, 1,280 were flaws in dependencies while 4,141 were downstream exposures, 2,776 validated with working proof-of-concepts. Unit 42 warned that faster discovery combined with an average 55-day patch deployment window has collapsed the patch-to-exploit gap.

Help Net SecurityAug 25, 18:03 UTC · 22d agoResearch1

Risky Bulletin: Academics find source code overlaps between Geedge and China's Great Firewall

Academics linked Chinese vendor Geedge Networks' Tiangou Secure Gateway source code to one of the Great Firewall's three traffic filtering capabilities.

US researchers presenting at USENIX Security reconstructed Geedge Networks' Tiangou Secure Gateway firmware from over 100,000 leaked files, including Git repositories with commit history, and matched its filtering behavior to sections of China's Great Firewall. They found only 1 of 3 characterized DNS injectors matched Geedge code, noted the system relies on memory-unsafe C components and copied third-party code, and said its bugs could aid future circumvention tools. Geedge also exports censorship tools to Kazakhstan, Ethiopia, Pakistan, and Myanmar. The newsletter additionally rounds up multiple breaches.

Risky Business NewsAug 21, 02:55 UTC · 27d agoResearch2