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OpenAI AI uncovers 948 Linux kernel privilege escalation vulnerabilities

Original title: OpenAI Cyber Model Uncovers 948 Linux Kernel Privilege Escalation Vulnerabilities

Cyber Security Newsby Guru Baran ()3 min read2
Part of a story covered by 7 sourcesOpenAI AI Pipeline Discovers 948 Linux LPE VulnerabilitiesMerged summary & timeline
AI summary · x-ai/grok-4.7Summaries by Vani AI

AI agents validated 948 Linux kernel flaws in 30 hours, with patches starting within 10 days and bounties valued at $18.9M-$66.3M.

OpenAI's cyber model pipeline scanned Linux kernel source, selecting audit targets covering 2.8M lines of code. Analyst agents generated candidates, triage agents built PoCs, and exploit agents confirmed 1,169 privilege escalations after variant analysis. Maintainers patched 61 upstream in 10 days. The run cost over $1.2M and used new techniques not seen by kernel experts. Real-world chaining of kernel flaws with PHP2Shell has occurred.

Key facts
  • 948 unique vulnerabilities found and patched
  • Bounties could reach $66.3M
  • New exploitation techniques developed
  • Patches sent via Patch the Planet program
Security assessment · AI, from the articleNo known exploitation

Impact: gain root as normal local user

ProductAffected
Linux kernel—
OpenAI cyber model—
What to do
  1. 1.Install kernel updates immediately
  2. 2.Limit unprivileged user namespaces
  3. 3.Use sandboxes such as gVisor
Analyze this story with Vani AIImpact, who is affected and what defenders should do, in a new chat

From the original article

3 min read at cybersecuritynews.com

OpenAI says an automated research pipeline found and proved 948 separate Linux kernel privilege escalation flaws in one run. These bugs could let a normal local user gain root access. The run took place in mid-October 2026 and used an upcoming cyber model, as OpenAI explains in its research write-up.

Cyber Security News

By Guru Baran · cybersecuritynews.com

Read the full article at Cyber Security News

A short excerpt; the article and its images belong to the publisher. Summary, key facts and assessment above are AI-written from the article and can be wrong.