OpenAI has developed an automated cybersecurity research pipeline that identified 948 distinct Linux kernel vulnerabilities capable of allowing local users to gain root access, while uncovering at least 10 previously undocumented exploitation techniques.

The system analyzed thousands of potential security issues, reproduced vulnerabilities in controlled environments and generated working exploits and candidate patches for human review.

In a research post, OpenAI said the pipeline identified 2,308 candidate findings and dynamically reproduced 1,724 of them. It subsequently generated 1,169 working local privilege escalation (LPE) exploits, which variant analysis narrowed to 948 distinct vulnerabilities.

The mid-October 2026 campaign used an upcoming cyber model that the company has not yet publicly identified. The full run cost $1.21 million in API credits, averaging about $1,279 per distinct LPE vulnerability.

The research highlights how increasingly capable models could help security teams identify and fix flaws in critical software before attackers exploit them.

OpenAI’s system followed a five-stage process covering vulnerability discovery, dynamic validation, exploitability assessment, patch generation and human review.

Scout agents first identified security-relevant sections of the Linux kernel, narrowing the audit to 5,034 targets covering about 2.8 million lines of code, or roughly 7 percent of the codebase.

Our security researchers built an autonomous cyber vulnerability discovery, exploitation, and patching pipeline.

In a single run with an upcoming cyber model, it validated and generated patches for 948 local privilege escalation vulnerabilities in the Linux kernel at a total API… pic.twitter.com/Nu2I0n2ayI

Analyst agents then examined those targets and produced 2,308 candidate findings within 12 hours.

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