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Vulnerability research, CVE deep dives and engineering write-ups from the Ostorlab team on AI pentesting and mobile, web and API security testing.

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See how Ostorlab detects LLM vulnerabilities through banking chatbot examples of private statement leaks, unauthorized tool actions and prompt injection.

Security

Ostorlab Neutron on UC Berkeley CyberGym: 97.1% Verified Exploitation (1,463/1,507 Tasks)

A technical deep-dive into how Ostorlab Neutron reached a 97.1% verified exploit solve rate (1,46...

Sep 15, 2026

Product

October 2026: From Security Findings to Tested Fixes

We added approvals to control dangerous actions, introduced Ticket Agent for autonomous triage an...

Oct 17, 2026

Security

Ostorlab vs MobSF: Analyst-Driven vs AI-Driven Mobile Security Testing (2026)

Ostorlab vs MobSF (Mobile Security Framework) for mobile app security testing: static and dynamic...

Oct 07, 2026

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False positives are an engineering-capacity problem, not only a scanner-quality problem. Learn how to measu...

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Jul 22, 2026

Learn how source code security testing works, why traditional SAST creates false positives, and how agentic...

Jul 16, 2026

See how Ostorlab detects LLM vulnerabilities through banking chatbot examples of private statement leaks, u...

Oct 23, 2026

The best Snyk Code, Checkmarx One and GitHub Advanced Security alternatives for SAST in 2026, and how Ostor...

Oct 07, 2026

How a small agent that turned bug tickets into pull requests became Ostorlab's ticket agent: an AI teammate...

Oct 06, 2026

Ostorlab vs MobSF (Mobile Security Framework) for mobile app security testing: static and dynamic analysis,...

Oct 07, 2026

Ostorlab vs Oversecured for mobile app security testing: iOS and Android coverage, exploit proof, authentic...

Oct 07, 2026

Ostorlab vs. pentesting firms: cost, testing frequency, depth and remediation, and when to use AI pentests,...

Sep 25, 2026