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Bright Security launches STAR Fuzzer for agentic harness generation

Original title: Bright Security Introduces STAR Fuzzer, Agentic Fuzzing That Writes Its Own Harnesses and Proves Every Finding

Cyber Security Newsby Cybernewswire ()11 min read3
Part of a story covered by 2 sourcesBright Security launches STAR Fuzzer with AI-written harnessesMerged summary & timeline
AI summary · x-ai/grok-4.7Summaries by Vani AI

The vendor says a first research run flagged High or Critical issues in 45% of projects tested.

Bright Security launched STAR Fuzzer, a mode of its STAR platform available at brightsec.com/fuzzer. AI selects security-critical functions and writes harnesses, while an evolutionary engine searches for crashes, memory exhaustion and memory-safety bugs without a running application. The company says the first open-source run found High or Critical issues in 45% of projects, and the first month produced ten published findings in eight projects, including the Crystal standard library, htop and RIOT OS.

Unconfirmed: Finding counts and coverage figures are Bright Security's own claims and are not independently verified.

Key facts
  • Confirmed findings include a byte-exact payload that reproduces the crash.
  • Named projects include the Crystal standard library, htop and RIOT OS.
  • A libxml2 harness reached about 13,600 regions in a 5-million-execution run, the vendor says.
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From the original article

11 min read at cybersecuritynews.com

San Rafael, United States, October 19th, 2026, CyberNewswire Built on an evolutionary engine first released in 2018, STAR Fuzzer by Bright Security finds crashes, memory exhaustion and memory-safety bugs in security-critical code without a running application. In its first open source research run, it found High or Critical issues in 45% of the projects tested, […]

Cyber Security News

By Cybernewswire · 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.