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vulnerabilities
When the Scanner Starts Thinking: Learnings from Mythos & GPT 5.5 Cyber in Security Testing
Zscaler tested frontier artificial intelligence (AI) models Anthropic Mythos and OpenAI GPT 5.5 Cyber across black-box, artifact inspection, and white-box testing harnesses designed to simulate real attack and defense scenarios. The models demonstrated superior reasoning across multi-step attack chains, identifying twice as many high-severity findings twice as fast as legacy tools while maintaining higher signal-to-noise ratios after validation. Success depends on embedding frontier AI into structured testing workflows with proper context and expert guidance, while defenders must prepare through Zero Trust architecture, external exposure reduction, and AI-specific red teaming before threat actors exploit these capabilities at scale.
Why it matters: Security teams and leaders need to understand how frontier AI models can accelerate both vulnerability discovery and attack planning, then decide whether to invest now in structured AI-powered security testing, context management, and Zero Trust defenses before adversaries gain the same advantages.
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- First seen by Cybersecurity Tracker