aiqbench analysis
This article focuses on an AI-driven security agent named PageBreak that leverages Gemini models to autonomously discover and validate over 500 cross-site scripting vulnerabilities in Google's web applications. By employing a proof-driven workflow where the AI generates hypotheses and a dedicated validator confirms exploitability, the system significantly reduces false positives while demonstrating advanced autonomous testing capabilities. This represents a significant advancement in using machine learning for automated software supply chain security and vulnerability management.
Google’s AI Hacker Finds 500+ XSS Flaws and Builds Working Exploit Chains
Google has revealed an internal AI security agent that found more than 500 verified cross-site scripting, or XSS, flaws across its own web applications. The system, called PageBreak, searches for weaknesses that could let an attacker run unwanted code in a visitor’s browser, including on sensitive services. The announcement matters because AI scanners can generate […] The post Google’s AI Hacker Finds 500+ XSS Flaws and Builds Working Exploit Chains appeared first on Cyber Security News.
Google has revealed an internal AI security agent that found more than 500 verified cross-site scripting, or XSS, flaws across its own web applications. The system, called PageBreak, searches for weaknesses that could let an attacker run unwanted code in a visitor’s browser, including on sensitive services. The announcement matters because AI scanners can generate large numbers of doubtful reports. PageBreak instead tests each suspected weakness against a live environment, looking for proof that a real attack works before it is sent to engineers. This reduces…
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