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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.

Surse care acoperăCybersecurity News, LessWrong, Latent Space, Fortune

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Google’s AI Hacker Finds 500+ XSS Flaws and Builds Working Exploit Chains

Cybersecurity News5 octombrie 20265 min de cititArticolul și perspectiva sunt în engleză.

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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