How we found 24 Android vulnerabilities using our open source AI security agent

GitHub Security Lab’s open-source Taskflow Agent uses customized AI prompts and multi-step workflows to help security researchers audit Android applications by identifying mobile entry points and checking relevant vulnerability classes such as insecure intents, deeplink flaws, and cross-app scripting. The author reports finding and disclosing 24 Android vulnerabilities with these taskflows, which require a GitHub Copilot license, can consume substantial model tokens, and may take hours to run on medium-sized repositories. Examples include an OsmAnd flaw that allowed unprivileged apps to silently alter imported settings and redirect map-tile or route requests to attacker-controlled servers, potentially exposing users’ location and travel data, and chained Wikipedia Android deeplink and cookie-domain validation bugs that could enable phishing, cookie theft, and account takeover across Wikimedia services. While the workflows can uncover complex logic issues and demonstrate strong model knowledge of security-relevant APIs, the author notes that AI often produces low-impact findings, false positives, and inaccurate severity estimates, making human review, proof-of-concept development, and debugging essential.

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