RedAI – AI-driven vulnerability discovery and live validation

Hacker News

Most AI security tools stop at flagging code that looks vulnerable. You end up with a wall of "potential" findings and no way to know which ones are real without manually reproducing each one. Finding and fixing are both cheap now; actually proving which findings are real and impactful is the last remaining hurdle. RedAI is built to close that gap. After scanner agents surface candidates, validator agents take each one into a live environment — a running instance of the target — and try to prove or disprove the finding. They navigate UIs, hit endpoints, write PoC scripts, spin up helper servers, capture logs and screenshots. The end result is a report of real, reproducible vulnerabilities with PoC steps and screenshots to prove it.

Visit product View on Hacker NewsApr 22, 2026

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27%27% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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25%25% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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