Cy

CyberGym/BountyBench-AI agents find zero-days and solve bug bounties

Hacker News

CyberGym/BountyBench-AI agents find zero-days and solve bug bounties

A turning point on AI agents in Cybersecurity, shown in two recent research papers from UC Berkeley and Stanford: CyberGym: AI agents discovered 15 zero-days in major open-source software BountyBench: AI agents solved real-world bug bounty tasks worth tens of thousands of dollars This represents a pivotal shift in cybersecurity — AI agents can now autonomously do what only elite human hackers could before. Check out their work: CyberGym: https://www.cybergym.io/ BountyBench: https://bountybench.github.io/

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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, tasks · Missing: mac, macos, cursor
82%82% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
63%63% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
53%53% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
25%25% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
20%20% predicted probability of success on AppSumo, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
9%9% predicted probability of success on BetaList, based on ML models trained on real launch data.

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