Takumi – An AI Security Engineer that found 10 zero-days (Vim, Next.js)

Hacker News

After hundreds of manual pen-tests we wondered: could an LLM-powered agent handle almost all the work of a security engineer? Takumi was the answer: a resounding yes. He is always available on Slack, just like another other colleague: - Leave it to Takumi—no prompt-tweaking needed: he auto-researches, analyzes code, and delivers concise reports - Works 24/7 to discover the logic-level flaws that SAST tools often miss, such as broken access control and auth bypasses - Has already filed real CVEs during private internal tests (Vim and Next.js being two major examples) Takumi is a SaaS product only costing $500/month. If you're an open-source developer, we also provide a program that lets you use it free of charge! Screenshots, docs, and details a free trial can be found here: https://flatt.tech/en/takumi We are eager to receive feedback, so please do not hesitate to share your experience with us! In addition, please feel free to comment if you have any questions whether its about the setup, the security reports, or anything else! Thanks a lot of taking a look!

Visit product View on Hacker NewsMay 19, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: agent, slack, code · Missing: mac, agents, macos

84%84% 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

77%77% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: month, way · Missing: mobile apps, ios, personal

46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

46%46% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

24%24% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: saas · Missing: arr, mrr, revenue

19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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