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Warden – AI application security reviews
Hacker NewsWarden – AI application security reviews
Hey HN, I built an AI security review tool called Warden for automating application security reviews. I built it because I worked at security organizations where this process took hours, and Warden makes it take minutes. It’s free right now to try, please give it a try and let me know if you have any feedback. Please share with your security friends! Here's a demo video: https://www.youtube.com/watch?v=Hfom0noLFq0 - Alp
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4points
Did not reach leaderboard
Launch Intel predictions
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AppSumoStrong fit for a featured deal · Strong signals: reviews · Missing: plus, platform, intuitive68%68% predicted probability of success on AppSumo, 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 · Strong signals: organizations · Missing: supports, reddit linkedin, podcasting63%63% predicted probability of success on Indie Hackers, 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 released46%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.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos43%43% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: video · Missing: mobile apps, ios, personal23%23% 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, revenue17%17% 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, crypto1%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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