Generate pentesting reports from pentest screen recordings

Hacker News

Onelook is an open-source, self-hosted project that generates pentesting reports based on screen recordings of pentesting sessions. To be clear, it does not upload the video to a LLM service. The video is processed with OCR and the texts are sent to the LLM service when 1) generating contexts for the video and 2) generating reports. You can choose which LLM provider (self-hosted ones too) to connect to. Hope it is useful to anyone and possibly find more use cases for it. Thank you!

Visit product View on Hacker NewsJul 19, 2024

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Product HuntOn track for Day 1 leaderboard · Strong signals: context, recordings, open · Missing: mac, agents, macos

87%87% 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.

TrustMRRFits verified-revenue profile · Strong signals: video · Missing: mobile apps, ios, personal

60%60% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

50%50% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

47%47% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

22%22% 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

13%13% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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