Osquery Powered Endpoint Security Analytics Platform

Hacker News

We have launched an endpoint security analytics product (https://sttor.com) powered by facebook's osquery agent. It is very easy to use and made with love for CTO/DevSecOps/DevOps. It will help to secure your Linux servers and employee machines (mac and windows). Our main motive is to simplify cybersecurity for organizations. Features ============== 1. Downloadable Vulnerable deb, rpm, chocolatey, msi, brew packages with CVE and fixes. 2. Rootkit, osx attacks, windows attacks detection in real-time. 3. Compliance Alert for Windows and macOS machines. 4. Intrusion, Malware, APT Detection 5. Incident Response Dashboard. 6. Real-time threat detection. 7. Live Query with fleet visibility 8. File Integrity Monitoring 9. Windows Registry Monitoring. You will get an instant report for any incidents detected. Daily endpoint security assessment report will get generated per organization. Pricing is equivalent to a cup of a coffee. Want to get a demo.? Plz ping me on twitter @raushan_rajj I will share credentials instantly.

Visit product View on Hacker NewsFeb 5, 2019

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Indie HackersFits the IH revenue-focused audience · Strong signals: organizations · Missing: supports, reddit linkedin, podcasting

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

61%61% predicted probability of success on Product Hunt, 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

42%42% 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 · Strong signals: platform · Missing: plus, intuitive, reviews

28%28% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

25%25% 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

16%16% 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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