Java Security Testing Startup

Hacker News

We are a startup company building out a new passive security testing technology specifically designed for DevSecOps (fast turnaround, accurate results, easy CI/CD integration, etc.). We are currently targeting Java but are looking to build out support for several other languages. A free version of the tool is accessible at https://www.adversalabs.com/install.html which will allow you to test for SQLi, XSS and XXE. To everyone who writes or maintains Java code, we'd love your feedback. Does it provide a good UX? Do you find the results valuable? We're happy to provide you with a free "Professional" license, providing access to full suite of security tests, if interested. Your feedback is much appreciated. Thank you!

Visit product View on Hacker NewsJun 26, 2018

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3points

Did not reach leaderboard

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84%84% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: new, code · Missing: mac, agents, macos

40%40% 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: lua, ide, io · Missing: https docs, excited, just released

32%32% 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

29%29% 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

13%13% 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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