Web Security Scanner - Can Your Site Score a 100%?

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http://webscanner.tk/quickscan/ Hi! I made this project over the couse of a week to help teach myself more about Django and web app development. I am studying computer security in school and web security is one of my passions. It is a tool that helps web developers ensure that they have implemented helpful security mechanisms like HTTPOnly flags, X-Frame-Options, etc. There are hundreds of tools that offer to scan websites for things like cross-site scripting, mySQL injection, etc. This tool simply looks for information that is available via one or two GET requests (the headers, protocols, body, etc.). It does NOT attempt to fuzz or otherwise target the site (test parameters or try XSS payloads). I did this because I wanted to lower the barrier of entry. Other tools require you to upload a file to your site, add some code or prove ownership. Since this site isn't exploiting anything, none of that is necessary. It's super simple to use and is aimed towards non-security people who still want to develop secure web applications.<p>This is a quick project! There's probably a lot of errors or things that behave weirdly (I once got a score of 110% but couldn't replicate it). If you want to check out the code, here it is, free and open-source: https://github.com/matthewdfuller/Web-Security-GUI Feel free to leave feedback! I'm not looking to make any money (just learn!), so this is free and there are no ads.

Visit product View on Hacker NewsApr 20, 2013

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

73%73% 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.

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

62%62% 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: io · Missing: https docs, excited, just released

48%48% 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

38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

30%30% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

12%12% 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.

Incorrect prediction on native model

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