V1.0.0 Release DuffMan – Fuzzer for Postman Collection

Hacker News

The tool allows to parse and fuzz all API Endpoints defined within a Postman Collections. It is created to help Security and Software Engineers to test and catch not properly handled errors. First Stable release: ## Features - Parse collection and environment files - Fuzz GET parameters - Fuzz form parameters - Fuzz multipart parameters - Fuzz path parameters - Fuzz JSON bodies - Filter output by response status code - Filter output by response time ## Improvements - Enhanced JSON body parsing ## Fixes - Fixed a bug with custom variables

Visit product View on Hacker NewsJul 23, 2024

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

57%57% 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.

Indie HackersIH features products with proven revenue · Strong signals: created, para · Missing: supports, reddit linkedin, podcasting

46%46% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

33%33% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

32%32% predicted probability of success on AppSumo, 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

31%31% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

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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