Krawl is a customizable, lightweight, cloud-native web deception server and anti-crawler that creates fake web applications with low-hanging vulnerabilities using realistic, randomly generated decoy data and AI-generated HTML templates.
This week brought fixes to the banlist workflow permissions system, addressing issues that were preventing the automated process from running correctly. The team also merged a community banlist update, keeping the banned card list current with the latest rulings.
Get this in your inbox every Monday →A deterministic 0–100 hygiene score — README, license, CI, tests, docs, and freshness.
Who ships this repo — author concentration and the bus factor across the last 300 mainline commits.
How welcoming this repo is to contributors — issue throughput, close time, responsiveness, and good-first-issue count.
What this project is built on — dependency count by ecosystem, the license mix, and anything worth a legal look before you adopt it.
Whether this project's CI can be trusted — pass rate, run times, flaky runs, and which workflow is the weak link.
Grounded in Krawl's README, structure, and recent commits — answers won't invent code they haven't seen.
A Monday email with what shipped, in plain English — no account needed.
A floor, not a guess: counts only commits whose author, co-author trailer, or message explicitly credits an AI tool (Claude, Copilot, Cursor, aider, Codex…). Based on 17 mainline commits. Unattributed AI code isn't counted here — the full audit estimates that separately.
