sherlock-project/sherlock
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Find security projects for defensive work and learning. Compare evidence quality, operating limits and maintenance before testing in a lab.
A security tool is useful when it answers a specific question and produces evidence you can interpret. That might mean finding a test credential in a repository, explaining a packet capture or checking a lab application for a documented weakness. Start with the question, then choose a project. This collection supports discovery for defensive work and authorized practice, with the original repository as the source for installation and operation.
Write down the asset, the test boundary and the expected finding. For a secret scanner, create a disposable repository with a deliberately fake credential and a similar-looking harmless string. For log analysis, prepare sample events with known timestamps. Decide what counts as a useful result before trying the tool. A long report is difficult to evaluate without a known input and an expected answer.
Inspect supported platforms, required privileges and the data the project stores or uploads. Identify whether its checks are passive, active or dependent on an external service. Read examples closely enough to understand which system receives each request. Keep early tests inside an environment you own or have permission to assess, using disposable data. The goal is to understand behavior before widening the scope.
Run the same lab input through each candidate. Check whether it identifies the planted finding and how clearly it explains the evidence. Examine false positives and failures, including an unreadable file or malformed input. Note whether output can be exported for review and whether the result gives enough context to reproduce it. OWASP WSTG provides testing guidance you can use to structure web application exercises.
A recently pushed repository may contain documentation changes rather than a new tool release. Stars measure attention, not detection accuracy. Check upstream release notes, issue discussions and the actual licence. The local index includes selected public metadata; it does not scan projects for vulnerabilities or test their claims. A category can be broad, so use a concrete term and follow the repository link for the current details.
1,112 non-archived matches. This preview is sorted by stars, not a recommendation or security assessment.
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Bitcoin Core integration/staging tree
Open-source AI penetration testing tool to find and fix your app’s vulnerabilities.
🔍 A Hex Editor for Reverse Engineers, Programmers and people who value their retinas when working at 3 AM.
Shannon is an AI pentester for web applications and APIs. It analyzes your source code, identifies attack vectors, and executes real exploits to prove vulnerabilities before they reach production.
An extremely fast Python linter and code formatter, written in Rust.
Choose one with clear setup instructions, sample inputs and outputs you can explain. A small log parser or an exercise around a fake secret often gives a clearer learning loop than an all-purpose platform. Success means understanding a finding and its limits, not merely getting the installation to finish.
A repository listing cannot establish coverage of your systems. Use the discovery process to find candidate tools, then validate each one against a defined task. Keep a record of what you tested and what remained outside scope so a tool report does not become an unsupported claim of security.
Editorially reviewed 8 November 2026. Repository summaries come from GitHub; metadata can change between checks. Send a correction.