github-actions-hardening
Skill153 starsChanged 44 days agoAGPL-3.0View on GitHub
Security hardening reviewer for GitHub Actions workflow files (.github/workflows/*.yml). Reasons about the Actions threat model that pattern matchers and general code linters miss — untrusted-input script injection, privileged triggers running fork code, mutable action references, and over-scoped tokens. Use this skill when asked to review, audit, harden, or secure a GitHub Actions workflow, when writing a new workflow, or for any request like "is this workflow safe?", "review my CI for security issues", "why is pull_request_target dangerous here?", "pin my actions", or "lock down GITHUB_TOKEN permissions". Covers script injection via ${{ }} interpolation, pull_request_target / workflow_run privilege escalation, SHA-pinning of third-party actions, least-privilege permissions, GITHUB_ENV/GITHUB_OUTPUT injection, secret exposure, OIDC over long-lived credentials, and self-hosted runner exposure on public repositories.
- Reads credentials
7 other projects use a version of this, 5 of them edited.
Adopted by
Most recently taken up by
- taixuann/development-spaceedited, first seen Nov 8, 2026
- docdyhr/simplenote-mcp-serveredited, first seen Nov 1, 2026
- kaandgnsh/Claude-Bluetheir own version, first seen Nov 1, 2026
- github/awesome-copilotedited, first seen Oct 25, 2026
- sb-dev/narrative-production-skillsedited, first seen Oct 20, 2026
- z-Zihan/Evirtheir own version, first seen Oct 13, 2026
Other versions7 projects use a version of this.
Word for word · 0
None found.
Edited · 5
- github/awesome-copilot★ 41k99% same
- docdyhr/simplenote-mcp-server★ 2199% same
- sb-dev/narrative-production-skills★ 299% same
- taixuann/development-space★ 199% same
- RorroRojas3/maf-agents★ 097% same
Wrote their own version · 2
- z-Zihan/Evir★ 11same name
- kaandgnsh/Claude-Blue★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository44 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- .github/copilot-instructions.mdCopilot instructions
- llms-full.txtllms.txt
- llms.txtllms.txt
- api-v1Skill
- asset-storageSkill
- backend-routeSkill
- backend-serviceSkill
- bun-runtimeSkill
- changelogSkill
- database-migrationSkill
- e2e-testSkill
- embedding-staticSkill
- exporterSkill
- frontend-moduleSkill
- i18nSkill
- ideviceSkill
- kysely-queriesSkill
- mkdocs-navSkill
- playwright-cliSkill
- verify-changeSkill
- websocket-yjsSkill
- xlf-translateSkill
- api-v1Skill
- asset-storageSkill
- backend-routeSkill
- backend-serviceSkill
- bun-runtimeSkill
- changelogSkill
- database-migrationSkill
- e2e-testSkill
- embedding-staticSkill
- exporterSkill
- frontend-moduleSkill
- github-actions-hardeningSkill
- i18nSkill
- ideviceSkill
- kysely-queriesSkill
- mkdocs-navSkill
- playwright-cliSkill
- verify-changeSkill
- websocket-yjsSkill
- xlf-translateSkill
The file
We split this skill into the rules it gives an agent
12 rules. 3 are common, 0 are distinctive, and 9 are very specific to this project.
3
Common
Most of the 7 edited versions we read keep these.
0
Distinctive
This author's own choices. Worth a look.
9
Very specific
Tied to their project's names, files or tools. Probably skip.
Licensed with conditions — read it at the source. We count its rules but don't quote them. Read them on GitHub.
“Common” is measured: kept by at least 6 in 10 of the 7 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

