Harden-Runner is a CI/CD security agent that works like an EDR for GitHub Actions runners. It monitors network egress, file integrity, and process activity on those runners, detecting threats in real-time.
Skill 디렉토리
AI Agent를 위한 재사용 가능한 Skill을 찾으세요.
모든 추천은 리포지토리, 감사, 설치 경로와 명확하게 연결됩니다.
검색 결과: harden
영문 디렉토리Conveniently and reasonably harden NixOS.
SlimBrave Neo — Debloat and harden Brave Browser on Linux and Windows. Python curses TUI + CLI. Zero dependencies.
Enhance the security and privacy of your Windows 10 and Windows 11 deployments with our fully optimized, hardened, and debloated script. Adhere to industry best practices and Department of Defense STIG/SRG requirements for optimal performance and security.
A collection of 24 installable agent skills for coding agents covering UI audits, typography, docs, PR review, and releases, with clear installation via npx.
Collection of reusable AI agent skills for code review, planning, research, and automation tasks.
Harden GitLab CI/CD pipelines for supply-chain security — SHA-pin `include:` and CI/CD components, scope the `CI_JOB_TOKEN` allowlist, protect and mask variables, pin job image digests, and use `id_tokens`/OIDC instead of long-lived secrets. Use when adding or auditing a `.gitlab-ci.yml`, before making a GitLab project public, when a supply-chain review flags CI gaps, or when standardizing pipeline hardening across GitLab projects (gitlab.com or self-hosted). GitLab-specific by design — for GitHub Actions use `harden-github-actions`; Forgejo/Gitea Actions are out of scope.
Harden GitHub Actions CI/CD workflows for supply-chain security — SHA-pin actions, least-privilege token permissions, verified toolchain installs, OpenSSF Scorecard, and SLSA provenance. Use when adding or auditing GitHub Actions workflows, before making a repository public, when a supply-chain review flags CI gaps, or when standardizing CI hardening across GitHub projects. GitHub-specific by design — GitLab CI and Forgejo Actions are out of scope.
Bootstrap a new project at a chosen graduation tier (t0 minimum, t1 decision-tracked, t2 full pattern language) following AI-Assisted Project Orchestration best practices. Use when starting a new software project, promoting an existing project to a higher tier, or converting an existing project for AI-assisted development.