Claude Skills by superagent-ai

Review application source code for broken authorization — IDOR / Broken Object Level Authorization (OWASP API1), Broken Function Level Authorization (API5), mass assignment (API3), multi-tenant isolation gaps, and privilege escalation. Reads routes, controllers, resolvers, and data models offline and reports the missing ownership/role check at file:line with a framework-correct fix. No running app, no credentials, no tools. Trigger when reviewing endpoints/handlers, auditing a PR diff that ad...

Scan GitHub Actions workflow files for security vulnerabilities by reading the YAML and reporting findings directly — no external tools, no installation, no shell execution. Use this skill whenever the user shares a `.github/workflows/` file, pastes workflow YAML, asks for a CI/CD security review, mentions `pull_request_target`, `workflow_run`, action pinning, `GITHUB_TOKEN` permissions, pwn requests, template injection, cache poisoning, secret exfiltration, supply chain risk, or any GitHub A...

Audit application source code and configuration for cryptography and secrets hygiene issues: hardcoded API keys, committed .env files, private keys, weak hashes, insecure encryption modes, unsafe randomness, bad KDF/password hashing, JWT signing mistakes, disabled TLS verification, and dangerous serialization. Runs a dependency-free offline scanner for high-recall findings, then the model confirms impact and writes concrete fixes with redacted evidence. Use when reviewing app code that handle...

Cursor-native offensive security engagement and exploitability autoresearch orchestrator inspired by offensive-claude. Use for an authorized offensive engagement, red-team or pentest workflow, Kill Chain style assessment, scoped web/network/cloud/mobile/AD/bug-bounty offensive plan, or exploitability validation of defensive findings. In validate-findings mode it runs a bounded, user-controlled autoresearch loop over deduplicated findings: several hypothesis passes / cycles of hypothesize, exp...

Audit Infrastructure-as-Code for security misconfigurations before it ships — Terraform (.tf/.tfvars/.hcl), CloudFormation/SAM (YAML/JSON), Kubernetes & Helm manifests, and Docker / Docker Compose. Reads the IaC offline and reports each misconfiguration at file:line with a severity (P0–P3) and a corrected snippet. A dependency-free scanner does the high-recall first pass; the model adds blast-radius and cross-resource judgment. No cloud credentials, no terraform apply, no pip install. Trigger...

Post Superagent PR security scan findings as inline GitHub pull request review comments using the authenticated gh CLI. Use whenever you need to comment on a PR scan finding, manage Superagent PR labels, complete a GitHub check run, or avoid posting findings as general PR thread comments. Trigger for any Superagent sandbox PR scan handoff that owns GitHub side effects via gh.

Guide authorized external penetration testing from recon through validation and scoped exploitation using free and open-source tools. Use for domain/IP attack surface mapping, subdomain discovery, nmap/httpx/nuclei/ffuf workflows, web app testing, SIP/NAS checks, Burp/ZAP validation, PoC documentation, and pentest reporting without commercial APIs.

Run a bounded red-teaming autoresearch loop to generate LLM guardrail training data. You (the agent running the skill) are the attacker and the judge: you craft attacks and label every response. The only model the harness calls is the target under test, over any OpenAI-compatible API (OpenRouter, Moonshot/Kimi, Fireworks, Ubicloud, OpenAI, or custom), with its key in `.red-team/.env`. Every attempt (pass and fail) is written to JSONL ready for fine-tuning guardrails in Llama Guard format. Use...

Audit a GitHub repository's security posture and hardening gaps across branch protection, CODEOWNERS, GitHub Actions, publish/release integrity, collaborator access, security features, and dependency review. Use when reviewing or hardening a repo, assessing GitHub configuration, checking CI/CD or Actions security, evaluating supply-chain posture, preparing maintainer-facing security todos, or when the user says "repo security posture", "audit my repo", "harden this GitHub repo", "actions secu...

Verify whether an incoming security advisory is a real, disclosable vulnerability in a target repository checkout, and assign an honest severity. Use when triaging an advisory, GHSA, scanner finding, or draft report from the researcher/reporter side to decide if it is worth disclosing. Optimizes against false confirmations and inflated severity.

Audit an AI agent skill for security risks before installing or trusting it. Runs a deterministic scanner (regex patterns, Python AST analysis, source-to-sink taint tracking, and YARA signatures) and then reasons about intent — catching prompt injection, credential exfiltration, persistence, memory poisoning, malicious code, supply-chain risks, and description-vs-behavior mismatch. Make sure to use this skill whenever the user wants to scan, audit, vet, review, or check the safety of a skill,...

Set up Superagent Context Guardrails at coding-agent tool boundaries, configure and safely use the remote MCP server, and manage signed webhooks for findings, security reports, Contributor Trust, and Runtime Guardrails. Use when the user asks to enable context scanning before an agent consumes URLs, files, email, skills, or MCP repositories; integrate coding-agent hooks; or install, connect, configure, troubleshoot, or operate Superagent from Cursor, Claude Code, Codex CLI, or another MCP cli...

Review new or changed dependencies for supply-chain compromise before they enter a project — malicious install scripts (preinstall/postinstall), binding.gyp/node-gyp install-time execution (June 2026 worm), self-propagating worms (Shai-Hulud, binding.gyp), credential harvesting and exfiltration, obfuscated payloads, typosquatting, slopsquatting (AI-hallucinated package names), dependency/namespace confusion, maintainer account takeover, and unpinned or unverified versions. Reads manifests, lo...

Triage inbound vulnerability reports - GitHub Advisories (GHSA/CVE), bug bounty submissions, HackerOne/Bugcrowd/Intigriti exports, or a researcher's issue - to decide whether a finding is real, by-design, or noise. Reads the report offline, cross-references the project's documented intent and threat model (SECURITY.md, README, code, closed issues), statically audits any PoC without executing it, and emits a structured markdown triage report with a P0-P3 / By-Design severity and a recommended ...