Api Security

Organization

transilienceai

api-security

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

Overview

Publisher	transilienceai
Repository	`communitytools`
Skill name	`api-security`
Stars	565
Forks	81
Bundled files	42
License	MIT
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
42 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by transilienceai on GitHub. Read the source before you install it.

Installation

Install the Api Security AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/transilienceai/communitytools/tree/main/skills/api-security
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/transilienceai/communitytools.git /tmp/communitytools
mkdir -p .claude/skills
cp -r /tmp/communitytools/skills/api-security .claude/skills/api-security

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Api Security in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Api Security on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Api Security is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

API Security

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

Techniques

Type	Key Vectors
GraphQL	Introspection, batching attacks, nested query DoS, field suggestion
REST API	BOLA/IDOR, mass assignment, rate limiting, auth bypass, versioning
WebSocket	Cross-site hijacking, message manipulation, auth flaws
Web-LLM	Prompt injection via API, excessive agency, data exfiltration

Workflow

Discover API endpoints and documentation (Swagger, GraphQL schema)
Map authentication and authorization mechanisms
Test per API type using appropriate techniques
Validate data exposure and access control flaws
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:

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.
Acquire per-role sessions: via authenticated-session-acquisition (MFA/OTP/SRP → reusable tokens) into the harness's token store.
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.
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)
- scenarios/rest/odata-deep-authz.md - OData $metadata enum + $filter/$orderby/$expand cross-tenant BOLA & injection
- scenarios/rest/cognito-unauth-and-srp.md - Cognito UNSIGNED unauthenticated posture (self-signup/enumeration) + SRP authenticated session
reference/websockets*.md - WebSocket vulnerability testing
- scenarios/websocket/authenticated-per-role-authz.md - authenticated per-role relay: BOLA/BFLA/channel-authz over the socket
reference/web-llm*.md - Web-LLM attack techniques and labs

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Api Security AI skill do?

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

Why use Api Security on TypingMind?

Because you install it once and use it with any model. Api Security is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Api Security in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/transilienceai/communitytools/tree/main/skills/api-security. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Api Security?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Api Security?

As many as you like. As long as a model supports skills, you can use Api Security with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Api Security AI skill free?

Yes. It is published on GitHub by transilienceai under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

API Security

Techniques

Workflow

API at scale (offline corpus / fixture-driven)

Reference

Bundled files

Frequently asked questions

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