Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/akashrpatil/awesome-offensive-security-skillsnpx agentmods add skills/akashrpatil/awesome-offensive-security-skills/api-enumeration-fuzzing-discoveryWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/akashrpatil/awesome-offensive-security-skills/api-enumeration-fuzzing-discovery)<a href="https://agentmods.dev/skills/akashrpatil/awesome-offensive-security-skills/api-enumeration-fuzzing-discovery"><img src="https://agentmods.dev/badge/skills/akashrpatil/awesome-offensive-security-skills/api-enumeration-fuzzing-discovery/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/akashrpatil/awesome-offensive-security-skills/api-enumeration-fuzzing-discovery"><img src="https://agentmods.dev/badge/skills/akashrpatil/awesome-offensive-security-skills/api-enumeration-fuzzing-discovery.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00057 | $0.02175 |
| Opus 5 | $0.00028 | $0.01087 |
| Sonnet 5 | $0.00011 | $0.00435 |
| Haiku 4.5 | $0.00006 | $0.00217 |
Grade A, and why
api-enumeration-fuzzing-discovery scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
cat subdomains.txt | waybackurls | grep "\.js" | xargs -n1 curl -s | grep -oE "api\/[a-zA-Z0-9\/_-]+" This is a copy
100% identical to api-enumeration-fuzzing-discovery — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 185 lines — stays where its author put it; the contents beside it link to each section on GitHub.
API Enumeration & Discovery
When to Use
- When initiating a web application pentest or bug bounty. You must find the APIs powering the frontend React/Vue apps.
- When searching for "Shadow APIs" (old
v1/endpoints developers forgot to turn off). - When seeking undocumented parameters (e.g., hidden
?admin=truequeries) on known endpoints. - When trying to locate API documentation exposed accidentally (Swagger/OpenAPI).
Prerequisites
- Authorized scope and target URLs from bug bounty program
- Burp Suite Professional (or Community) configured with browser proxy
- Familiarity with OWASP Top 10 and common web vulnerability classes
- SecLists wordlists for fuzzing and enumeration
Workflow
Phase 1: Passive Reconnaissance (API Spying)
# Concept: Watch the application talk to itself. Modern Single Page Applications (SPAs)
# constantly make XHR/AJAX requests to internal APIs.
# 1. Burp Suite Proxy History
# Browse the target site normally for 5 minutes. Filter Burp history for `/api/`.
# Document paths like: `api.target.com/v2/users/123/profile`
# 2. JavaScript Source Analysis (Crucial)
# Search the frontend webpack bundles for hidden API routes.
# Tool: x8 (or manually using Burp mapping)
cat subdomains.txt | waybackurls | grep "\.js" | xargs -n1 curl -s | grep -oE "api\/[a-zA-Z0-9\/_-]+"
Phase 2: Active Endpoint Brute-Forcing (Fuzzing)
# Concept: Guess standard, unlinked API endpoints utilizing massive wordlists.
# 1. Brute-force directories with FFUF (using seclists/Discovery/Web-Content/api)
ffuf -w Web-Content/api/api-endpoints.txt -u https://api.target.com/v1/FUZZ -mc 200,401,403
# 2. Advanced Kiterunner Exploitation
# Kiterunner is purpose-built for API discovery, using datasets of actual Swagger routes instead of generic words.
kr scan https://api.target.com -w routes-large.kite
# 3. Find Version Downgrades (Shadow APIs)
# If `/v3/users` is secure, check `/v1/users` or `/v2/users`. Older APIs often lack modern authentication.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 185 lines · 57 tokens per session scan A dc7a36880d7e
api-enumeration-fuzzing-discovery is a skill published in the GitHub repository akashrpatil/awesome-offensive-security-skills (4 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 57 tokens to every session and 2,175 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 100% identical to api-enumeration-fuzzing-discovery, differing in 0 lines, and is treated as a copy.
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