detecting-api-enumeration-attacks
by mukul975detecting-api-enumeration-attacks helps Security Audit teams detect API probing, BOLA, and IDOR by analyzing sequential IDs, 404 bursts, authorization failures, and docs discovery paths. It is built for log-driven detection guidance, rule drafting, and practical review of API abuse patterns.
This skill scores 79/100, which means it is a solid listing candidate for Agent Skills Finder. Users should find it clearly targeted and practical for API enumeration/BOLA/IDOR detection, though they should still expect some implementation-specific tuning and incomplete end-to-end workflow detail.
- Strong triggerability: the frontmatter and overview explicitly frame the skill around detecting API enumeration attacks, BOLA, and IDOR.
- Good operational evidence: the repository includes a runnable Python agent script plus a dedicated API reference with log format, detection techniques, and thresholds.
- Useful install decision value: the skill covers concrete signals like sequential IDs, endpoint fuzzing, rate abuse, and common discovery paths, which gives agents a clearer starting point than a generic prompt.
- Workflow clarity is decent but not fully complete: the excerpts show detection logic and references, but not a clearly documented start-to-finish usage flow or install command in SKILL.md.
- Some guidance looks threshold-based and environment-dependent, so users may need to tune thresholds and patterns for their own logging stack and traffic profile.
Overview of detecting-api-enumeration-attacks skill
What this skill is for
The detecting-api-enumeration-attacks skill helps you spot API probing that looks like BOLA, IDOR, or other resource-enumeration abuse. It is most useful for Security Audit work where you need to turn messy API logs into a defensible detection approach, not just a generic writeup.
Who should install it
Use the detecting-api-enumeration-attacks skill if you are a SOC analyst, appsec engineer, blue teamer, or auditor working with API gateway, reverse proxy, or app logs. It is a good fit when you need pattern-based detection, threat hunting ideas, or rule-building guidance for sequential IDs, endpoint discovery, and authorization-failure signals.
What makes it different
This is not a broad API security checklist. The skill focuses on observable attack behavior: sequential identifier access, high-404 fuzzing, bursty request rates, and probing of common discovery paths like /swagger, /api-docs, and GraphQL introspection. That makes it more actionable than a vague detecting-api-enumeration-attacks prompt when you need detection logic or audit evidence.
How to Use detecting-api-enumeration-attacks skill
Install and inspect the support files
Run the detecting-api-enumeration-attacks install flow for your platform, then review the skill package starting with SKILL.md. In this repo, the most useful companion files are references/api-reference.md for detection patterns and thresholds, and scripts/agent.py for the parsing and matching logic the skill is built around.
Give the skill the right input context
The detecting-api-enumeration-attacks usage pattern works best when you provide:
- log source type: API gateway, WAF, reverse proxy, or app log
- time window: incident range or hunt window
- suspected endpoints:
/api/v1/users,/accounts/{id}, GraphQL, docs paths - known-good behavior: normal request rate, common users, expected status codes
- constraints: SIEM, scripting language, or reporting format
A weak prompt says: “Find API abuse.”
A stronger prompt says: “Using detecting-api-enumeration-attacks, analyze 24 hours of NGINX logs for one IP with rising 404s, sequential /api/v1/users/{id} requests, and authorization failures. Return likely attack patterns, evidence fields, and a detection rule draft.”
Follow a practical workflow
Start by mapping the attack surface, then check for sequential IDs, then look for rate anomalies and endpoint discovery. For Security Audit usage, separate signal types: 200/403/404 mix, path entropy, object-ID progression, and repeated hits to documentation or introspection endpoints. That order helps you avoid false positives from normal retries or noisy clients.
Read these files first
For fastest onboarding, read in this order:
SKILL.mdfor the intended detection scopereferences/api-reference.mdfor thresholds, paths, and WAF rule categoriesscripts/agent.pyfor regexes, log parsing, and threshold assumptions
If you plan to adapt the skill, inspect the patterns and thresholds before changing the wording of your prompt.
detecting-api-enumeration-attacks skill FAQ
Is this only for incident response?
No. The detecting-api-enumeration-attacks skill is useful for incident response, but it is also strong for pre-incident audit work, detection engineering, and validation of API monitoring coverage.
Do I need a SIEM to use it well?
No, but the skill becomes more useful when you have structured logs. It can still help with raw access logs, gateway exports, or small sample files if you want a first-pass hunt.
How is this different from a generic prompt?
A generic prompt may explain BOLA or IDOR in theory. The detecting-api-enumeration-attacks skill is better when you need concrete indicators, candidate queries, and a workflow that starts from logs and ends with detection-ready output.
Is it beginner friendly?
Yes, if you can supply logs and basic context. It is less suitable if you only want a high-level overview of API security with no data to analyze.
How to Improve detecting-api-enumeration-attacks skill
Provide cleaner evidence up front
The quality of detecting-api-enumeration-attacks output depends on the evidence you attach. Include raw log samples, timestamp range, response codes, and any known account or resource IDs. If possible, note whether identifiers are numeric, UUID-based, or mixed, because that changes how enumeration is detected.
Ask for one outcome at a time
The best detecting-api-enumeration-attacks guide outputs are narrower than “find everything suspicious.” Ask for a hunt summary, a detection rule draft, or a false-positive review first. Then iterate into remediation notes or reporting language after the pattern is validated.
Watch for common failure modes
The main risk is overcalling normal client behavior as enumeration. Burst traffic from mobile apps, load tests, pagination, retries, and crawler-like monitoring can look similar. Improve results by telling the skill which traffic is expected, which endpoints are public, and which status codes are acceptable.
Iterate with thresholds and examples
If the first result is too broad, refine the prompt with thresholds from references/api-reference.md or your own environment. For example, ask it to focus on “more than 50 requests per minute from one IP” or “10+ sequential IDs within one session.” For detecting-api-enumeration-attacks for Security Audit, that tighter framing usually produces evidence you can actually defend.