claude-red is a library of structured skills that give Claude specialized offensive-security methods for areas such as web vulnerabilities, shellcode, exploit development, and identity systems. It is intended for authorized red-team work, bug-bounty triage, security research, CTF preparation, and operator training. Its catalogue contains the project's skills for loading these security specializations into Claude.
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/SnailSploit/Claude-Rednpx agentmods add skills/snailsploit/claude-red/offensive-api-abuseWrote 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/snailsploit/claude-red/offensive-api-abuse)<a href="https://agentmods.dev/skills/snailsploit/claude-red/offensive-api-abuse"><img src="https://agentmods.dev/badge/skills/snailsploit/claude-red/offensive-api-abuse/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/snailsploit/claude-red/offensive-api-abuse"><img src="https://agentmods.dev/badge/skills/snailsploit/claude-red/offensive-api-abuse.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 14 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Server-Side Request Forgery · line 215 Code accesses a cloud instance metadata endpoint (e.g. 169.254.169.254). A single request can return temporary IAM credentials, making this a high-value SSRF target for credential theft.Fix: Remove access to cloud metadata endpoints unless strictly required. If metadata is needed, restrict it (e.g. IMDSv2 with hop limit) and never expose returned credentials.
- high Memory Poisoning · line 233 Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
- medium Data Exfiltration · line 34 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 39 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 45 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 198 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 221 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 53 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 101 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 127 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 143 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 276 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 371 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 426 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00184 | $0.05750 |
| Opus 5.5 | $0.00074 | $0.02300 |
| Sonnet 5.5 | $0.00037 | $0.01150 |
| Haiku 4.5 | $0.00018 | $0.00575 |
Grade B, and why
offensive-api-abuse scanned grade B with 2 findings 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 1mo 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.
Cloud metadata endpointmediumServer-side request forgery
One request to 169.254.169.254 can return temporary IAM credentials.
"http://169.254.169.254/latest/meta-data/" Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s -X POST -H "Authorization: Bearer $TOKEN" \ How it starts
The opening of the file, as written. The whole thing — 500 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Offensive API Abuse and Advanced Exploitation
You are conducting authorized security assessments targeting the business logic layer of API-driven applications. Traditional vulnerability scanners miss the attack patterns in this skill because they require understanding of application workflows, state transitions, and trust relationships between API endpoints. Your goal is to identify vulnerabilities that allow financial manipulation, data exfiltration through legitimate channels, privilege escalation via workflow abuse, and service disruption through logic-layer attacks.
Quick Workflow
- Map the complete API surface including undocumented endpoints using Arjun, ParamSpider, and manual discovery.
- Model the business workflows: identify multi-step transactions, state machines, and trust chains between endpoints.
- Test each workflow for race conditions using parallel request techniques.
- Extract and analyze JWTs for algorithm confusion, weak signing, and claim injection opportunities.
- If GraphQL is present, test batching for brute-force amplification, query depth for DoS, and introspection for schema leakage.
- Probe pagination for data enumeration and exfiltration opportunities.
- Test webhook configurations for SSRF and callback hijacking.
- Search for API key leakage in client code, error responses, and public repositories.
- Verify all discovered endpoints for authorization consistency.
- Document business impact for each finding with financial or operational consequence estimates.
Business Logic Bypass via API Chaining
Business logic vulnerabilities emerge when individual API endpoints are secure in isolation but the workflow connecting them has exploitable gaps. You identify these by mapping the intended transaction flow and then deviating from it.
# E-commerce checkout bypass
# Normal flow: add_to_cart -> apply_coupon -> calculate_total -> pay -> confirm
# Attack: skip payment and go directly to confirm
curl -s -X POST -H "Authorization: Bearer $TOKEN" \
-H "Content-Type: application/json" \
-d '{"product_id": "PROD-001", "quantity": 1}' \
"https://target.example.com/api/v1/cart/items" | jq .
curl -s -X POST -H "Authorization: Bearer $TOKEN" \
-H "Content-Type: application/json" \
-d '{"coupon_code": "SAVE20"}' \
"https://target.example.com/api/v1/cart/coupon" | jq .
# Skip payment -- attempt direct order confirmation
curl -s -X POST -H "Authorization: Bearer $TOKEN" \
-H "Content-Type: application/json" \
-d '{"cart_id": "CART-12345"}' \
"https://target.example.com/api/v1/orders/confirm" | jq .
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.
- 1mo ago First seen · 500 lines · 184 tokens per session scan B 42cd1e419aea
offensive-api-abuse is a skill published in the GitHub repository SnailSploit/Claude-Red (7,620 stars, last pushed 7d ago), licensed MIT. It adds 184 tokens to every session and 5,750 once invoked, about $0.0007 per session on Opus 5.5. A static security scan graded it B with 2 findings (cloud metadata endpoint, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
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agent-ready-api-catalog
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agent-ready-link-headers
Sub-skill de agent-ready-cloudflare: Implement Link Response Headers.
agent-ready-mcp-server-card
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