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-bug-identificationWrote 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-bug-identification)<a href="https://agentmods.dev/skills/snailsploit/claude-red/offensive-bug-identification"><img src="https://agentmods.dev/badge/skills/snailsploit/claude-red/offensive-bug-identification/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-bug-identification"><img src="https://agentmods.dev/badge/skills/snailsploit/claude-red/offensive-bug-identification.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 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 200 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 Tool Misuse · line 691 Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
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 | $0.00000 | $0.13479 |
| Opus 5.5 | $0.00000 | $0.05392 |
| Sonnet 5.5 | $0.00000 | $0.02696 |
| Haiku 4.5 | $0.00000 | $0.01348 |
Grade C, and why
offensive-bug-identification scanned grade C 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 endpointhighServer-side request forgery
One request to 169.254.169.254 can return temporary IAM credentials.
- SSRF paths into metadata services (`169.254.169.254`, IMDSv2 bypass techniques) Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
wget -Uri https://www.catalog.update.microsoft.com/Download.aspx?q=KB5037778 -OutFile kb.msu How it starts
The opening of the file, as written. The whole thing — 1,255 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SKILL: Bug Identification
Metadata
- Skill Name: bug-identification
- Folder: offensive-bug-identification
- Source: https://github.com/SnailSploit/offensive-checklist/blob/main/bug-identification.md
Description
Systematic bug identification methodology: source code review patterns, black-box testing strategies, taint analysis, dangerous function hunting, data flow tracing, and automated scanning setup. Use for code audits, bug bounty triage, or building vulnerability identification pipelines.
Trigger Phrases
Use this skill when the conversation involves any of:
bug identification, code review, taint analysis, dangerous functions, data flow, source audit, black box, vulnerability identification, static analysis, code audit, bug hunting
Instructions for Claude
When this skill is active:
- Load and apply the full methodology below as your operational checklist
- Follow steps in order unless the user specifies otherwise
- For each technique, consider applicability to the current target/context
- Track which checklist items have been completed
- Suggest next steps based on findings
Full Methodology
Bug Identification
Overview
Bug identification is the process of discovering potential vulnerabilities in software through various techniques including static analysis, dynamic analysis, and fuzzing. This document outlines methodologies and tools for effective vulnerability research.
For practical exploit development, see Exploit Development.
flowchart TD
BugId["Bug Identification"]
%% Main Methods
Static["Static Analysis"]
Dynamic["Dynamic Analysis"]
Fuzzing["Fuzzing"]
AI["AI-Assisted"]
%% Static Analysis Methods
CodeReview["Manual Code Review"]
RevEng["Reverse Engineering"]
PatchDiff["Patch Diffing"]
StaticTools["Static Analysis Tools"]
SBOM["Supply Chain Analysis"]
%% Dynamic Analysis Methods
DebugTrace["Debugging/Tracing"]
DBI["Dynamic Binary Instrumentation"]
Taint["Taint Analysis"]
SymExec["Symbolic Execution"]
Snapshot["Snapshot Analysis"]
%% Fuzzing Methods
DumbFuzz["Dumb Fuzzing"]
SmartFuzz["Smart Fuzzing"]
EvoFuzz["Evolutionary Fuzzing"]
LLMFuzz["LLM-Guided Fuzzing"]
%% AI Methods
LLMTriage["LLM Crash Triage"]
MLPattern["ML Pattern Recognition"]
AutoVariant["Automated Variant Analysis"]
%% Connections
BugId --> Static
BugId --> Dynamic
BugId --> Fuzzing
BugId --> AI
Static --> CodeReview
Static --> RevEng
Static --> PatchDiff
Static --> StaticTools
Static --> SBOM
Dynamic --> DebugTrace
Dynamic --> DBI
Dynamic --> Taint
Dynamic --> SymExec
Dynamic --> Snapshot
Fuzzing --> DumbFuzz
Fuzzing --> SmartFuzz
Fuzzing --> EvoFuzz
Fuzzing --> LLMFuzz
AI --> LLMTriage
AI --> MLPattern
AI --> AutoVariant
%% Combinations
Taint -.-> Fuzzing
SymExec -.-> Fuzzing
RevEng -.-> Fuzzing
AI -.-> Fuzzing
AI -.-> Static
class BugId primary
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 · 1,255 lines · 0 tokens per session scan C b80715679fc4
offensive-bug-identification is a skill published in the GitHub repository SnailSploit/Claude-Red (7,604 stars, last pushed 7d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 13,479 tokens. A static security scan graded it C 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.
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