Borrowing it
Nothing to install: this file belongs to Krishcalin/Agentic-AI-Cyber-Security. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Krishcalin/Agentic-AI-Cyber-Security/main/CLAUDE.mdgit clone --depth 1 https://github.com/Krishcalin/Agentic-AI-Cyber-SecurityWrote 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/instructions/krishcalin/agentic-ai-cyber-security/claude-md)<a href="https://agentmods.dev/instructions/krishcalin/agentic-ai-cyber-security/claude-md"><img src="https://agentmods.dev/badge/instructions/krishcalin/agentic-ai-cyber-security/claude-md.svg" alt="Measured on agentmods" 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 | $0.06452 | $0.06452 |
| Opus 5 | $0.03226 | $0.03226 |
| Sonnet 5 | $0.01290 | $0.01290 |
| Haiku 4.5 | $0.00645 | $0.00645 |
Grade B, and why
Agentic-AI-Cyber-Security CLAUDE.md scanned grade B with 3 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 7d 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.
Instruction-override phrasingmediumPrompt injection
Text telling the model to disregard its earlier instructions or safety rules is the shape of a prompt injection, whoever wrote it.
python main.py scan-prompt --text "Ignore previous instructions and..." 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.
- [x] Dockerfile rules (16) — :latest, root, secrets, curl|bash Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
- Sinks: `os.system()`, `subprocess.run()`, `cursor.execute()`, `eval()` How it starts
The opening of the file, as written. The whole thing — 519 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md — Agentic AI Cyber Security
Project Overview
An open-source Python-based source code security analyzer that identifies security flaws, flags fictitious or non-existent dependencies, prevents prompt injection attacks, and delivers AI-driven semantic code analysis — accessible through MCP integrations with Claude Code or command-line interfaces and CI/CD pipelines.
Repository: https://github.com/Krishcalin/Agentic-AI-Cyber-Security License: MIT Python: 3.10+ Status: All phases + P1/P2/P3 complete — MITRE ATLAS + OWASP LLM Top 10 mapped Rules: 441 across 19 languages | Engines: 24 | MCP Tools: 30 | CLI Commands: 25+ Inspired by: sinewaveai/agent-security-scanner-mcp
Architecture
Directory Structure
Agentic-AI-Cyber-Security/
├── config/ # Configuration files
│ ├── settings.yaml # Global scanner settings
│ └── profiles/ # Scan profiles (quick, full, ci)
│ ├── quick.yaml
│ ├── full.yaml
│ └── ci.yaml
├── core/ # Core engine components
│ ├── __init__.py
│ ├── engine.py # Main scanner orchestrator
│ ├── ast_analyzer.py # AST-based vulnerability detection (Python)
│ ├── pattern_matcher.py # Regex/pattern-based scanning (multi-lang)
│ ├── taint_tracker.py # Cross-function taint flow analysis
│ ├── package_checker.py # Dependency verification (PyPI, npm, crates)
│ ├── prompt_scanner.py # Prompt injection detection engine
│ ├── semantic_reviewer.py # LLM-powered code review (Claude API)
│ ├── fix_generator.py # Auto-fix template engine
│ ├── mcp_auditor.py # MCP server security auditor (Tier 1)
│ ├── rag_scanner.py # RAG pipeline security scanner (Tier 1)
│ ├── tool_response_analyzer.py # Tool response injection analyzer (Tier 1)
│ ├── chain_detector.py # Multi-step exploit chain detector (Tier 2)
│ ├── policy_engine.py # Declarative YAML policy engine (Tier 2)
│ ├── runtime_monitor.py # Real-time session anomaly detection (Tier 2)
│ ├── redteam_generator.py # Adversarial test suite generator (Tier 2)
│ ├── dependency_analyzer.py # Supply chain dependency analyzer (Tier 2)
│ ├── reporter.py # Report generation (terminal, JSON, SARIF, HTML)
│ ├── grader.py # A–F security grading system
│ ├── models.py # Data models (Finding, ScanResult, Severity)
│ └── logger.py # Structured logging
├── rules/ # YAML security rules (organized by language)
│ ├── python.yaml # Python-specific rules
│ ├── javascript.yaml # JavaScript/TypeScript rules
│ ├── java.yaml # Java rules
│ ├── go.yaml # Go rules
│ ├── php.yaml # PHP rules
│ ├── ruby.yaml # Ruby rules
│ ├── c_cpp.yaml # C/C++ rules
│ ├── dockerfile.yaml # Dockerfile rules
│ ├── terraform.yaml # Terraform/IaC rules
│ ├── kubernetes.yaml # Kubernetes manifest rules
│ ├── typescript.yaml # TypeScript rules (34) — Tier 2
│ ├── shell.yaml # Shell/Bash rules (30) — Tier 2
│ ├── rust.yaml # Rust rules (30) — Tier 2
│ ├── swift.yaml # Swift/iOS rules (30) — Tier 2
│ ├── kotlin.yaml # Kotlin/Android rules (30) — Tier 2
│ ├── prompt_injection.yaml # Prompt injection patterns
│ └── common.yaml # Cross-language rules (secrets, hardcoded creds)
├── mcp_server/ # MCP (Model Context Protocol) server
│ ├── __init__.py
│ ├── server.py # MCP server entry point (stdio transport)
│ ├── tools.py # MCP tool definitions and handlers
│ └── schemas.py # Input/output JSON schemas for tools
├── cli/ # CLI interface
│ ├── __init__.py
│ └── main.py # Click-based CLI entry point
├── integrations/ # CI/CD and editor integrations
│ ├── github_actions.py # GitHub Actions reporter
│ ├── gitlab_ci.py # GitLab CI integration
│ └── sarif_exporter.py # SARIF 2.1.0 export for Code Scanning
├── data/ # Static data files
│ ├── pypi_packages.bloom # Bloom filter — PyPI package names
│ ├── npm_packages.bloom # Bloom filter — npm package names
│ ├── crates_packages.bloom # Bloom filter — crates.io package names
│ └── known_malicious.yaml # Known malicious package list
├── templates/ # Report templates
│ ├── report.html # HTML report template (Jinja2)
│ └── fix_templates/ # Auto-fix templates by CWE
│ ├── cwe_78.py # OS Command Injection fixes
│ ├── cwe_89.py # SQL Injection fixes
│ ├── cwe_79.py # XSS fixes
│ ├── cwe_798.py # Hardcoded Credentials fixes
│ └── ...
├── tests/ # pytest test suite
│ ├── conftest.py
│ ├── test_engine.py
│ ├── test_ast_analyzer.py
│ ├── test_pattern_matcher.py
│ ├── test_taint_tracker.py
│ ├── test_package_checker.py
│ ├── test_prompt_scanner.py
│ ├── test_semantic_reviewer.py
│ ├── test_fix_generator.py
│ ├── test_grader.py
│ ├── test_mcp_server.py
│ ├── test_rules/ # Rule validation tests
│ └── fixtures/ # Vulnerable code samples per language
│ ├── python_vulnerable.py
│ ├── javascript_vulnerable.js
│ └── ...
├── benchmarks/ # Performance and accuracy benchmarks
│ ├── accuracy_test.py # Precision/recall against known CVEs
│ └── results.md # Benchmark results
├── main.py # CLI entry point
├── pyproject.toml # Project metadata + dependencies
├── requirements.txt # Pinned dependencies
├── CLAUDE.md # This file
└── README.md
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.
- 7d ago First seen · 519 lines · 6,452 tokens per session scan B c2ee471e7b46
Agentic-AI-Cyber-Security CLAUDE.md is an instructions file published in the GitHub repository Krishcalin/Agentic-AI-Cyber-Security (1 stars, last pushed 5mo ago), licensed MIT. It adds 6,452 tokens to every session, about $0.0323 per session on Opus 5. A static security scan graded it B with 3 findings (instruction-override phrasing, makes network calls, runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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