Red Specter Arsenal
Offensive AI Security Framework — 14 tools for authorised penetration testing of AI agents, MCP servers, RAG pipelines, and autonomous systems.
Overview
Red Specter Arsenal is a unified offensive AI security framework. Every existing AI security testing tool — Garak, PyRIT, Promptfoo — tests LLMs. Arsenal tests AI agents. An LLM responds to prompts. An AI agent has memory, tools, credentials, and the ability to act autonomously. That is a completely different attack surface.
Arsenal provides 14 tools under a single CLI (arsenal),
784 attack payloads, and a full pipeline from scanning through attack path mapping
to Ed25519-signed evidence reports.
The 14 Tools
| # | Tool | Command | What It Does |
|---|---|---|---|
| 01 | Phantom Swarm | arsenal swarm scan | 5 attack agents, 19 vectors — AI agent pen-testing |
| 02 | MCP Scanner | arsenal mcp scan | 8 probes for MCP server security |
| 03 | Honeypot | arsenal honeypot deploy | 6 AI agent personas, 4-level trap escalation |
| 04 | Inject Fuzzer | arsenal inject fuzz | 6 generators, 5 mutators, 126+ payloads |
| 05 | C2 Simulator | arsenal c2 assess | 5 implants, 4 covert channels |
| 06 | Memory Scanner | arsenal memory scan | 6 probes for AI memory systems |
| 07 | Tool Scanner | arsenal tool scan | 7 probes for tool-use vulnerabilities |
| 08 | Auth Scanner | arsenal auth scan | 7 probes for AI authentication |
| 09 | RAG Scanner | arsenal rag scan | 6 probes for RAG pipeline attacks |
| 10 | Supply Chain | arsenal supply scan | 7 probes for AI supply chain security |
| 11 | Canary Deploy | arsenal canary deploy | 5 asset types for tripwire detection |
| 12 | Drift Scanner | arsenal drift scan | 6 probes for safety degradation over time |
| 13 | Path Mapper | arsenal path map | BloodHound-style attack graph analysis |
| 14 | Report Builder | arsenal report build | Unified reporting with Ed25519 signing |
Tool Details
Five co-ordinated attack agents that probe AI agents for vulnerabilities across 19 attack vectors.
- WRAITH — Reconnaissance and fingerprinting
- SPECTER — Prompt injection and manipulation
- SHADE — Evasion and bypass techniques
- PHANTOM — Multi-agent swarm attacks
- REVENANT — Persistence and re-infection
19 vectors (V-001 to V-019) mapped to OWASP Agentic Top 10 and MITRE ATLAS. Platform presets for OpenAI, Anthropic, LangChain, CrewAI, AutoGen, MCP, LangServe, and generic targets.
Security scanner for Model Context Protocol servers. 8 probes covering the full MCP attack surface.
- Discovery — Enumerate exposed MCP endpoints
- Authentication — Test auth mechanisms and bypass
- Tool Poisoning — Inject malicious tool definitions
- Schema Validation — Test schema enforcement
- Capability Abuse — Probe over-provisioned capabilities
- Transport Security — Test transport layer weaknesses
- Server Impersonation — Test for spoofing vulnerabilities
- Data Exfiltration — Test data leakage via MCP channels
Deploys decoy AI agent endpoints with 6 configurable personas. 4-level trap escalation from passive observation to active engagement. SQLite-backed attack capture with real-time classification.
- Personas: OpenAI, Anthropic, LangChain, MCP, Generic, Vulnerable
- FastAPI server with configurable trap levels
- Automatic attack classification and evidence collection
Advanced prompt injection fuzzing engine with 6 payload generators, 5 mutation engines, and 3 fuzzing strategies.
- Generators: Direct injection, Indirect injection, Jailbreak, Extraction, Exfiltration, Composite
- Mutators: Encoding, Obfuscation, Semantic, Structural, Evasion
- Strategies: Guided, Random, Adaptive
- 126+ base payloads, expanded by mutation to thousands of variants
Simulates command-and-control infrastructure for AI agents. Tests whether agents can be covertly controlled by an adversary.
- Implants: Prompt-based, Memory-resident, Tool-hijacking, Exfiltration, Lateral movement
- Channels: HTTP callback, Steganographic, Tool-based, Memory-based
- FastAPI-based controller for real-time implant management
- 5 operational modules for post-compromise simulation
Tests AI agent memory systems for poisoning, persistence, and manipulation vulnerabilities. 6 probes, 67 payloads.
- Short-term memory manipulation
- Vector store poisoning
- Delayed trigger implants
- Cross-session persistence
- Retrieval bias injection
- Dormant implant planting
Tests tool-use vulnerabilities in AI agents. 7 probes, 70 payloads.
- Schema confusion attacks
- Argument smuggling
- Output chain manipulation
- Over-permission exploitation
- Approval bypass
- Result poisoning
- Unsafe tool composition
Tests authentication and identity vulnerabilities in AI agent systems. 7 probes, 67 payloads.
- Token leakage and extraction
- Confused deputy attacks
- OAuth flow abuse
- Agent impersonation
- Stale credential exploitation
- Trust chain manipulation
- MCP authentication bypass
Tests Retrieval-Augmented Generation pipelines for poisoning and manipulation. 6 probes, 58 payloads.
- Document injection
- Hidden instruction embedding
- Ranking manipulation
- Citation corruption
- Policy implantation
- Retrieval-based exfiltration
Tests AI agent supply chain integrity. 7 probes, 70 payloads.
- Dependency chain analysis
- Tool integrity verification
- Model provenance validation
- Plugin manifest poisoning
- Template provenance attacks
- MCP trust boundary testing
- Sandbox escape vectors
Plants decoy assets into agent context and monitors for unauthorised access or leakage. 5 asset types, 58 payloads.
- Canary documents — decoy files with tracking markers
- Canary endpoints — honeypot API URLs
- Canary records — fake database entries
- Canary references — trackable citations
- Canary credentials — decoy tokens and keys
Measures safety degradation over time. Tests whether agent guardrails weaken across extended conversations. 6 probes with DriftCurve temporal analysis.
- Guardrail decay measurement
- Policy compliance drift
- Goal drift detection
- Memory contamination over turns
- Tool abuse escalation
- Baseline comparison analysis
Produces DriftCurve data structures showing safety scores across conversation turns — visual evidence of degradation.
BloodHound-style attack graph analysis. Consumes findings from all 13 other tools and builds a unified attack graph.
- Graph construction from cross-tool findings
- DFS/BFS path traversal
- Attack chain identification
- Blast radius calculation
- Compromise simulation from any entry point
- Worst-case scenario analysis
Unified reporting across all Arsenal tools. Aggregates, deduplicates, scores, and signs findings into board-ready evidence bundles.
- Aggregator: Loader, Normalizer, Deduplicator, Scorer
- Formatters: JSON evidence bundle, HTML report, PDF export
- Coverage maps: OWASP Agentic Top 10, MITRE ATLAS
- Signing: Ed25519 digital signatures on all reports
- Integrity: SHA-256 evidence chains across all findings
Full Assault Mode
One command runs the complete kill chain. All 14 tools execute in sequence, findings feed into attack path mapping with compromise simulation, and the result is a signed evidence bundle.
What Happens
- Phases 1-10: All scanning tools run against the target
- Phase 11: Attack Path Mapper builds a unified graph from all findings
- Phase 12: Report Builder aggregates, deduplicates, scores, and signs
- Output: JSON evidence bundle, HTML report, attack graph
CLI Options
Key Features
Requirements
- Python 3.11+
- httpx — async HTTP client
- typer — CLI framework
- rich — terminal formatting
- pydantic — data validation
- jinja2 — report templating
- pyyaml — configuration
- cryptography — Ed25519 signing
- fastapi + uvicorn — honeypot and C2 servers
Standards Coverage
Every finding Arsenal produces is mapped to industry security frameworks:
- OWASP Agentic Top 10 — 10/10 categories covered
- MITRE ATLAS — technique-level mapping
- NIST AI RMF — alignment
Each finding includes: severity, confidence score, evidence, remediation guidance, OWASP reference, and MITRE reference.
Packaging
Arsenal is available in three package formats for security-focused Linux distributions:
- Debian / Kali / Parrot / REMnux / Tsurugi — .deb package
- BlackArch — PKGBUILD
- PyPI — pip install
For access, contact richard@red-specter.co.uk
Disclaimer
Red Specter Arsenal is designed for authorised security testing, research, and educational purposes only. You must have explicit written permission from the system owner before running any Arsenal tool against a target. Unauthorised use may violate the Computer Misuse Act 1990 (UK), the Computer Fraud and Abuse Act (US), or equivalent legislation in your jurisdiction. The authors accept no liability for misuse.