prompt-injection-mcp
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- AlicenseNot gradedqualityBmaintenanceEnables red-team testing of AI agents against indirect prompt injection by fuzzing payloads with delimiter evasion and Unicode homoglyphs, detecting exfiltration canaries, enforcing least-privilege tool boundaries, and producing cryptographic audit proofs.7MIT
- AlicenseNot gradedqualityBmaintenanceEnables real-time injection fuzzing and canary-based exfiltration detection over untrusted prompts, RAG context, and agent actions, with entropy analysis, outbound channel interception, least-privilege sandboxing, and cryptographic audit proofs.7MIT
- AlicenseBqualityDmaintenanceEnables testing AI safety classifier robustness against query decomposition, obfuscation, and multi-agent attacks. Provides tools for full evaluation pipelines, query previews, and status checks.46MIT
- AlicenseBqualityDmaintenanceProvides local, dependency-free security scanning tools for LLM configurations, prompts, RAG sources, and more, enabling AI coding agents to detect prompt injections and other vulnerabilities without external network access.8MIT
- AlicenseNot gradedqualityAmaintenanceEnables users to scan untrusted text, files, and directory trees for prompt-injection patterns and receive severity-ranked, explainable verdicts before content reaches an agent. It runs locally and returns clean, review, or blocked verdicts for safer agent input.1MIT
- AlicenseBqualityDmaintenanceEnables security teams to run controlled adversarial penetration tests against authorized ML/LLM API endpoints, scoring responses and generating evidence for compliance frameworks such as SOC 2, ISO 27001, and GDPR.62MIT
TDQS
Scored across 8 tools
Each tool targets a distinct phase of the testing workflow: listing categories, retrieving payloads (by category, ID, or keyword), generating custom payloads, running tests, analyzing responses, and reporting. Minor overlap exists between search_payloads and get_payloads_by_category, but their scopes and verbs are clearly differentiated.
All tool names use consistent snake_case and follow a verb_noun or verb_noun_preposition pattern (list_, get_, run_, generate_, analyze_, search_). No conventions are mixed.
8 tools cover the entire prompt-injection testing lifecycle without redundancy. Each tool maps to a natural workflow step, making the set lean yet sufficient.
The core workflow from payload discovery to report generation is fully covered. Missing management operations for payloads (update/delete) and test sequences, but the read/generate/run/analyze path is complete for typical testing use.