LLM prompt injection detection for Go applications
High-performance MCP server for USPTO Enriched Citation API v3 with AI-powered data extraction, token-saving context reduction, progressive disclosure workflows, and seamless cross-MCP integration
A multi-layered prompt injection detection system built with Laravel.
High-performance MCP server for USPTO Patent File Wrapper API with secure document downloads, metadata access, and context reduction
High-performance MCP server for USPTO Final Petition Decisions API with context reduction and cross-MCP integration
High-performance MCP server for USPTO Patent Trial and Appeal Board (PTAB) with context reduction, progressive disclosure workflows, and seamless cross-MCP integration
Official JavaScript/TypeScript SDK for LockLLM
Official Python SDK for LockLLM
MalPromptSentinel (MPS) is a Claude Code skill that detects malicious prompts in uploaded files before Claude processes them. It provides two-tier scanning to identify prompt injection attacks, role manipulation attempts, privilege escalation, and other adversarial techniques.
Infrastructure for capturing LLM activations and SAE (Sparse Autoencoders) features, training probes for prompt maliciousness detection, and evaluating out-of-distribution generalization with Leave-One-Dataset-Out (LODO)
🚀 Improve patent analysis with a high-performance MCP server for USPTO Final Petition Decisions, featuring context reduction and customizable fields.
🔒 Safeguard LLM behavior with PromptGuard to detect unseen regressions and ensure reliable outputs amid evolving model updates.
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