Engineering Security for Autonomous AI Systems
AgentClad Security was founded to solve the unique security challenges introduced by non-deterministic LLM decision loops, Model Context Protocol (MCP) tool integrations, and agentic access to production environments.
Engineering Principles
Concrete Code Proofs
We deliver reproducible proof-of-concept exploits, patch PRs, and containerized test cases—never theoretical fluff or generic advisory slides.
Non-Deterministic Rigor
Standard Web2 penetration testing fails against AI agents. We audit system prompt boundaries, memory state corruption, and model tool delegation limits.
Zero Telemetry Privacy
We maintain strict NDA confidentiality. Client system prompts, model weights, and proprietary architecture blueprints are protected under air-gapped security protocols.
Notice Regarding Technical Artifacts & Working Brand
All sample audit reports, deliverable templates, and code artifacts displayed on this platform are labeled as fictional samples for demonstration purposes. Legal entity incorporation and commercial licensing terms remain subject to counsel review.
Connect with Our Security Engineering Team
Discuss your AI architecture, threat surface, or compliance targets with our lead researchers.