Independent research and defensive infrastructure for autonomous AI agent systems.
The Problem
Autonomous AI agents are deployed across critical infrastructure today — energy, defense, financial systems, healthcare, and supply chains. Peer-reviewed research demonstrates that every major platform is vulnerable to a class of attack that requires no malware, no network penetration, and no specialized tools. An adversary needs only natural-language proficiency and access to any channel the agent monitors.
Current defenses — retraining, system prompts, guardrails — cannot address this. The vulnerability is architectural.
What We Do
Clear Tech Labs develops and tests inference-layer defensive architecture for AI agent systems. Our solution operates as an independent pre-filter and post-filter on agent interactions — intercepting and evaluating all input before it reaches the language model, and validating all output before it reaches the user or executes actions.
The solution is:
- Platform agnostic — works across OpenAI, Anthropic, Google Gemini, xAI, and open-source models
- Portable — one implementation defends the entire ecosystem
- Purely defensive — not a weapon, not an intelligence tool, not an offensive capability
- Operational — currently being tested for deployment
Current Work
NIST RFI Response (March 2026)
Formal response to NIST CAISI Request for Information on AI agent security (Docket NIST-2025-0035). Addresses threat landscape, defensive architecture, assessment methodology, deployment controls, and monitoring.
AI Agent Threat Assessment
National security threat assessment covering autonomous AI agent vulnerabilities, active supply chain compromise, and the inference-layer defense solution. Available upon request — password protected.
NIST Framework Alignment
Detailed mapping of defensive architecture to NIST Cybersecurity Framework 2.0 and NIST AI Risk Management Framework 1.0. Available upon request.
Request a Briefing
The team behind this work is available to brief decision-makers directly — in person or remotely — on the threat, the architecture, and the deployment path.
One meeting is all that is needed to evaluate next steps.
Clear Tech Labs
All published findings derived from peer-reviewed research and publicly disclosed vulnerabilities.