Zero‑trust, sovereign LLM clusters and autonomous hardening – managed in‑house.
Get StartedProduction-grade private inference clusters on high-performance multi-vendor hardware. Massive context windows, frontier-class local reasoning models, fully GPU-optimized for enterprise-scale deployments. No data leaves your perimeter.
Production hardening for local frontier models and agentic systems. Poisoning resistance, supply-chain provenance, runtime guardrails, model firewalling, and safe tool-use sandboxes for autonomous operations.
SBIR/STTR, NIST, DHS, and agency‑specific AI cybersecurity compliance. Full narrative development, budget justification, compliance mapping (NIST AI RMF, FedRAMP‑aligned), and autonomous daily compliance monitoring pipelines.
Custom intelligence pipelines that surface relevant security feeds, grant opportunities, and emerging threats specific to your AI stack—so you stay ahead without noise.
Hardened local AI systems built on your hardware: from model selection and runtime guardrails to air-gapped deployment. We engineer sovereign infrastructure you own and control.
Turnkey deployment and ongoing stewardship of private AI infrastructure. We handle setup, monitoring, and evolution so your system remains secure, performant, and yours alone.
runs continuous research on AI supply‑chain attacks, model poisoning, exposed inference endpoints, and live opportunities. All stored locally with full provenance.
Arbitrary code execution via deserialization in popular ML pipelines. Attackers poison model weights or weights metadata to gain footholds inside corporate AI training environments.
Attackers register near‑identical model names and Python packages. Unsuspecting teams pull \"hermes‑3\" or \"llama‑3.1\" variants that contain backdoors or data exfil.
Adversarial prompts that hijack autonomous agents mid‑task. Research showed 86% of tested frontier agents could be diverted to attacker goals with carefully crafted natural language.
Injecting a handful of malicious documents into a RAG corpus gives near‑total control over model outputs. Works against production retrieval systems used by enterprises.
Publicly reachable inference endpoints (Ollama, vLLM, OpenRouter misconfigs) being actively scanned and exploited. One reported case involved $500k+ in unauthorized compute.
1. Model provenance & signing 2. Supply‑chain SBOM 3. Runtime guardrails 4. Private inference only 5. Continuous autonomous threat intel (daily).