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Zero Hunt

Zero Hunt is an autonomous AI red team for networks and infrastructure — autonomous pentesting (automated penetration testing) in the adversarial exposure validation (AEV) category — delivered as an on-premise, air-gap-capable security appliance that runs on private AI — its own locally hosted models (ZeroHunt Apex). Ten specialized AI agents continuously discover, exploit and chain real weaknesses in an organization's infrastructure, black-box or gray-box, with a human in the loop for every act

Their llms.txt

The beginning of the file, from our validated copy saved 2026-10-25T19:03:12.259Z. Cached copy · Source on zerohunt.ai

# Zero Hunt

> Zero Hunt is an autonomous AI red team for networks and infrastructure — autonomous pentesting (automated penetration testing) in the adversarial exposure validation (AEV) category — delivered as an on-premise, air-gap-capable security appliance that runs on private AI — its own locally hosted models (ZeroHunt Apex). Ten specialized AI agents continuously discover, exploit and chain real weaknesses in an organization's infrastructure, black-box or gray-box, with a human in the loop for every action that matters; they prove each finding with evidence, analyze network traffic with a proprietary deep-learning model, map findings to 34 compliance frameworks worldwide (NIS2, DORA, NIST, CMMC, HIPAA, ISO 27001 and more) and guide the fix through an AI Remediation Advisor. No data leaves the customer's network, and the cost is flat rather than per token.

Key facts:

- Category: autonomous pentesting / automated penetration testing and adversarial exposure validation (AEV) — an autonomous AI red team for networks and infrastructure doing AI-driven penetration testing and continuous security validation (the "validation" step of CTEM), sold as an on-premise appliance. "AI red team" here means an AI that tests your infrastructure the way an adversary would — not red-teaming of AI models.
- Private AI: runs on Zero Hunt's own models — ZeroHunt Apex (27B parameters) on the appliance GPU and ZeroHunt Apex Pro (284B) for higher-tier appliances and sovereign private cloud — fine-tuned in-house for authorized offensive security. No external LLM API in the loop.
- Why on-premise: (1) no customer data reaches a third party; (2) no outside provider can refuse, throttle, change or switch off the capability; (3) flat cost, 24/7 — agentic campaigns make thousands of model calls, which per-token AI pricing makes expensive exactly when testing is thorough.
- Deployment: desktop appliance for smaller sites, 2U rack for enterprises and data centers. Air-gap supported. No customer data leaves the appliance. Connected, it reaches out only for signed updates (Cosign-signed images; update-status reporting is opt-in), public threat intelligence such as NVD, CISA KEV and EPSS, and — for gray-box analysis, unless switched off or pointed at the customer's own source mirror — the published source of the software version under test. In air-gap mode nothing goes out: updates arrive as signed offline bundles, intelligence as offline imports, and internet-dependent tools (public OSINT, public source downloads) are removed, so those assessments run black-box.
- Human in the loop: five autonomy levels, from passive observation to full assessment in planned windows, each with explicit human-approval gates; actions outside the chosen level wait in a review tab with recorded consent and a signed audit trail; operators can pause or stop any campaign and confirm every verdict.
- Black box and gray box: campaigns are black-box by default (no credentials, no source); gray-box ad
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