CyberArmor.AI
CyberArmor provides AI trust infrastructure that enforces real-time controls over what large language models can read, share, and output. The platform gates untrusted content before ingestion, redacts sensitive data before it leaves, and blocks insecure responses according to policy, recording every decision on a tamper-evident ledger. It can be self-hosted, cloud-hosted, or fully air-gapped, with a 15-minute local proof-of-concept available.
- Cybersecurity
- Artificial Intelligence
- Software Only
Funding
Founders
Founder details are not available yet.
Product
Problem
As AI systems are integrated into enterprise workflows, organizations lack real-time, enforceable controls over what models can read, share, and output. Untrusted content can reach models unchecked, sensitive data can leave without redaction, and insecure AI responses can reach downstream systems, creating security, compliance, and governance risks that traditional security tools do not address.
Solution
CyberArmor provides an AI trust infrastructure platform that enforces policy in both directions: hostile content is gated before it becomes AI context, and secrets, PII, and dangerous output are stopped before they leave. A pre-ingestion URL and context trust gate evaluates external content for phishing, hidden prompt injection, and promptware before a human, browser, endpoint, app, or AI agent ingests it. A policy engine backed by OPA decides allow, warn, redact, block, or isolate actions, while redaction and response enforcement catch dangerous output such as shell commands or script injections on the way out. Every decision is recorded on a hash-chained, tamper-evident ledger for audit and compliance, and the platform can be self-hosted, cloud-hosted, or fully air-gapped.
Target Audience
Primary customers are CISOs, security architects, and heads of AI governance at enterprises that deploy or plan to deploy AI systems, including AI coding agents, and need enforceable, auditable controls over AI activity.
Features
- URL & Context Trust Gate with canonicalisation, homoglyph/punycode checks, SSRF-guarded safe crawl, and optional Playwright detonation to surface hidden promptware
- Policy Enforcement Engine backed by OPA with Python fallback, evaluating tenant, actor, workload, model, provider, data, and risk context
- Redaction across 37 classes of sensitive data, plus dangerous-output detection for shell commands, script injections, and browser-data-exfiltration patterns (OWASP LLM02)
- AI Asset Discovery & Inventory with AI Bill of Materials (A-BOM), OSV-backed CVE matching enriched by CISA KEV and FIRST EPSS scoring
- Hash-chained, tamper-evident evidence ledger recording all policy decisions with artifact references
- Enforcement points including endpoint agents (Windows, macOS, Linux), browser/VS Code/Office extensions, RASP SDKs in 9 languages, SIEM forwarders, and a ROS 2 robotics agent