Kairo
Kairo provides continuous, autonomous security testing that probes production systems around the clock, mapping exploitable paths that emerge from routine code changes. The platform reproduces attacks against shadow copies and verifies findings against live environments, shipping evidence with every detection. It has demonstrated effectiveness in live incident response, including stopping a ransomware attack that avoided over $6M in losses.
- Cybersecurity
- AI Agents
- Artificial Intelligence
- Software Only
Funding
Funding not disclosed
Founders
Founder details are not available yet.
Product
Problem
Software changes continuously as humans and AI agents create new behaviors with every release, yet traditional security tools only inspect static code snapshots or test specific moments in time. Attackers exploit the gaps between these checks, finding exploitable paths that emerge from routine changes and go undetected by periodic scans or manual pentests.
Solution
Kairo tests how software actually behaves in production, not just what the code looks like. It maps exploitable paths that emerge from routine changes, reproduces attacks against a shadow copy of the system, and proves them against a running production environment. Autonomous agents probe customer stacks around the clock, so new exposures are caught as they appear rather than discovered by the next attacker. Every finding ships with the evidence that reproduces it, and each verified result improves what Kairo looks for next, creating a continuously learning security testing loop.
Target Audience
Primary customers are security teams at defense, healthcare, and software/SaaS organizations that operate complex production systems and need continuous verification of their security posture against emerging threats.
Features
- Always-on autonomous agents that probe production stacks continuously, not once a quarter
- Shadow-copy attack reproduction that validates exploit chains without risking the live environment
- Evidence attached to every finding, including the exact reproduction path for immediate verification
- Behavioral analysis of both code and the agents/users that interact with it, not just static code review
- Mapping of how routine changes combine into new exploitable paths before they become production reality
- Findings verified against running production systems rather than shipped as scanner alerts
- Validation under a Cyber Verification Program and participation in AI agent security research initiatives