AI systems touch sensitive data at every layer.
Input, memory, tool-calls, outputs.
Gray Swan is built to catch it before it walks out the door.
AI agents interact with customer PII, proprietary data, and internal systems in ways traditional DLP was never designed for. The risk isn’t hypothetical.
Sensitive data leaks through crafted inputs or unguarded outputs.
Mishandled data in AI pipelines triggers compliance violations before anyone notices.
Information retained across sessions surfaces to the wrong user or workflow.
Agents with API, database, and file access can be manipulated into retrieving or sharing data they shouldn't.
Most AI security vendors build defenses based on known attacks. Gray Swan discovers the unknown ones.
Gray Swan sits between your AI systems and the data they touch. Monitoring, validating, and enforcing policy in real time; not keyword matching.
Context-aware enforcement trained on real adversarial techniques discovered by our research team and in our Arena.
Shade autonomously red-teams your AI systems for data exposure risks. Simulate prompt injection, context manipulation, and tool-call exploitation at scale.
Every test scenario is built on threat intelligence from Gray Swan’s Arena, where emerging attack techniques are discovered long before they surface publicly.
Every prompt, response, and tool interaction validated against your custom policies, as it happens; not after the fact.
Simulates the exact data extraction techniques attackers use today: jailbreaks, indirect prompt injection, context manipulation. So you find the gaps before they do.
New attack patterns are discovered continuously in Gray Swan’s Arena and fed directly into your detection models, keeping protection ahead of the threat landscape.
Our research has directly informed the safety evaluations of some of the most advanced AI models in the world.
See how Gray Swan prevents data exposure across your AI stack, without slowing down deployment.
