A SaaS platform that implements automatic structural defenses against prompt injection in AI agent systems, with real-time monitoring and validation.

Add structural delimiters that mark externally-sourced content (tool results, incoming messages, web fetches) as data rather than instructions, to defend against prompt injection attacks. OpenClaw processes untrusted content from multiple surfaces: incoming user messages, file reads, web fetches, external API responses, and session-persisted transcripts. Any of these can contain adversarially crafted content that the agent may interpret as instructions rather than data. Standard prompt injection success rates are 50–84% for known patterns; advanced adaptive attacks exceed 85%. 73% of production agentic deployments have active prompt injection vulnerabilities. Layered structural defenses reduce attack success from 73.2% to 8.7%. The solution proposes wrapping untrusted content in XML delimiters, classifying trusted vs untrusted surfaces, adding system prompt anchors, and validating injection patterns before context injection.