Research & Disclosures
Security Research
In-depth analysis of MCP attack vectors, vulnerability patterns, and defensive strategies for AI agent ecosystems
MCP Sprawl
How unchecked growth of MCP servers creates hidden attack surfaces and operational blind spots across your AI infrastructure.
Command Injection
Exploiting unsanitized inputs in MCP tool calls to execute arbitrary commands on connected systems.
Tool Poisoning
Malicious MCP servers that masquerade as legitimate tools to intercept sensitive data and corrupt agent behavior.
MCP Security Guardrails
Designing and deploying policy-driven constraints that keep AI agents operating within safe boundaries.
Shadow AI
Unauthorized AI agents and MCP connections that operate outside IT visibility, bypassing security controls.
Jailbroken AI
Techniques that bypass model safety layers through crafted MCP contexts, enabling restricted actions.
Rug Pull
Trusted MCP servers that change behavior post-deployment to exfiltrate data or manipulate agent actions.
MCP Observability
Building comprehensive audit trails and real-time monitoring for all agent-to-tool interactions.