MCP Security + Guardian Agent Demo This demo showcases MCP Security Guardrails using Daxa, Inc MCP gateway— the foundation of agentic security. A few key concepts to watch for: 🔐 1. Security guardrails = static layer + agentic layer MCP security policy is the combination of traditional static controls and a new dynamic, agentic layer. Static Layer (Traditional Guardrails) These look familiar — identity, posture, and content-based controls — but rebuilt for AI agents and MCP workflows. 🧬 Identity-Based Guardrails Enforce authentication Ensure RBAC authorization flows down through MCP to the APIs the agent calls. OAuth will likely become the norm Validate whether the agent should have write/delete permissions. NB: developers are not security people — RBAC will often be missing, incomplete, or overly permissive. 👉 This is where a new compensating access controls come in (enter the Guardian Agent i.e. agentic IAM/PAM). 🛡️ Posture-Based Guardrails Zero-trust logic applied to AI agents: Should this agent be allowed to update HR policy? Is the agent running with known critical or high vulnerabilities? Are compensating security controls enabled on the host? Yes — the usual ZTNA mambo-jumbo, but for agents instead of humans. 📦 Content-Based Guardrails Where the MCP security agent / eBPF / gateway / SSE components matter: Inspect data returned to the agent Detect prompt injection attempts in queries and responses Classic DLP and threat-detection territory 🔮 2. The Agentic Layer — Enter the Guardian Agent This is the exciting part. In the demo, this is represented by Daxa’s concept of the Guardian Agent — (and honestly, don’t we all need a guardian agent?) Why this matters: MCP security itself becomes agentic — because only AI can watch AI. Think of it as a modern UEBA: not rules and time series, but generative-AI-powered behavioral reasoning across identity, posture, content, and context (with state and continuous learning). This dual-layer pattern — static guardrails + agentic behavioral oversight — is something we will likely see across the entire security stack. It’s essentially the natural evolution of everything detection & response: 👉 AI-Detection Response (AIDR) for acronym lovers. Enjoy the demo! Let me know what I missed and resonates. #aisecurity #agentsecurity #mcpsecurity #mcp #daxa #pebble #guardianagen
Great demo—love the two-layer guardrails concept. For API security, how is end-to-end identity and authorization enforced as agents call multiple MCP services? Do you rely on OAuth/OIDC tokens, and is mTLS used between microservices to enforce least privilege when RBAC is imperfect at design time? On the Guardian Agent, what signals drive its behavior, and how do you prevent policy drift or overreach? For content guards, how quickly can you detect prompt injection and data leakage across chained calls, and how is that logged for forensics? Would also love to see a concrete API-centric threat model and playbook to accompany this. #aisecurity #agentsecurity #mcpsecurity #mcp #daxa #guardianagen
Nico Popp thanks for adding life to the guardian agent concept. The demo was really informative. quick question" Guardian agents can only 'guard' registered agents (at least for now). How do you see guardian agents guarding unregistered agents (that are nonetheless detected? And are you still classifying runtime data that hasn't been classified at rest, and if yes, how do you manage the permissions for access of runtime-classified data that has no permissions yet associated?