A foundational rethink of security

AI creates attack surface area that grows faster than defenses.

What makes agentic security hard

Instructions and data intertwined

No syntactic boundary distinguishes commands from content.

Non-determinism

Execution paths emerge from LLM reasoning, not static code.

Semantic ambiguity

Infinite paraphrase space defeats pattern matching.

Stateful multi-turn context

Gradual manipulation appears benign in isolation.

Dynamic derivation chains

Prompts spawn prompts; policies must compose correctly.

Who, What, Why is scattered

Who authorized this call? What is the actual intent? Is this permitted? Why?

Agentic interactions reduce to 4 boundaries — prompts, data, context, tools

"Read the Q4 docs and email summary to john@company.com"

User Prompt
     ↓
┌──────────────────────────┐
│   LLM (Claude/GPT-4)     │
│   Decides: read + email  │
└──────────────────────────┘
     │
✗ Boundary 1: No verification of LLM intent
     ↓
┌──────────────────────────┐
│   Client Tool Calling    │
│   Invokes MCP servers    │
└──────────────────────────┘
     │
✗ Boundary 2: Tools called with full privileges
     │
     ├─────────────────────┐
     │                     │
     ↓                     ↓
┌──────────┐         ┌──────────┐
│MCP Server│         │MCP Server│
│filesystem│         │  gmail   │
└──────────┘         └──────────┘
     │                     │
✗ Boundary 3           ✗ Boundary 4
Data=Instr            Context leak
(injection)           (poisoning)
     ↓                     ↓
Read Q4.pdf          Send Email

MACAW protects every boundary crossing with cryptographic proofs.

Intent + Integrity

Protect all boundaries simultaneously.

Intent

We express intent and organizational permissions using MAPL policies. Policies verify that the desired operation matches what's actually permitted before execution.

  • Declarative policies checked before execution
  • Hierarchical inheritance — permissions only narrow
  • Attestations for external approval flows

Integrity

Every boundary crossing is cryptographically signed. Every response is verified. Tamper with anything and the chain breaks.

  • Every agent/tool gets cryptographic identity
  • Hash-chained audit logs with signed entries
  • Verifiable proof of who, what, when, why

Architecture

3 New Trust Primitives

Foundational primitives that enable policy-based controls across all agentic frameworks.

Authenticated Workflows

Every tool call, LLM invocation, and agent interaction is signed and policy-enforced. The complete request lifecycle has cryptographic proof.

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Authenticated Prompts

Every prompt has cryptographic origin. Track lineage from root to derived prompts. Know exactly where instructions came from.

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Authenticated Context

Session state is isolated and verified. No context bleed between users. Every piece of context has provenance.

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Implementation

Distributed Zero-Trust Mesh

Scalable, distributed, resilient enforcement at the edge with minimal blast radius.

Traditional Gateway

App → Gateway → LLM
       ↓
    (single point
     of failure)
  • • Single point of failure
  • • Latency overhead
  • • Can't enforce at runtime

MACAW Mesh

App ←PEP→ Agent ←PEP→ Tool
     │          │
     └── Policy ┘
    (enforced at edge)
  • • Enforcement at every endpoint
  • • Highly resilient, no SPOF
  • • Sub-millisecond overhead
┌────────────────────────────────────────────────────────────────┐
│                    MACAW CONTROL PLANE                         │
│                                                                │
│ ┌────────┐ ┌────────┐ ┌────────┐ ┌────────┐ ┌────────┐        │
│ │ Policy │ │ Agent  │ │ Audit  │ │Identity│ │Attestat│        │
│ │ Store  │ │Registry│ │  Logs  │ │ Bridge │ │ion Svc │        │
│ └────────┘ └────────┘ └────────┘ └────────┘ └────────┘        │
│                                                                │
└────────────────────────────────────────────────────────────────┘
                              ↑ ↓
┌────────────────────────────────────────────────────────────────┐
│                        DATA PLANE                              │
│                                                                │
│ ┌─────────┐            ┌─────────┐            ┌─────────┐     │
│ │   App   │            │  Agent  │            │  Tool   │     │
│ │  ┌───┐  │←──signed──→│  ┌───┐  │←──signed──→│  ┌───┐  │     │
│ │  │PEP│  │            │  │PEP│  │            │  │PEP│  │     │
│ │  └───┘  │            │  └───┘  │            │  └───┘  │     │
│ └─────────┘            └─────────┘            └─────────┘     │
│                                                                │
│ PEP = Policy Enforcement Point (embedded in SDK)              │
└────────────────────────────────────────────────────────────────┘

MAPL: Built for Agentic AI

Express agentic constraints in a dynamic, scalable manner as agents evolve and invocation context changes.

Policy Intersection

ORGANIZATIONAL        SERVICE
HIERARCHY             CONSTRAINTS
─────────────         ───────────

company:fintech       service:analytics-api
      │                       │
      ▼                       │
team:analytics                │
      │                       │
      └───────────┬───────────┘
                  ▼
            user:alice ◄── caller
                  │
                  │ delegated via
                  ▼
           app:dashboard ◄── app
                  │
                  ▼
          ═══════════════════
          EFFECTIVE POLICY
          (intersection of all)
          ═══════════════════

Policies compose through intersection. Each level can only restrict, never expand permissions.

Policy Example

{
  "policy_id": "user:alice",
  "extends": "team:engineering",
  "scope": "user",

  "resources": [
    "llm:openai/chat.completions",
    "tool:calculator/*"
  ],

  "constraints": {
    "llm:openai/chat.completions": {
      "model": ["gpt-3.5-turbo"],
      "max_tokens": { "max": 1000 }
    }
  }
}

Declarative policies with AI-specific primitives: models, tokens, tools, attestations.

Plug-n-Play Enterprise

Complex infrastructure made simple by design.

YOUR IDP                 MACAW
────────                 ─────

┌──────────┐         ┌──────────────┐
│  Okta    │         │   Identity   │
│  Azure   │──JWT───→│    Bridge    │
│ Keycloak │         │              │
└──────────┘         │  ┌────────┐  │
                     │  │ Claims │  │
                     │  │ Mapper │  │
                     │  └────────┘  │
                     │      ↓       │
                     │  ┌────────┐  │
                     │  │ Policy │  │
                     │  │ Context│  │
                     │  └────────┘  │
                     │      ↓       │
                     │  ┌────────┐  │
                     │  │  OTEL  │──────→ Your Stack
                     │  │ Export │  │
                     │  └────────┘  │
                     └──────────────┘

Identity Bridge

Connect any OIDC/JWT provider. Map claims to MACAW policy attributes. Switch IDPs without code changes.

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OTEL Export

Export traces and metrics to your existing observability stack. One config, full visibility.

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Agentic Traces

End-to-end visibility across request flows, policy resolution, agent lifecycle, and prompt chains.

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Multi-Tenant Config

Team management, signing controls, log rotation, and attestation settings — all configurable.

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The Complete Picture

4

Attack Boundaries

3

Primitives

0

Trust Assumptions

1

Line of Code

MACAW provides deterministic security for agentic AI — not probabilistic detection, but cryptographic proof at every boundary.