Don't reinvent the infrastructure.
Secure your agents where they already run.
Kubernetes. Docker. SPIFFE. OPA. Decades of production mileage, assembled into a single agentic security substrate. Many frameworks propose entirely new paradigms like WASM sandboxes and novel runtimes that still need to earn enterprise trust. PRECINCT assembles what already has it. Your stack stays. Your processes stay. Your auditors already understand the components.
Already have an agent? Connect it in 4 steps →
The Authorization Crisis in Agentic AI
50 : 1
Non-human identities already outnumber humans 50 to 1. AI agents are not static service accounts. They are adaptive, goal-oriented, ephemeral, and potentially adversarial. Traditional IAM frameworks were designed for predictable, human-initiated workflows, not for autonomous reasoning agents that decide at runtime which tools to invoke and what data to access.
| Dimension | Traditional Service Account | AI Agent |
|---|---|---|
| Behavior | Deterministic, pre-coded paths | Adaptive, goal-oriented reasoning |
| Scope | Fixed permissions, known at deploy time | Dynamic: decides at runtime which tools to call |
| Lifetime | Long-lived, static credentials | Ephemeral, session-scoped, potentially spawning sub-agents |
| Decision-making | None: executes coded logic | Autonomous multi-step planning and execution |
| Resource access | Pre-configured, bounded | Emergent: discovered and requested at runtime |
| Trust model | Implicit trust once authenticated | Continuous verification required at every step |
Every Organization Faces Three Choices
Build from Scratch
Years of security engineering drag, duplicated effort across teams, uneven controls, and no guarantee of completeness. Every gap is a breach waiting to happen.
Buy a Closed Platform
Vendor lock-in from day one. Opaque controls you cannot inspect. Reduced auditability. Your security posture depends on someone else's roadmap.
Adopt PRECINCT
Open, portable, auditable, and enterprise-ready. Every layer is inspectable. Every policy decision is logged. Deploy on any infrastructure. No vendor lock-in. Apache 2.0 licensed.
Get StartedNine Key Innovations
Late-Binding Secrets
Agents never see real credentials. They operate with opaque, meaningless tokens that are resolved to actual secrets only at egress time, inside the gateway.
13-Layer Defense-in-Depth
An ordered middleware chain where every request passes through 13 distinct enforcement layers before reaching any upstream service.
Tool Registry with Hash Verification
Every tool is registered with a cryptographic hash. The gateway verifies tool integrity at invocation time, defending against tool poisoning and rug-pull attacks.
Session Context Engine
Tracks cumulative agent behavior across requests within a session. Detects cross-request data exfiltration patterns and maintains a running risk score.
Five Governed Planes + RLM
Model, Tool, Context, Loop, and Ingress planes each with their own policy domain, plus a cross-cutting RLM (Recursive Language Models) governance engine. RLM, introduced by Zhang, Kraska & Khattab (2025), enables LLMs to recursively decompose and delegate tasks across depth levels -- PRECINCT governs these recursive call chains with per-lineage resource limits.
Python & Go SDKs
First-class SDK support in both Python and Go. Agents integrate with the PRECINCT gateway using idiomatic libraries that handle SPIFFE identity, error mapping, and structured logging automatically.
Multi-Agent Governance
The RLM Governance Engine tracks multi-agent lineage across nested subcalls, enforcing depth limits, subcall budgets, and budget-unit accounting so recursive agent chains cannot spiral out of control. A loop state machine with operator halt provides a human kill switch for runaway loops.
Model Egress Governance
All LLM provider access is gateway-mediated in production. The gateway acts as the sole identity and policy enforcement point for model egress, enabling auditable control over model selection, cost budgets, data residency, and per-provider trust policies.
Principal Hierarchy
Agent identities resolve into a six-level authority hierarchy, from System down to Unknown. An instruction from an operator carries fundamentally different permissions than the same instruction from a standard agent, enabling owner-only operations and delegation-aware authorization.
The 13-Layer Enforcement Chain
Every request traverses these layers in strict order. No shortcuts. No bypass.
Key design constraint: Token substitution happens last, at step 13, immediately before egress. No middleware layer ever sees raw credentials. The agent never possesses, observes, or logs a real secret.
Complete Capability Coverage
A single capability map that consolidates runtime controls, integrations, operations tooling, and proof workflows.
Runtime Enforcement
13-layer chain with policy, DLP, memory tiering, CLI shell-injection prevention, step-up, deep scan, rate limiting, and late-binding token substitution.
Identity & Secrets
SPIFFE/SPIRE workload identity with SPIKE-backed secret references so agents never hold real credentials.
Adapter Coverage
Reference port adapter with live HTTP, WebSocket, and webhook enforcement through the gateway.
Ops & Assurance
Compose + Kubernetes workflows, dual observability (Phoenix + optional OpenSearch Dashboards), compliance automation, and security validation gates.
Built on Proven Open-Source Infrastructure
SPIFFE / SPIRE
The CNCF standard for workload identity. Every agent, service, and sidecar receives a cryptographically verifiable SPIFFE ID: no static secrets, no shared tokens. Identity is attested, not asserted.
Learn more →SPIKE
The secrets store purpose-built for SPIFFE workloads. Agents authenticate with their SVID and receive only the secrets their policy permits, scoped to the current session and task.
Learn more →OPA (Open Policy Agent)
Fine-grained, declarative policy enforcement. Every agent request is evaluated against Rego policies that encode your organization's security requirements as auditable, version-controlled code.
Learn more →PRECINCT Gateway
The enforcement point. A reverse proxy that orchestrates the 13-layer middleware chain, mediates all agent-to-tool communication, and ensures no request bypasses policy evaluation.
Learn more →Compliance-Ready from Day One
Pre-built control mappings. One-button evidence generation. Auditor-ready reports.
Run Anywhere
Docker Compose
Local development and evaluation
Stand up the entire PRECINCT stack on your laptop in minutes. Ideal for evaluation, demos, and local development workflows.
make upKubernetes
Production on any conformant cluster
Production-grade deployment on any Kubernetes-conformant cluster. Helm charts, health checks, and horizontal scaling included.
make k8s-upGrounded in Peer-Reviewed Research
PRECINCT's threat model, defense architecture, and governance design are informed by published security research, not invented in isolation.
Agents of Chaos
Shapira et al. (2026). A structured red-teaming exercise: 20 researchers spent 2 weeks attacking autonomous agents in a live environment. PRECINCT's 13-layer chain defends against all 16 documented threat case studies.
Read more →Securing the Model Context Protocol
Proposes a five-layer defense framework for MCP security: authentication, provenance tracking, isolation, inline policy enforcement, and centralized governance. PRECINCT implements all five layers.
Read more →Prompt Injection on Agentic Coding Assistants
Demonstrates 85%+ attack success rates against state-of-the-art agentic coding tools via prompt injection. Validates the need for PRECINCT's deep scan inspection and tool registry hash verification at the infrastructure level.
Read more →Recursive Language Models
Zhang, Kraska & Khattab (2025). Introduces the RLM framework enabling LLMs to recursively self-call over unbounded contexts via a REPL environment. PRECINCT's RLM Governance Engine enforces depth, subcall, and budget limits on these recursive chains.
Read more →Sponsored By
Special thanks to Cibertrend, Inc. and Hextropian Systems, Inc. for sponsoring the development of PRECINCT.
