EnforceCore

The runtime enforcement layer for agentic AI systems.

EnforceCore provides mandatory, policy-driven enforcement at every external call boundary for any Python-based agentic system. It ensures that AI agents operate within defined safety constraints — tool access, PII redaction, cost budgets, rate limits, content rules, and network controls — with cryptographically verifiable audit trails.

Quick Start

pip install enforcecore
from enforcecore import enforce

@enforce(policy="policies/strict.yaml")
async def search_web(query: str) -> str:
    return await api.search(query)

Key Features

Feature Description
🔒 Policy Enforcement YAML-defined policies with allow/deny lists, tool gating
🕵️ PII Redaction Regex-based detection of emails, phones, SSNs, credit cards, secrets
📜 Merkle Audit Trail SHA-256 chained, tamper-proof audit logs
💰 Cost & Resource Guard Budget tracking, time limits, memory limits, kill switch
🌐 Network Control Domain allow/deny lists with wildcard support
⚡ Rate Limiting Sliding-window per-tool and global rate limits
🔌 Framework Integrations LangChain callback handler, LangGraph, CrewAI, AutoGen adapters
📊 OpenTelemetry Traces, metrics, and spans for observability
🧪 Evaluation Suite 26 adversarial scenarios across 11 threat categories + benchmarks
🔌 Plugin Ecosystem Custom guards, redactors, and audit backends via PyPI entry-points
📋 Compliance Reporting EU AI Act, SOC2, GDPR compliance exports
🏗️ Multi-Tenant Hierarchical policies with tenant-level isolation