RAXIT SDK - Runtime AI eXecution Integrity & Trust
Project description
RAXIT SDK
Runtime AI eXecution Integrity & Trust - Security scanning SDK for AI agent applications.
Overview
RAXIT SDK is a static analysis tool that scans AI agent codebases and generates an Agent Assets Schema for security analysis, compliance checking, and runtime enforcement. It implements the A2AS (Agentic AI Runtime Security) framework developed collaboratively by AWS, Google, Meta, Cisco, and other major tech companies.
Features
- 12+ Framework Extractors: LangGraph, CrewAI, AutoGen, Swarm, PydanticAI, LlamaIndex, Google ADK, and more
- Security Analysis: Semgrep/CodeQL rules for trust boundary detection
- CaMeL Provenance: Agent asset metadata with data flow tracking
- CLI Tools:
raxit init,raxit migrate,raxit status - Incremental Scanning: xxhash-based cache for fast re-scans
- Trust Boundary Detection: Meta's "Rule of Two" compliance checking
- Graph Topology Extraction: Complete LangGraph structure analysis
Installation
Python (TestPyPI - Beta)
pip install -i https://test.pypi.org/simple/ raxit-sdk
TypeScript/Node.js (npm - Beta)
npm install @raxit/raxit@beta
Rust (crates.io)
[dependencies]
raxit-core = "0.1"
From Source (Development)
Using UV (recommended):
cd src/ai-security-sdk
uv venv
uv pip install -e ".[dev]"
Using pip:
pip install -e ".[dev]"
Quick Start
# Scan your agent project
cd /path/to/your/agent/project
raxit init
# View generated assets
cat .raxit/assets.yaml
Usage
Scanning a Project
raxit init [directory] --output .raxit/assets.yaml
Options:
--output/-o: Output file path (default:.raxit/assets.yaml)--format: Output format (yamlorjson, default:yaml)--workers: Number of parallel workers for scanning--incremental: Enable incremental scanning with cache--sign: Sign the schema with HMAC-SHA256--detect-trust: Enable trust boundary detection
Schema Migration
raxit migrate .raxit/assets.yaml --target-version 0.8.0
Status Check
raxit status
Shows tool version, dependencies, and configuration.
Architecture
raxit_sdk/
├── cli/ # Command-line interface
├── parser/ # AST parsing and framework extractors
│ ├── extractors/ # Framework-specific extractors (12+ frameworks)
│ └── analyzers/ # Cross-cutting analysis (secrets, networks, memory, etc.)
├── schema/ # Pydantic models for Agent Assets Schema
├── trust/ # Security analysis (Semgrep, CodeQL, Joern)
├── decorators/ # Trust decorators for agent code
└── integrity/ # Cryptographic signing and verification
Supported Frameworks
The SDK can extract agent metadata from these frameworks:
- LangGraph - StateGraph, nodes, edges, conditional routing
- CrewAI - Agents, tasks, crews, pipelines
- AutoGen - Agents, tools, group chats
- OpenAI Agents - Agent SDK
- Swarm - Multi-agent orchestration
- PydanticAI - Type-safe agents
- LlamaIndex - FunctionAgent, ReActAgent
- Google ADK - Sequential/parallel/loop agents
- n8n - Workflow automation (JSON)
- AgentChat - Conversational agents
- Strands - Custom framework
- Generic - Custom agent implementations
Examples
See examples/ directory for sample agent projects across multiple frameworks:
examples/langgraph/- LangGraph examplesexamples/crewai/- CrewAI examplesexamples/custom/- Custom agent implementations- And more...
Development
Running Tests
# All tests
uv run pytest tests/ -v
# Specific test suite
uv run pytest tests/test_extractors/ -v
uv run pytest tests/test_integration/ -v
Code Quality
# Lint
uv run ruff check raxit_sdk/
# Type check
uv run mypy raxit_sdk/
Trust Boundary Analysis
RAXIT implements Meta's "Rule of Two" for trust boundary detection:
A component is non-compliant if it has ALL three properties:
- [A] Processes untrusted input
- [B] Has sensitive access (credentials, data, systems)
- [C] Performs external actions (network, files, processes)
Use raxit init --detect-trust to enable this analysis. Requires Semgrep and optionally Joern for deep taint analysis.
Agent Assets Schema
The generated schema includes:
- Manifest: Metadata about the scan
- Agents: AI agents with roles, tools, and models
- Tools: Functions and capabilities
- Models: LLM configurations
- Graphs: LangGraph topologies
- DataFlows: CaMeL provenance tracking
- Networks: External API endpoints
- Memory: Vector stores and databases
- Secrets: Detected credentials (names only)
- Boundaries: Trust boundary analysis
- Guardrails: Security controls
- Audit: Security findings
License
Proprietary - raxIT Labs
Contact
For questions and support: engineering@raxit.io
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