nuguard 0.6.2

AI application security — SBOM generation, vulnerability scanning, behavioral validation, and adversarial red-teaming for AI Agents

NuGuard Open Source

NuGuard is an open source AI application security toolkit. Its goal is to provide the most extensive redteaming and behavioral validation of Agentic AI applications.

AI developers can focus on building their applications while NuGuard continuously tests and validates them against a wide range of security risks, including prompt injection, tool misuse, data exfiltration, and more.

What It Does

• Generate an AI-SBOM from a local codebase or Git repo
• Analyze the SBOM for structural AI security risks and supply-chain issues
• Propose an AI behavioral policy based on the SBOM
• Perform static and runtime behavioral testing purpose built around the AI-SBOM and the behavioral policy
• Red-team a sandboxed AI application: most extensive and updated catalog of attack vectors plus custom-built scenarios. This includes prompt injection, tool abuse, data exfiltration, and related attack scenarios that exercise the various sub-agents, tools, and capabilities of the target system.
• Automated remediation suggestions for findings, including code snippets and policy adjustments
• Export findings in text, JSON, Markdown, and SARIF-oriented workflows

Current CLI Surface

Implemented and usable today:

• nuguard sbom
• nuguard analyze
• nuguard scan
• nuguard policy
• nuguard behavior
• nuguard redteam

Requirements

• Python 3.12+
• uv for the recommended local workflow

Installation

Python CLI:

pip install nuguard

The steps below describe how to set up a local development environment. This is recommended if you want to run the latest code, contribute to the project, or run the CLI with LLM-assisted features that require local environment variable configuration.

uv sync --dev

Run the CLI with:

uv run nuguard --help

Or, from the virtual environment:

. .venv/bin/activate
nuguard --help

Claude users can use plugin commands.

Follow the instructions in docs/plugin-guide.md to set up the NuGuard plugin for Claude and use it to run commands like /nuguard-sbom, /nuguard-analyze, and /nuguard-redteam directly from your conversations with Claude.

Quick Start

1. Generate an AI-SBOM

nuguard sbom generate --source . --output app.sbom.json

You can also scan a remote repository:

nuguard sbom generate \
  --from-repo https://github.com/org/repo \
  --ref main \
  --output app.sbom.json

2. Run Static Analysis

nuguard analyze --sbom app.sbom.json --format markdown

Typical outputs:

• markdown for human review
• json for automation
• sarif for code scanning pipelines

3. Behavioral Testing

nuguard behavior \
  --sbom app.sbom.json \
  --target http://localhost:3000 \
  --format markdown

4. Red-Team a Live App

nuguard redteam \
  --config nuguard.yaml \
  --output reports/redteam.md \
  --format markdown

For richer red-team coverage, you can also provide:

• a cognitive policy with --policy
• canary values with --canary
• a config file with --config

5. Run the Unified Pipeline

nuguard scan \
  --source . \
  --output-dir nuguard-reports

This is the easiest way to run SBOM generation plus static analysis in one pass.

Configuration

NuGuard supports project configuration through nuguard.yaml. A ready-to-edit example lives at nuguard.yaml.example.

Key areas in the example config:

• sbom: existing SBOM path
• source: source directory for generation
• policy: cognitive policy path
• llm: model settings for LLM-assisted features
• behavior: target URL, endpoint, and test profile settings for behavioral testing
• redteam: target URL, endpoint, canary file, profiles, scenario filters, guided conversation settings, and finding trigger controls (finding_triggers.*)
• analyze: minimum severity threshold
• database: SQLite or Postgres-backed storage settings
• output: output format and failure threshold

CLI flags take precedence over nuguard.yaml, which takes precedence over environment variables and built-in defaults.

Red-Team Canaries

NuGuard can watch for seeded canary values during dynamic testing to produce high-confidence exfiltration findings. Start from canary.example.json, create your local canary.json, seed those values into the target system, then point nuguard redteam at that file with --canary.

More detail is available in docs/redteam-engine.md.

Development

Install dev dependencies:

make dev

Run tests:

make test

Run linting and type checks:

make lint

Format the codebase:

make fmt

Publishing

This repo includes GitHub Actions workflows for Trusted Publishing to TestPyPI and PyPI:

• publish-testpypi.yml
• publish-pypi.yml

Before the workflows can publish, configure Trusted Publishers in TestPyPI and PyPI for the nuguard project with:

• owner/org: NuGuardAI
• repository: nuguard
• workflow file: publish-testpypi.yml or publish-pypi.yml
• environment: testpypi or pypi

Recommended release flow:

1. Run the TestPyPI workflow manually from GitHub Actions.
2. Verify the package install and CLI behavior from TestPyPI.
3. Create a GitHub release to trigger the PyPI publish workflow.

Repo Notes

• The repository currently contains example outputs and benchmark fixtures under tests/output/
• Some red-team and benchmark tests are opt-in and gated by environment variables
• LLM-assisted features depend on provider credentials being available via environment variables

License

License information is available in the LICENSE file.