An inventory that connects the dots.
Generate an AI-SBOM of agents, models, prompts, tools, and datastores. See the relationships that make your application work.
AI application safety & security
Know what’s in your AI application. Test what it can do. Turn security findings into evidence your team can act on.
pip install nuguard
Open source · Apache 2.0 · Python 3.12+
Source, behavior policy, and runtime evidence in one workflow.
From source to runtime
AI security goes beyond the model. Connect your code, policies, tools, and live behavior to understand where risk travels.
Generate an AI-SBOM of agents, models, prompts, tools, and datastores. See the relationships that make your application work.
Bring AI-specific analysis, Semgrep source checks, Checkov infrastructure checks, and dependency findings into the same review.
Explore analysisDefine allowed behavior in a Cognitive Policy. Check responses and tool use against the boundaries your team expects.
Explore behavior testingProbe prompt injection, data leakage, and tool misuse. Use multi-turn attacks and campaign mode to explore connected conversations.
Explore red-teamingRun bounded, explicitly authorized Nuclei-based tests against the web and API surfaces around your AI application.
Explore web pentestingReview affected assets, evidence, and remediation. Export reports and SARIF, then set severity gates for your release workflow.
Explore reporting & CIA clear path forward
Start with source code. Add your application’s policy and an authorized sandbox when you’re ready to test runtime behavior.
Turn source code into an AI-SBOM of your assets and data paths. The first scan needs no live target or LLM key.
Read the discovery guide# Map your application from source
nuguard sbom generate \
--source . \
--output app.sbom.json
Use a Cognitive Policy to describe allowed topics, data handling, and restricted actions. Validate it before live testing.
Read the policy guide# Validate your Cognitive Policy
nuguard policy validate \
--file cognitive_policy.md
Analyze the AI-SBOM for security issues and relationships that deserve a closer look. Review findings before moving to runtime checks.
Read the analysis guide# Analyze the discovered application
nuguard analyze \
--sbom app.sbom.json \
--source .
Configure your target and test identity, then verify the connection. Run behavior, red-team, or web tests to answer specific security questions.
Set up runtime testing# Verify your configured sandbox first
nuguard target verify \
--config nuguard.yaml \
--sbom app.sbom.json
Retain reports, review findings, and use severity gates in CI. Fix confirmed issues and rerun the relevant checks; review coverage gaps alongside results.
Explore release gates# Retain evidence and gate on severity
nuguard scan --source . \
--output-dir nuguard-reports \
--fail-on high
Fits your stack
Discover AI assets across languages, agent frameworks, exported workflows, and cloud deployments.
See support by integration Support depth varies by integration.Built for the whole team
Trace findings to code and assets. Test locally, fix the cause, and rerun the check.
Start buildingMake security repeatable with policy boundaries, CI gates, and release evidence.
Explore CI workflowsConnect inventory and attack paths with runtime evidence and coverage gaps.
Explore runtime testingStart with visibility
Map your application today. Build confidence with every test.
Prefer to run it yourself? Explore the open-source project ↗