Govern every AI Agent your enterprise depends on.
AgentGuardian helps enterprises discover, test, control, monitor, and prove AI agents with adversarial evidence.
Building with design partners across banking, healthcare, and public-sector teams in APAC.
Two products. One agent governance mission.
AgentGuardian Open Source.
Open-source red teaming for AI agents.
For developers, security engineers, and AI builders who want to test agents locally or in CI/CD.
- Prompt injection testing
- Tool abuse testing
- RAG poisoning testing
- Memory attack testing
- AIVSS scoring
- Local reports
- SARIF / JSON / HTML exports
- CI/CD gate
$ pip install agent-guardian
$ agent-guardian scan ./my_agent.py
$ agent-guardian serveAgentGuardian Enterprise.
Enterprise AI agent governance platform.
For security, risk, compliance, and AI platform teams governing agents across the organization.
- Agent discovery
- Shadow agent inventory
- Scheduled & continuous scans
- Runtime policy enforcement
- Monitoring & drift detection
- Approvals & exceptions
- Signed evidence packs
- SSO · RBAC · audit logs
- Customer-resident deployment
What AgentGuardian Enterprise does.
Discover
Find sanctioned, shadow, and experimental AI agents across cloud, SaaS, MCP servers, internal platforms, and custom applications.
Test
Run continuous adversarial red teaming against prompt injection, tool abuse, RAG poisoning, memory attacks, supply-chain risk, and agent-to-agent compromise.
Control
Enforce runtime policy for tool calls, data access, approvals, model egress, and agent-to-agent actions.
Prove
Generate signed evidence packs with attack traces, AIVSS scores, findings, remediation guidance, and governance mapping.
How AgentGuardian works.
Discover the agent
Map tools, memory, identity, data access, and agent-to-agent connections.
Attack the agent
Run adversarial probes against prompt, tools, RAG, memory, code execution, and multi-agent behavior.
Score the risk
Classify findings with AIVSS and severity levels.
Enforce policy
Apply enterprise controls for tools, approvals, data access, and unsafe actions.
Produce evidence
Generate signed evidence packs for security, risk, audit, and governance review.
Audit-ready evidence from real adversarial tests.
AgentGuardian does not rely only on questionnaires or posture inference. Every assessment can produce a signed evidence pack with attack traces, scores, findings, and framework mapping.
- Agents in scope
- Attack transcript
- AIVSS score
- Findings by severity
- Policy decisions
- Remediation guidance
- Framework mapping
- Verification manifest
EP-2026-Q1-0007
Built for the teams accountable for AI agents.
Find and test the real AI agent attack surface.
Continuous adversarial red teaming against prompt injection, tool abuse, RAG poisoning, memory attacks, and agent-to-agent compromise — across every agent in your estate.
Turn AI governance into signed, reviewable evidence.
Every assessment produces a signed evidence pack with attack traces, AIVSS scores, findings, remediation guidance, and framework mapping for audit and regulator review.
Give developers open-source red teaming, keep production governed.
Developers run AgentGuardian Open Source locally and in CI/CD. The same engine powers AgentGuardian Enterprise — so what developers see in build is what the security team sees in production.
Frequently asked questions.
Is AgentGuardian Open Source the full platform?
Is AgentGuardian a guardrail?
Does our data leave our environment?
Start with red teaming.
Scale to enterprise governance.
Run AgentGuardian Open Source locally in minutes, or book a demo to see the enterprise governance platform.