Govern every AI agent your enterprise depends on.
The AI agent governance platform built on adversarial truth.
Discover every agent. Classify risk with AIVSS. Red-team continuously with an eleven-agent adversarial swarm. Enforce policy at runtime. Generate signed evidence your auditor can verify.
Built by Glacien · APAC-built · AWS-native · Apache 2.0 swarm available
Currently in design-partner phase with banking, healthcare, and public-sector teams across APAC.
Who's this for?
AgentGuardian is built around the three roles accountable for AI agents in regulated enterprises — each gets the artefacts and controls their function actually needs.
See your real AI attack surface.
Find every AI agent in your environment. Test continuously against agentic threats — goal hijack, tool misuse, memory poisoning, supply chain — the full OWASP ASI01–10.
See CISO use caseProve your AI governance is real.
Generate signed evidence packs mapped to your governance framework. Hand them to your auditor, your board, your regulator — cross-mapped to EU AI Act, NIST AI RMF, ISO 42001, MAS, APRA.
See Risk use caseShip agents without security becoming the blocker.
Inventory agents across every platform. Run AIVSS in CI/CD. Enforce policy before agents act. Move from pilot to production without an audit standoff.
See Platform use caseOne platform. Full agent lifecycle. Six capabilities.
A single control plane covering the full lifecycle — from discovery and AIVSS classification to continuous red-teaming, runtime enforcement, monitoring, and signed evidence.
Discover
Find every AI agent — sanctioned and shadow — across SaaS, cloud, homegrown frameworks, MCP servers, and endpoints. AI Bill of Materials included.
Classify
Score every agent with AIVSS — the OWASP-aligned scoring system that combines CVSS with ten agentic risk amplification factors. One number, comparable across releases and frameworks.
Red-team
Test continuously with an eleven-agent adversarial swarm. Goal hijack, tool misuse, memory poisoning, supply chain, code execution, A2A, drift — full OWASP ASI01–10 mapped to MITRE ATLAS.
Enforce
Apply runtime policy before agents act — tool calls, data access, model egress, agent-to-agent messages, human approval gates. Cedar-based policy engine.
Monitor
Track behavioural drift, tool anomalies, memory poisoning indicators, identity risk, cost spikes. SOC- and SIEM-ready event streams.
Evidence
Generate signed PDF/A-3 evidence packs with hash-chain anchoring. Cross-mapped to EU AI Act, NIST AI RMF, ISO 42001.
Most platforms infer risk from configuration.
We derive it from adversarial truth.
Other platforms look at how your agents are configured — permissions, tool inventory, identity scope, posture. They produce risk scores from posture signals.
AgentGuardian does something different. Every classification, every AIVSS score, every finding in every evidence pack starts from an actual adversarial attack run against the actual deployed agent — its actual goal, its actual tools, its actual memory, its actual framework.
The eleven specialist red-team agents that run those attacks are open source. Apache 2.0. Inspectable on GitHub. Reproducible from pip install agent-guardian. The same swarm that powers AgentGuardian's classifications also runs on a developer's laptop in CI/CD.
Three layers. One signed result.
AgentGuardian runs as a control plane in the cloud and a data plane inside your environment. Your regulated telemetry, prompts, tool calls, and evidence stays on your side. The eleven-agent swarm runs scans on demand or on a schedule, produces an AIVSS score, and writes a signed evidence pack to your customer-resident storage.
Control Plane
Sees signed manifests only — metadata, never payloads.
- Console
- Tenant management
- Policy authoring
- Dashboards
- Billing
Data Plane
Inside your VPC. Regulated telemetry never leaves.
- Agent discovery
- 11-agent swarm
- Runtime enforcement
- KMS signing
- Audit ledger
- Evidence storage
Target Agents
LangChain, LangGraph, AutoGen, CrewAI, Bedrock, Vertex AI, custom.
- Tool-calling agents
- Memory-bound agents
- A2A flows
- MCP servers
- Custom REST endpoints
What happens during a scan.
Four phases. The swarm discovers your agent, attacks it, scores the result, and emits a signed evidence pack.
Map the attack surface.
Discovery agent traces every tool, memory binding, identity boundary, and framework hook of the target.
Eleven specialists fire in parallel.
Recon, goal-hijack, tool-abuse, privilege, supply-chain, code-exec, memory-poison, A2A, cascade, trust-exploit, drift.
Score on 0–100.
OWASP-aligned scoring. CVSS base metrics combined with ten agentic risk amplification factors.
Sign and emit.
PDF/A-3 + PAdES-LTA, hash-chain anchored, machine-readable JSON sidecar, framework mapping.
From discovery to signed evidence — in one scan.
The artefact your CRO actually wants.
Every AgentGuardian scan produces a signed evidence pack: PDF/A-3 + PAdES-LTA signature, RFC 3161 timestamp, hash-chain anchored, machine-readable JSON sidecar, cross-framework mapping. Hand it to your Internal Audit team. Hand it to your regulator. Hand it to your Board Risk Committee.
- Executive summary
- Agent inventory in scope
- AIVSS risk classification
- OWASP ASI01–10 evaluation results
- Runtime policy decisions
- Approval and exception history
- Cross-framework mapping appendix
- Signature manifest + verification instructions
EP-2026-Q1-0007
Works with the agent frameworks your team already uses.
AgentGuardian connects to any agent that exposes an inference endpoint — first-class support across the frameworks your platform team is already shipping with.
Test your AI agents while you build them.
Glacien releases the eleven-agent adversarial swarm as an open-source Apache 2.0 Python package, free for any developer. Use it locally during build. Run it in CI/CD as a security gate. The same engine powers AgentGuardian Enterprise — so what developers see locally is what the security team sees in the platform.
What developers get.
Free for developers, researchers, and security engineers.
The eleven specialist red-team agents (recon, goal hijack, tool abuse, memory poisoning, supply chain, code execution, A2A, cascade, trust exploit, drift), the AIVSS engine, probes mapped to OWASP ASI01–10 + MITRE ATLAS + CSA Agentic RT, a local UI, and a CI/CD gate.
- Eleven specialist red-team agents
- AIVSS v0.5 scoring engine
- OWASP ASI01–10 + ATLAS probes
- Local single-page UI
- PDF + HTML + JSON + SARIF reports
- CI/CD gate (--fail-under)
$ pip install agent-guardian
$ agent-guardian scan ./my_agent.py
$ agent-guardian serveWhat the platform adds.
Same attack engine. Centralised, governed, evidenced.
The platform doesn't add a different swarm. It adds discovery across your estate, scheduling, runtime enforcement, signed evidence packs, audit log, SSO, and customer-resident deployment around the same eleven-agent core.
- Centralised inventory + discovery
- Scheduled + continuous scans
- Runtime policy enforcement
- SAML SSO · SCIM · MFA · RBAC
- Signed PDF/A-3 evidence packs
- Audit log · exceptions · approvals
- Customer-resident data plane
- AWS Marketplace procurement
Why we open-sourced it: adversarial methodology shouldn't be a black box. Apache 2.0 means anyone can read the code, reproduce a scan, and verify the methodology.
Maps to the frameworks your governance team already uses.
Every Evidence Pack carries a cross-mapping appendix tailored to whatever framework set you operate under — plus your internal audit standard, your board risk policy, and your own AI governance framework if you have one.
AI Frameworks
- EU AI Act
- NIST AI RMF
- ISO/IEC 42001
- ISO/IEC 23894
- CVSS v4.0 + AIVSS v0.5
Security Frameworks
- MITRE ATLAS
- OWASP Agentic Top 10
- OWASP LLM Top 10
- CSA Agentic RT
Regional Regulators
- MAS Singapore
- APRA Australia
- RBI India
- OJK Indonesia
- BNM Malaysia · BSP Philippines
Pick the plan that fits your environment.
All plans include the open-source red-teaming swarm. Move up as agent count and governance scope grow.
For a single team
Running AgentGuardian against pre-production agents.
- Up to 5 agents
- 11-agent adversarial swarm
- AIVSS scoring
- OWASP ASI01–10 + ATLAS tags
- PDF + JSON + SARIF reports
- Slack / email support
For platform & security teams
Running AgentGuardian across multiple production agents.
- Up to 50 agents
- Scheduled + continuous scans
- Runtime policy enforcement
- SAML SSO + SCIM
- Signed PDF/A-3 evidence packs
- Priority support + 99.9% SLA
For enterprise-wide governance
Customer-resident deployment, full audit, multi-team rollout.
- Unlimited agents
- Customer-resident data plane
- SOC 2 Type II
- 7-year immutable audit log
- Dedicated customer-success manager
- AWS Marketplace procurement
All plans include the open-source red-teaming swarm. See full pricing comparison →
Frequently asked questions.
How is AgentGuardian different from a runtime guardrail like Lakera or Prompt Security?
Does AgentGuardian access our prompts, tool calls, or production data?
Which agent frameworks do you support?
How do you produce an AIVSS score?
Can we run AgentGuardian air-gapped or on-premise?
What evidence does the Evidence Pack actually contain?
How does AgentGuardian integrate with our SIEM, SOC, and ticketing tools?
Is the open-source red-teaming swarm the same as the platform's swarm?
Govern the agents your enterprise
is about to depend on.
AI agents are becoming part of business operations, security workflows, customer experience, and regulated decision-making. AgentGuardian helps you discover them, test them, control them, monitor them, and prove they are governed — with adversarial truth, not posture inference.