Fabraix Red Team Playground
Free · Open source
AI security researchers
An agent that processes refunds, grants access, or deploys to production without a policy check is one bad input away from an incident — and most agent frameworks give you no enforcement layer between 'the model decided' and 'the action fired.' Stacksona sits at that gap.
Stacksona is a runtime governance layer that intercepts agent tool calls before execution and evaluates them against rules derived from your existing policies. Safe actions pass through automatically, policy violations are rejected outright, and edge cases — the $2,400 refund that needs a manager, the data export that requires sign-off — pause the workflow at that specific action while the rest of the agent state is preserved. The integration surface is real: JavaScript SDK, an MCP server, an n8n node, and a decision API, so it attaches to the agent stack you already run rather than replacing it. The ceiling appears when your policy logic requires context the governance layer cannot resolve autonomously — at that point, human review queues grow and the throughput advantage of automation narrows.
Bottom line: Pick this when you need to operationalize a refund or approval policy against live agent actions without rebuilding your stack — but plan for review queue management when edge-case volume scales beyond what a small ops team can clear in real time.
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Free · Open source
AI security researchers
Freemium
Legal professionals handling confidential cases
An agent that processes refunds, grants access, or deploys to production without a policy check is one bad input away from an incident — and most agent frameworks give you no enforcement layer between ‘the model decided’ and ‘the action fired.’ Stacksona sits at that gap.
Stacksona is a runtime governance layer that intercepts agent tool calls before execution and evaluates them against rules derived from your existing policies. Safe actions pass through automatically, policy violations are rejected outright, and edge cases pause the workflow at that specific action while the rest of the agent state is preserved. The vendor states this converts plain-language policy documents into enforceable runtime rules.
The integration surface includes a JavaScript SDK, an MCP server, an n8n node, and a decision API, so it attaches to the agent stack you already run rather than replacing it. A 14-day free trial is available.
Teams apply it to refunds and customer operations, finance and procurement approvals, access and permission changes, production deployments and exports, and sensitive data handling.
Every decision, policy result, and outcome is retained as evidence for audit trails. Selective pause at the specific action that crosses a review threshold keeps routine work automatic. No self-hosted deployment option exists, so teams under data residency rules or in air-gapped environments cannot use it. Review queue throughput depends on human reviewer availability and creates backlogs during spikes.
Best for teams needing policy enforcement for agent actions, organizations with existing policies to operationalize, workflows requiring selective human oversight, and audit and compliance tracking of decisions. Skip it if you require self-hosted options or guaranteed review SLAs during volume spikes.
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