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stack_safety_verdict

Costs 1 credit ($0.02). The signed deploy gate for an AI software stack (up to 10 packages): the overall BLOCK / HOLD / PASS / UNKNOWN gate and a per-package verdict, fusing the ingested AI-stack CVE batch with the CISA KEV catalog, plus the matched-CVE evidence and an AFTA-signed receipt. Versus...

Part of the TensorFeed server.

stack_safety_verdict can trigger actions in TensorFeed, with no limits today. PolicyLayer puts allow, deny, and rate-limit rules on every call. Live in minutes.

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AI agents invoke stack_safety_verdict to trigger processes or run actions in TensorFeed. Execute operations can have side effects beyond the immediate call -- triggering builds, sending notifications, or starting workflows. Rate limits and argument validation are essential to prevent runaway execution.

stack_safety_verdict can trigger processes with real-world consequences. An uncontrolled agent might start dozens of builds, send mass notifications, or kick off expensive compute jobs. PolicyLayer enforces rate limits and validates arguments to keep execution within safe bounds.

Execute tools trigger processes. Rate-limit and validate arguments to prevent unintended side effects.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "stack_safety_verdict": {
      "limits": [
        {
          "counter": "stack_safety_verdict_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

See the full TensorFeed policy for all 79 tools.

Get this rule live on your own TensorFeed server in minutes. PolicyLayer enforces it on every call, before it runs.

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View all 79 tools →

These attack patterns abuse exactly the kind of access stack_safety_verdict gives an agent. Each links to the full case and the policy that stops it:

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so stack_safety_verdict only ever does what you allow.

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Other execute tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.

What does the stack_safety_verdict tool do? +

Costs 1 credit ($0.02). The signed deploy gate for an AI software stack (up to 10 packages): the overall BLOCK / HOLD / PASS / UNKNOWN gate and a per-package verdict, fusing the ingested AI-stack CVE batch with the CISA KEV catalog, plus the matched-CVE evidence and an AFTA-signed receipt. Versus the free stack_safety_verdict_preview it adds the matched-CVE ids, affected ranges, fixed versions, and KEV status per package, raises the cap to 10 packages, and ships the receipt, with no rate limit. Never-false-confirm: BLOCK only on exploited with no fix. Get credits at tensorfeed.ai/developers/agent-payments. Strict premium, no free trial.. It is categorised as a Execute tool in the TensorFeed MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on stack_safety_verdict? +

Register the TensorFeed MCP server in PolicyLayer and add a rule for stack_safety_verdict: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches TensorFeed. Nothing to install.

What risk level is stack_safety_verdict? +

stack_safety_verdict is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit stack_safety_verdict? +

Yes. Add a rate_limit block to the stack_safety_verdict rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.

How do I block stack_safety_verdict completely? +

Set action: deny in the PolicyLayer policy for stack_safety_verdict. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.

What MCP server provides stack_safety_verdict? +

stack_safety_verdict is provided by the TensorFeed MCP server (https://mcp.tensorfeed.ai/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every TensorFeed tool call.

Deterministic rules across all 79 TensorFeed tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

Free to start. No card required.

4,600+ MCP servers and 31,000+ tools scanned and risk-classified.

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