Medium Risk

dora_metrics_deep_dive

Analyzes DORA metrics (Deployment Frequency, Mean Time to Recovery, Change Failure Rate) with deep correlation to code review patterns. Designed for CTOs to identify bottlenecks in software delivery pipelines. Inputs include GitHub repository identifiers and optional time ranges. Outputs structur...

Part of the Gapup Mcp server.

dora_metrics_deep_dive can modify Gapup Mcp data, with no limits today. PolicyLayer puts allow, deny, and rate-limit rules on every call. Live in minutes.

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AI agents use dora_metrics_deep_dive to create or modify resources in Gapup Mcp. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.

Without a policy, an AI agent could call dora_metrics_deep_dive repeatedly, creating or modifying resources faster than any human could review. PolicyLayer's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach Gapup Mcp.

Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "dora_metrics_deep_dive": {
      "limits": [
        {
          "counter": "dora_metrics_deep_dive_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

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

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

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

What does the dora_metrics_deep_dive tool do? +

Analyzes DORA metrics (Deployment Frequency, Mean Time to Recovery, Change Failure Rate) with deep correlation to code review patterns. Designed for CTOs to identify bottlenecks in software delivery pipelines. Inputs include GitHub repository identifiers and optional time ranges. Outputs structured metrics with trend analysis and code review depth insights.. It is categorised as a Write tool in the Gapup Mcp MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on dora_metrics_deep_dive? +

Register the Gapup MCP server in PolicyLayer and add a rule for dora_metrics_deep_dive: 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 Gapup Mcp. Nothing to install.

What risk level is dora_metrics_deep_dive? +

dora_metrics_deep_dive is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit dora_metrics_deep_dive? +

Yes. Add a rate_limit block to the dora_metrics_deep_dive 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 dora_metrics_deep_dive completely? +

Set action: deny in the PolicyLayer policy for dora_metrics_deep_dive. 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 dora_metrics_deep_dive? +

dora_metrics_deep_dive is provided by the Gapup MCP server (https://mcp.gapup.io/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Gapup Mcp tool call.

Deterministic rules across all 271 Gapup Mcp tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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