Low Risk

profile_time

CPU time (bottleneck) profile from a .jfr file. Uses bottom-up aggregation: each method is counted in every sample where it appears in the stack, including time spent in callees. Returns methods consuming the most CPU time. Use when the goal is to find performance bottlenecks and slow code paths.

Risk signalsAccepts file system path (filepath) · Bulk/mass operation — affects multiple targets

Part of the Javaperf server.

profile_time is read-only, but an agent in a loop can still rack up calls and cost. PolicyLayer caps every call before it runs. Live in minutes.

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AI agents call profile_time to retrieve information from Javaperf without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.

Even though profile_time only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.

Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "profile_time": {}
  }
}

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

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These attack patterns abuse exactly the kind of access profile_time 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 profile_time only ever does what you allow.

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Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.

What does the profile_time tool do? +

CPU time (bottleneck) profile from a .jfr file. Uses bottom-up aggregation: each method is counted in every sample where it appears in the stack, including time spent in callees. Returns methods consuming the most CPU time. Use when the goal is to find performance bottlenecks and slow code paths.. It is categorised as a Read tool in the Javaperf MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on profile_time? +

Register the Javaperf MCP server in PolicyLayer and add a rule for profile_time: 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 Javaperf. Nothing to install.

What risk level is profile_time? +

profile_time is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit profile_time? +

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

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

profile_time is provided by the Javaperf MCP server (javaperf). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Javaperf tool call.

Deterministic rules across all 26 Javaperf tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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

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