Medium Risk

update_agent_policy

Create or update a policy/guardrail for an agent. Policy types: • brand_safety - Content must align with brand guidelines • platform_compliance - Must follow platform ad policies • approval_gate - Require human approval before execution • budget_limit - Cap spending or resource usage • content_fi...

Part of the SendIt server.

update_agent_policy can modify SendIt 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 update_agent_policy to create or modify resources in SendIt. 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 update_agent_policy 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 SendIt.

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

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

See the full SendIt policy for all 148 tools.

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These attack patterns abuse exactly the kind of access update_agent_policy 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 update_agent_policy 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 update_agent_policy tool do? +

Create or update a policy/guardrail for an agent. Policy types: • brand_safety - Content must align with brand guidelines • platform_compliance - Must follow platform ad policies • approval_gate - Require human approval before execution • budget_limit - Cap spending or resource usage • content_filter - Filter certain topics or language. It is categorised as a Write tool in the SendIt MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on update_agent_policy? +

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

What risk level is update_agent_policy? +

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

Can I rate-limit update_agent_policy? +

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

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

update_agent_policy is provided by the SendIt MCP server (https://sendit.infiniteappsai.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every SendIt tool call.

Deterministic rules across all 148 SendIt tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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