Medium Risk

assign_task

Assign a user to a task by name or email. The user is added to the task's assignees and linked in the knowledge graph.

Part of the ContextLayer server.

assign_task can modify ContextLayer 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 assign_task to create or modify resources in ContextLayer. 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 assign_task 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 ContextLayer.

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

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

See the full ContextLayer policy for all 62 tools.

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

Assign a user to a task by name or email. The user is added to the task's assignees and linked in the knowledge graph.. It is categorised as a Write tool in the ContextLayer MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on assign_task? +

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

What risk level is assign_task? +

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

Can I rate-limit assign_task? +

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

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

assign_task is provided by the ContextLayer MCP server (https://api.dotnova.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 ContextLayer tool call.

Deterministic rules across all 62 ContextLayer 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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