Medium Risk

send_landing_chat

Reply to a prospect in their landing-page chat. Long-poll on the prospect's side delivers within 3s. Body is plain text up to 2000 chars.

Risk signalsAccepts raw HTML/template content (body)

Part of the Computeback server.

send_landing_chat can modify Computeback 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 send_landing_chat to create or modify resources in Computeback. 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 send_landing_chat 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 Computeback.

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

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

See the full Computeback policy for all 28 tools.

Get this rule live on your own Computeback 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 send_landing_chat 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 send_landing_chat 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 send_landing_chat tool do? +

Reply to a prospect in their landing-page chat. Long-poll on the prospect's side delivers within 3s. Body is plain text up to 2000 chars.. It is categorised as a Write tool in the Computeback MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on send_landing_chat? +

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

What risk level is send_landing_chat? +

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

Can I rate-limit send_landing_chat? +

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

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

send_landing_chat is provided by the Computeback MCP server (@autonomad1/computeback-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Computeback tool call.

Deterministic rules across all 28 Computeback tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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