Medium Risk

cross_sell_reco

Recommandations cross-sell — Gapup agent-payable C-suite expertise (CRO). Returns a structured, audited deliverable. Reference case: Alan × Gapup Hub — 3 produits recommandés · Fit 'perfect' × 2 · ARR potentiel +€18k. Inputs are validated server-side — send the documented case fields.

Risk signalsHigh parameter count (13 properties)

Part of the Mcp Knowledge server.

cross_sell_reco can modify Mcp Knowledge 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 cross_sell_reco to create or modify resources in Mcp Knowledge. 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 cross_sell_reco 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 Mcp Knowledge.

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

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

See the full Mcp Knowledge policy for all 271 tools.

Get this rule live on your own Mcp Knowledge 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 cross_sell_reco 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 cross_sell_reco 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 cross_sell_reco tool do? +

Recommandations cross-sell — Gapup agent-payable C-suite expertise (CRO). Returns a structured, audited deliverable. Reference case: Alan × Gapup Hub — 3 produits recommandés · Fit 'perfect' × 2 · ARR potentiel +€18k. Inputs are validated server-side — send the documented case fields.. It is categorised as a Write tool in the Mcp Knowledge MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on cross_sell_reco? +

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

What risk level is cross_sell_reco? +

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

Can I rate-limit cross_sell_reco? +

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

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

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

Enforce policy on every Mcp Knowledge tool call.

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

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