Call this before routing traffic, bidding on inventory, or trusting a counterparty. It fuses ALL THREE TunnelMind lenses for one subject — Scry (attacker intelligence + threat feeds + open ports), Sigil (ad-supply-chain position + trust score + ATAP witness count), and Tracker (DDG/IAB catalog + ...
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AI agents call profile_entity to retrieve information from TunnelMind Data API 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_entity 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.
{
"version": "1",
"default": "deny",
"tools": {
"profile_entity": {}
}
} See the full TunnelMind Data API policy for all 54 tools.
These attack patterns abuse exactly the kind of access profile_entity gives an agent. Each links to the full case and the policy that stops it:
Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.
Call this before routing traffic, bidding on inventory, or trusting a counterparty. It fuses ALL THREE TunnelMind lenses for one subject — Scry (attacker intelligence + threat feeds + open ports), Sigil (ad-supply-chain position + trust score + ATAP witness count), and Tracker (DDG/IAB catalog + prevalence + categories) — into a single confidence-scored profile plus a signed P38 receipt. The cross_lens.hits field tells you if the same infrastructure appears in attack data AND supply-chain data — that's your highest-confidence signal, and the one no siloed competitor can give you. cross_lens.flags surfaces the actionable highlights (cross_lens_overlap:scry+sigil, in_threat_intel:..., high_prevalence_tracker, corroborated_by_N_lenses). Confidence weighting: each lens contributes a base score; a 1.5× multiplier applies when ≥2 lenses corroborate the same subject; and the Scry contribution is weighted by the attestation tier of the sensors that observed it (silicon_root 1.0 → self_asserted 0.5). Bounded [0,1] and carried into the receipt. Unlike cross_lens_verify (one node → one verdict) and cross_lens_lookup (one node → raw three-lens view), profile_entity takes the SUBJECT as any combination of ip / domain / entity and returns the richest fused detail for a pre-transaction decision. At least one of ip / domain / entity is required.. It is categorised as a Read tool in the TunnelMind Data API MCP Server, which means it retrieves data without modifying state.
Register the TunnelMind Data API MCP server in PolicyLayer and add a rule for profile_entity: 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 TunnelMind Data API. Nothing to install.
profile_entity is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the profile_entity 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.
Set action: deny in the PolicyLayer policy for profile_entity. 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.
profile_entity is provided by the TunnelMind Data API MCP server (https://mcp-data.tunnelmind.ai/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 54 TunnelMind Data API tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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