dcl_evaluate_output_sanitizer
FINAL-GATE Output Sanitizer ($0.02). Post-processing checkpoint that strips secrets/credentials, PII, crypto material (seed phrases, private keys, wallet addresses), internal network details (private IPs, MAC addresses, .internal/.local/.corp hostnames), and unsafe shell/SQL/path-traversal fragme...
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What dcl_evaluate_output_sanitizer does on Dcl Trust Oracle
AI agents invoke dcl_evaluate_output_sanitizer to trigger actions in Dcl Trust Oracle. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.
| Parameter | Type | Required | Description |
|---|---|---|---|
agent_id | string | Yes | Identifier of the agent that produced the response. |
response | string | Yes | The raw LLM/agent response to sanitize before it is delivered to a user, downstream agent, or external system. |
Parameters from the server's own tool schema.
Why dcl_evaluate_output_sanitizer is rated High
Actively transforms and filters model output, executing redaction logic with broad data-altering effects.
From the tool's definition strips secrets, PII, crypto material, unsafe shell/SQL fragments
Attacks that exploit this kind of access
The rule that runs dcl_evaluate_output_sanitizer safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Dcl Trust Oracle, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For dcl_evaluate_output_sanitizer, this is the rule to start with:
dcl_evaluate_output_sanitizer stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Dcl Trust Oracle, apply this rule, and every dcl_evaluate_output_sanitizer call is checked against it from then on.
Questions about dcl_evaluate_output_sanitizer
FINAL-GATE Output Sanitizer ($0.02). Post-processing checkpoint that strips secrets/credentials, PII, crypto material (seed phrases, private keys, wallet addresses), internal network details (private IPs, MAC addresses, .internal/.local/.corp hostnames), and unsafe shell/SQL/path-traversal fragments from a raw model response — plus a narrow, high-precision safety net for direct self-harm-instruction-seeking and targeted-harassment phrasing (not a general toxicity classifier). Returns a single sanitized_output with every match replaced by [REDACTED]; use that instead of the original whenever verdict is NO_COMMIT. Run this as the LAST gate before a response reaches its destination — after dcl_evaluate_jailbreak_crypto/other input-side checks have already run, and immediately before dcl_commit seals the final decision. Internally re-uses the same detection tables as dcl_evaluate_secrets/dcl_evaluate_pii for the secrets/PII categories, so results stay consistent with those tools. It is categorised as a Execute tool in the Dcl Trust Oracle MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
dcl_evaluate_output_sanitizer accepts 2 parameters: agent_id, response. Required: agent_id, response. The full parameter table on this page comes from the server's own tool schema.
Register the Dcl Trust Oracle MCP server in PolicyLayer and add a rule for dcl_evaluate_output_sanitizer: 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 Dcl Trust Oracle. Nothing to install.
dcl_evaluate_output_sanitizer is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the dcl_evaluate_output_sanitizer 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 dcl_evaluate_output_sanitizer. 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.
dcl_evaluate_output_sanitizer is provided by the Dcl Trust Oracle MCP server (https://mcp.fronesislabs.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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