Protective check on outbound responses — catches system prompt leaks, unexpected PII, or topic drift before delivery, so what you ship matches what you meant. Call this AFTER the LLM generates a response, BEFORE returning it to the user or downstream system. DECISION LOGIC: - If blocked=true: do ...
Risk signalsHandles credentials or secrets (pii_tokens[].token) · High parameter count (10 properties)
Part of the Shrike Security server.
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AI agents call scan_response to retrieve information from Shrike Security 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 scan_response 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": {
"scan_response": {}
}
}See the full Shrike Security policy for all 12 tools.
These attack patterns abuse exactly the kind of access scan_response 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.
Protective check on outbound responses — catches system prompt leaks, unexpected PII, or topic drift before delivery, so what you ship matches what you meant. Call this AFTER the LLM generates a response, BEFORE returning it to the user or downstream system. DECISION LOGIC: - If blocked=true: do NOT deliver the response. Regenerate with a modified prompt or return the user_message as a safe fallback. - If blocked=false: the response is safe to deliver. Detects in LLM output: - System prompt leaks (LLM revealing its instructions) - Unexpected PII in output (PII not present in the original prompt) - Toxic or hostile language in generated content - Topic drift (response diverges from prompt intent) Provide original_prompt for best results — it enables PII diff analysis and topic mismatch detection. When pii_tokens is provided (from scan_prompt with redact_pii=true), safe responses include rehydrated_response with PII tokens restored. Enterprise context: Paired with scan_prompt, this completes the inbound/outbound scan pattern that prevents data exfiltration through model outputs and ensures compliance with data handling policies. ERROR HANDLING: If this tool returns an error or is unavailable, default to BLOCKING the response. Do NOT deliver unscanned LLM output.. It is categorised as a Read tool in the Shrike Security MCP Server, which means it retrieves data without modifying state.
Register the Shrike Security MCP server in PolicyLayer and add a rule for scan_response: 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 Shrike Security. Nothing to install.
scan_response 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 scan_response 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 scan_response. 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.
scan_response is provided by the Shrike Security MCP server (shrike-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 12 Shrike Security tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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