Low Risk

secret_exposure_check

Deep scan any text/payload for secrets, credentials, and PII. Detects: API keys (OpenAI, GitHub, AWS), tokens (Slack, Bearer), private keys (ETH, Bitcoin), credentials (passwords, secrets), and PII (emails, credit cards, SSNs). Returns findings with severity and remediation guidance.

Risk signalsAccepts raw HTML/template content (payload)

Part of the Agentguard server.

secret_exposure_check is read-only, but an agent in a loop can still rack up calls and cost. PolicyLayer caps every call before it runs. Live in minutes.

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AI agents call secret_exposure_check to retrieve information from Agentguard 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 secret_exposure_check 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.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "secret_exposure_check": {}
  }
}

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Get this rule live on your own Agentguard 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 secret_exposure_check 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 secret_exposure_check only ever does what you allow.

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Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.

What does the secret_exposure_check tool do? +

Deep scan any text/payload for secrets, credentials, and PII. Detects: API keys (OpenAI, GitHub, AWS), tokens (Slack, Bearer), private keys (ETH, Bitcoin), credentials (passwords, secrets), and PII (emails, credit cards, SSNs). Returns findings with severity and remediation guidance.. It is categorised as a Read tool in the Agentguard MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on secret_exposure_check? +

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

What risk level is secret_exposure_check? +

secret_exposure_check is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit secret_exposure_check? +

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

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

secret_exposure_check is provided by the Agentguard MCP server (https://feedoracle.io/guard-oracle/mcp/). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Agentguard tool call.

Deterministic rules across all 24 Agentguard tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

Free to start. No card required.

4,600+ MCP servers and 31,000+ tools scanned and risk-classified.

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