Low Risk

replay_guard_check

Detect replay attacks — identical requests sent multiple times in a time window. Uses SHA256 fingerprint of (agent_id + tool_name + args). Default window: 300 seconds (5 min). Returns is_replay=true/false with duplicate count and first/last seen timestamps.

Part of the Agentguard server.

replay_guard_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 replay_guard_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 replay_guard_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": {
    "replay_guard_check": {}
  }
}

See the full Agentguard policy for all 24 tools.

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 replay_guard_check gives an agent. Each links to the full case and the policy that stops it:

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so replay_guard_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 replay_guard_check tool do? +

Detect replay attacks — identical requests sent multiple times in a time window. Uses SHA256 fingerprint of (agent_id + tool_name + args). Default window: 300 seconds (5 min). Returns is_replay=true/false with duplicate count and first/last seen timestamps.. 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 replay_guard_check? +

Register the Agentguard MCP server in PolicyLayer and add a rule for replay_guard_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 replay_guard_check? +

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

Can I rate-limit replay_guard_check? +

Yes. Add a rate_limit block to the replay_guard_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 replay_guard_check completely? +

Set action: deny in the PolicyLayer policy for replay_guard_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 replay_guard_check? +

replay_guard_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.

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

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