AI agents call list_findings to retrieve information from Reptor without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
list_findings retrieves or queries findings data without modifying state, matching the Read category definition. No side effects are expected from listing operations. Severity is low because reading pentest findings, while potentially containing sensitive information, does not enable direct harm through the tool itself—access controls should govern data visibility at the server level.
From the tool's definition Tool name 'list_findings' indicates a retrieval operation. Server context describes it as part of pentest reporting features that wraps the reptor CLI.
Documented attack patterns abuse exactly the kind of access list_findings gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Reptor, and nothing reaches the server without passing your rules. This is the rule we recommend for list_findings:
{
"version": "1",
"default": "deny",
"tools": {
"list_findings": {}
}
}list_findings is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
Free to start. No card required.
list_findings. It is categorised as a Read tool in the Reptor MCP Server, which means it retrieves data without modifying state.
Register the Reptor MCP server in PolicyLayer and add a rule for list_findings: 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 Reptor. Nothing to install.
list_findings 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 list_findings 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 list_findings. 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.
list_findings is provided by the Reptor MCP server (slvnlrt/reptor-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Reptor, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
7 Reptor tools catalogued and risk-classified — across an index of 43,000+ MCP servers.