save partial findings for later use (like open ports, used protocols, versions etc.) if finding data is too long or already exists in another file dont save it
AI agents use save_partial_finding to create or update resources in PentestMCP — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your PentestMCP environment.
An AI agent can call save_partial_finding faster than any human can review — one bad instruction and it creates or modifies resources in PentestMCP by the hundred, each call as confident as the last.
Attacks that exploit this kind of access
save partial findings for later use (like open ports, used protocols, versions etc.) if finding data is too long or already exists in another file dont save it. It is categorised as a Write tool in the PentestMCP MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Pentest MCP server in PolicyLayer and add a rule for save_partial_finding: 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 PentestMCP. Nothing to install.
save_partial_finding is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the save_partial_finding 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 save_partial_finding. 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.
save_partial_finding is provided by the Pentest MCP server (youssefsahnoun/pentestmcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.