AI agents use catch to create or update resources in Rr — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Rr environment.
This tool creates a new catchpoint in the debugger session, which is a write/configuration action (modifying debugger state). It does not execute code, delete data, or involve finances. It is reversible as catchpoints can be removed. Severity is medium because misconfiguration could disrupt a debugging session but has limited blast radius beyond the debug environment.
From the tool's definition Set a catchpoint to break on C++ exceptions or syscalls
Attacks that exploit this kind of access
Set a catchpoint to break on C++ exceptions or syscalls. It is categorised as a Write tool in the Rr MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Rr MCP server in PolicyLayer and add a rule for catch: 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 Rr. Nothing to install.
catch 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 catch 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 catch. 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.
catch is provided by the Rr MCP server (jnjaeschke/rr-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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