AI agents invoke checkpoint_restore to trigger actions in Rr. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
Restoring a checkpoint modifies the live state of a debugging session by rewinding/replaying execution to a prior state. This is an active state-change operation that affects program execution flow, not merely reading data. While it uses a previously saved snapshot (making it somewhat reversible), it triggers an external operation that alters the current execution context — classifying it as Execute.
From the tool's definition Restore a previously created checkpoint, instantly
Attacks that exploit this kind of access
Restore a previously created checkpoint, instantly. It is categorised as a Execute tool in the Rr MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Rr MCP server in PolicyLayer and add a rule for checkpoint_restore: 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.
checkpoint_restore is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the checkpoint_restore 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 checkpoint_restore. 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.
checkpoint_restore 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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