Save current session state Use when native conversation memory is wrong because you need durable cross-session state — restoring agent definitions, swarm topology, memory store, breaker history. For in-session continuation only, no tool needed. Pair with session_save before exiting and session_re...
AI agents use session_save to create or update resources in Ruflo — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Ruflo environment.
This tool creates or modifies persisted session data, which is a Write operation. The state being saved includes agent definitions and swarm topology that could affect subsequent agent behavior. Severity is medium because while the operation is reversible (session state can be overwritten), improper saves could corrupt agent coordination or leave the system in an inconsistent state.
From the tool's definition Tool description states 'Save current session state' and mentions 'restoring agent definitions, swarm topology, memory store, breaker history.' The verb 'save' and the explicit purpose of persisting state indicates data creation/modification.
Attacks that exploit this kind of access
Save current session state Use when native conversation memory is wrong because you need durable cross-session state — restoring agent definitions, swarm topology, memory store, breaker history. For in-session continuation only, no tool needed. Pair with session_save before exiting and session_restore on resume. It is categorised as a Write tool in the Ruflo MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Ruflo MCP server in PolicyLayer and add a rule for session_save: 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 Ruflo. Nothing to install.
session_save 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 session_save 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 session_save. 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.
session_save is provided by the Ruflo MCP server (ruvnet/ruflo). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
session_save is one line of Ruflo's registry record.
The record carries the whole server: verified identity, auth posture, risk grade, every tool classified, recommended policy — re-checked continuously.
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