Access hive shared memory Use when native Task is wrong because you need queen-led collective intelligence — Byzantine-FT consensus, broadcast across many worker agents, shared memory with bounded conflict. For a single subagent, native Task is fine. Pair with swarm_init first to set topology.
AI agents call hive-mind_memory to retrieve information from Ruflo without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The primary described action is 'access' (read) of shared memory, which leans Read. However, the mention of Byzantine-FT consensus, broadcasting to worker agents, and conflict resolution suggests this tool may also write to or modify shared memory state. The description is ambiguous about whether this is read-only or read-write.
From the tool's definition 'Access hive shared memory' — the tool is described as accessing (reading) shared memory; however, 'broadcast across many worker agents' and 'shared memory with bounded conflict' imply potential write/coordination side effects
Attacks that exploit this kind of access
Access hive shared memory Use when native Task is wrong because you need queen-led collective intelligence — Byzantine-FT consensus, broadcast across many worker agents, shared memory with bounded conflict. For a single subagent, native Task is fine. Pair with swarm_init first to set topology. It is categorised as a Read tool in the Ruflo MCP Server, which means it retrieves data without modifying state.
Register the Ruflo MCP server in PolicyLayer and add a rule for hive-mind_memory: 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.
hive-mind_memory 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 hive-mind_memory 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 hive-mind_memory. 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.
hive-mind_memory 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.
hive-mind_memory 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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