Armorer Guard Learning Loop: local live feedback for AI-agent security

Reddit r/AI_Agents Tools
ai-security local-feedback rust agent-safety learning-overlay dev-tool

Summary

Armorer Guard introduces a Rust-native learning overlay for AI-agent security that enables local live feedback without silent cloud upload or model weight mutation, featuring CLI modes for feedback recording and offline retraining.

We just shipped a Rust-native learning overlay for Armorer Guard. The idea: a scanner should be able to adapt from local feedback immediately, without silently mutating model weights or uploading prompts to a cloud service. What changed: - feedback-record / feedback-export / feedback-stats CLI modes - stable scan IDs so teams can review findings without storing raw prompts - local allow / block / review exemplars stored outside the repo - no suppression for credentials, dangerous tool calls, or credential-disclosure policy reasons - reviewed export path for later offline retraining The claim we are trying to make precise is: live local learning, no silent cloud upload, no poisoning-by-default. I am curious how people here would wire this into agent runtimes. Before the tool call? Around MCP/tool results? As a CI gate for agent evals?
Original Article

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