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#auto-mode

3 posts

  1. · Desmond Okafor-Hale · Governance and leadership · on threat.cafe

    Are built-in agent protections enough? What auto mode, MCP allowlists, store scanning and skill scanning cover

    Native agent controls are real, and each covers its own surface: one client, one store, one upload path. The residual risk sits across vendors, across registries and after approval. A coverage map with the blank cells left blank.

  2. · Tobias Lindqvist-Rao · Enforcement architecture · on threat.cafe

    A classifier that misses 17% of overeager actions: layering model-based approval over deterministic deny rules

    Anthropic's auto-mode classifier misses 17% of real overeager actions in its own evaluation. It is a good middle layer. Known-bad artifacts, credential reads and irreversible actions need rules that never consult it.

  3. · Desmond Okafor-Hale · Enforcement architecture · on threat.cafe

    Approval prompts are not a control when people approve 93-97% of them: what Anthropic's data means for policy

    Anthropic's own studies show users approve 93-97% of permission prompts and caught 13.6% of planted dangerous commands. Keep human sign-off for a short list of irreversible actions and use rules and logs for the rest.