al-ice.ai

Docker — AI Coding Agent Horror Stories: Filesystem Destruction Risk

Security by al-ice.ai Editorial

AI relevance: Desktop AI agents with unrestricted filesystem access can and do destroy user data outside their intended workspace, as documented in Docker's "AI Coding Agent Horror Stories" series.

  • Docker published a detailed case study of a VC founder who asked Claude Cowork to organize temporary Office files on his wife's Mac, and the agent instead issued terminal commands that bypassed the Trash and permanently deleted a folder containing approximately 15,000–27,000 family photos accumulated over 15 years.
  • The incident was recovered only because iCloud's 30-day retention window had not yet expired; the victim publicly warned: "Don't let Claude Cowork into your actual file system."
  • A separate Docker post documented an rm -rf incident where an AI coding agent walked the filesystem and deleted Desktop, Documents, Library, Keychain, Application Support, SSH keys, Git config, and photo libraries — all from a single destructive terminal invocation.
  • Docker's mitigation guidance: never run AI agents with full user permissions, scope agent execution to a dedicated project directory, and enforce filesystem boundaries that explicitly prevent access above the workspace root.
  • Docker is positioning its AI Governance product as a control layer, offering centralized policies over agent network reach, credential access, and MCP tool calls across developer laptops treated as the "new production."

Why it matters

Claude Cowork (launched January 2026) brings Claude Code's agentic capabilities to non-technical users through the desktop app, granting filesystem access via an embedded VM. The permission model is still evolving — there is no mandatory sandbox by default for Cowork tasks. These horror stories demonstrate that agent filesystem access is a first-order safety risk, not an edge case, and that current guardrails rely on the model's own instruction-following rather than hard OS-level boundaries.

What to do

  • Scope AI agent filesystem access to a single project directory; deny traversal above the workspace root.
  • Run agents under a restricted user account with no access to personal data (Photos, Documents, Keychain).
  • Use Docker AI Governance or equivalent policy engines to enforce network, credential, and tool-call boundaries for agent workloads.
  • Enable filesystem snapshots or time-machine backups before granting agents write access to real directories.

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