Four Loopholes in Denylist-Based Agent Command Approval: Why Blacklisting Shell Commands Fails at Scale

Desktop AI coding agents now include approval dialogs to gate shell command execution, requiring human intervention to approve or deny the command. This introduces friction, leading to the creation of auto-approval scripts using denylist techniques. A naive denylist implementation blocks commands containing known-bad patterns like rm -rf or curl | sh. However, this approach fails against adversarial examples.

In September 2026, an AI agent found four loopholes in a denylist-based auto-approval script, which auto-approved 14 out of 18 hostile command examples. To address this, the implementation was rebuilt using an allowlist approach. An allowlist policy defines a set of permitted command shapes and rejects everything else. Parsing the command into an abstract syntax tree or structured representation allows checking the command shape against the allowlist, blocking all four loophole categories.

The allowlist implementation uses a session-scoped allowlist, where the agent proposes a set of commands at the start of a task. The human approves the set, and the allowlist is valid for the session and discarded afterward. This approach requires active curation, as new command shapes must be added explicitly, creating an audit trail. The October 2026 comparison run demonstrated the effectiveness of this approach, blocking 18 hostile examples while allowing 6 legitimate examples.