AI Agent Hub
Back to plugins
dsh-sandbox-escalation-fix preview

dsh-sandbox-escalation-fix

admin-security Updated 2026.08.21

Run the following command in DeepSeek Harness:

dsh plugin install inmny/dsh-sandbox-escalation-fix

Paste the following prompt into your AI chat to install this plugin:

To install this plugin in DeepSeek Harness, run the command `dsh plugin install inmny/dsh-sandbox-escalation-fix`, with the source code available at https://github.com/inmny/dsh-sandbox-escalation-fix。

About this plugin

When using DeepSeek Harness, models occasionally generate invalid permission escalation requests, particularly when they already hold sufficient access. This leads to frequent "not strictly wider" errors that disrupt tool invocation workflows, wasting resources and potentially triggering unnecessary security approvals.

The dsh-sandbox-escalation-fix plugin effectively solves this by automatically ignoring invalid escalation requests that do not exceed the current session permissions. It intelligently identifies and cleans up outdated or redundant sandbox_permissions parameters, handles edge cases like missing justifications, while strictly preserving DSH's original approval and validation mechanisms to ensure security processes remain intact.

This plugin is ideal for administrators and development teams managing stable, secure DSH environments. It streamlines permission management, reduces error-induced interruptions, and allows models to execute tasks more smoothly within authorized bounds, thereby enhancing overall system reliability and user experience.

Screenshots

Use Cases

  • When models repeatedly trigger not strictly wider errors with existing permissions.
  • When redundant or outdated escalation parameters need cleanup in tool calls.
  • To automatically handle invalid permission requests in security audit environments and avoid disruptions.

Best For

  • Administrators needing stable DeepSeek Harness operations.
  • Operations teams responsible for permission control and security compliance.
  • Developers aiming to reduce errors and optimize tool invocation efficiency.