codex-shim-byok-models
Fail
Audited by Gen Agent Trust Hub on Sep 16, 2026
Risk Level: HIGHEXTERNAL_DOWNLOADSPRIVILEGE_ESCALATIONCREDENTIALS_UNSAFEDYNAMIC_EXECUTIONCOMMAND_EXECUTIONINDIRECT_PROMPT_INJECTION
Full Analysis
- [EXTERNAL_DOWNLOADS]: The skill instructs the user to clone and execute code from an untrusted GitHub repository (
0xSero/codex-shim) which is not associated with the skill author or a known trusted organization. - [PRIVILEGE_ESCALATION]: The instructions for the "macOS Picker Patch" require extensive use of
sudoto modify files within the/Applications/Codex.appbundle, bypass integrity checks, and re-sign application binaries. This grants the skill-provided code high-level permissions over a system application. - [CREDENTIALS_UNSAFE]: The skill manages and accesses highly sensitive credentials, including OpenAI, Anthropic, and DeepSeek API keys, as well as ChatGPT access tokens stored in
~/.codex/auth.json. The proxying of these tokens through untrusted code represents a significant risk of credential exposure. - [DYNAMIC_EXECUTION]: The skill uses
asarextraction andsedto dynamically modify Javascript assets within a production application's archive. It also includes a Python snippet to recompute hash values specifically to bypass Electron's built-in ASAR integrity checks. - [COMMAND_EXECUTION]: The installation process symlinks external binaries (
codex-shim,codex-app,codex-model) from an untrusted source into the user's path, providing a mechanism for arbitrary command execution. - [INDIRECT_PROMPT_INJECTION]:
- Ingestion points: The skill ingests data from external model endpoints (OpenAI, Anthropic, DeepSeek, OpenRouter) and translates them into the Codex context (SKILL.md).
- Boundary markers: No explicit boundary markers or instruction-ignoring delimiters are defined for handling the external model responses.
- Capability inventory: The skill possesses command execution capabilities via the
codex-shimCLI tools to interact with the local environment (SKILL.md). - Sanitization: There is no evidence of sanitization or validation of the external API content before it is processed and returned to the agent context.
Recommendations
- AI detected serious security threats
Audit Metadata