nerv-break-gpt-jailbreak-framework
Fail
Audited by Gen Agent Trust Hub on Sep 16, 2026
Risk Level: HIGHPROMPT_INJECTIONCOMMAND_EXECUTIONPERSISTENCEEXTERNAL_DOWNLOADSREMOTE_CODE_EXECUTIONDYNAMIC_EXECUTIONINDIRECT_PROMPT_INJECTION
Full Analysis
- [PROMPT_INJECTION]: The skill is explicitly designed to bypass AI safety guidelines and model refusals. It uses a "Context Reconstruction" technique via the
bridge.mdsystem prompt to map sensitive operations to benign terms, attempting to evade intent classification. Additionally, it employs a "Real-Time Tamper Engine" with regex rules to intercept and replace model refusal responses with enforced execution directives. - [COMMAND_EXECUTION]: The framework includes
mcp_server.py, which executes arbitrary shell commands usingsubprocess.run(shell=True). The commands are constructed by replacing placeholders in a JSON-defined template with arguments provided at runtime, which is a high-risk pattern for command injection. - [PERSISTENCE]: The
deploy.pyscript automates the modification of the local~/.codex/config.tomlfile to persistently inject the "NERV-BREAK" jailbreak prompt into the system prompts of the Codex CLI environment. This ensures the bypass mechanism is automatically applied to future sessions. - [EXTERNAL_DOWNLOADS]: The installation instructions require cloning a repository from an untrusted source (
github.com/zxwn) and installing unverified dependencies viapip install -r requirements.txt. - [REMOTE_CODE_EXECUTION]: The skill facilitates the execution of external code by directing the user to run a batch script (
lab.bat) and multiple Python scripts (proxy_relay.py,deploy.py) downloaded from a remote repository. - [DYNAMIC_EXECUTION]: The proxy relay and MCP server components dynamically assemble executable strings and logic at runtime. The
mcp_server.pyspecifically uses a dynamic lookup and execution model for security tools based on a local configuration file. - [INDIRECT_PROMPT_INJECTION]: The skill is vulnerable to indirect prompt injection due to its architecture.
- Ingestion points: Data enters the system via the
proxy_relay.pyendpoint and tool arguments inmcp_server.py. - Boundary markers: No delimiters or instructions to ignore embedded commands are present in the processing scripts.
- Capability inventory: The skill has access to network operations (Flask proxy, requests), file system writes (
deploy.py,save_memory), and arbitrary shell execution (mcp_server.py). - Sanitization: There is no evidence of input validation, escaping, or sanitization before data is passed to the shell or interpolated into system prompts.
Recommendations
- AI detected serious security threats
Audit Metadata