Universal Agent

This skill should be used when the user needs to execute tasks through a complete automated workflow: understand natural language intent, dynamically generat...

This skill truly executes arbitrary shell commands and generated Python code and thus has high potential impact. Specific points to consider before installing or running: - Metadata mismatch: the registry claims no required env vars, but the script uses an LLM API key (config.json or LLM_API_KEY) for standalone mode and expects UA_* env vars in bridge mode. Ask the publisher to correct the metadata. - Prefer Bridge mode with a trusted external 'brain' (external agent provides UA_* inputs) rather than Standalone mode, unless you fully trust and have reviewed the script. Bridge mode lets you control what code/commands are fed to the executor. - Do not run Standalone mode without reviewing the code yourself. The script will write temp scripts, persist a memory file, and can run arbitrary system/network commands — run it in a sandboxed container with minimal privileges and limited network access. - Do not include secrets or credentials in task descriptions. Remove or rotate any API keys stored in config.json before sharing the environment. - If you need to use it, set command/script timeouts low, leave dangerous_mode = false, and inspect/wipe the memory file regularly. If the publisher can (1) update the registry metadata to declare LLM_API_KEY and describe UA_* env vars explicitly, and (2) provide a clear, auditable safety policy or a hardened execution sandbox mode, my confidence in moving this to benign would increase.

Type: OpenClaw Skill Name: universal-agent Version: 1.0.0 The bundle implements a 'Universal Agent' framework designed to execute arbitrary shell commands and Python scripts based on LLM-generated logic. While the script `universal_agent.py` includes a safety class (`UniversalExecutor`) with regex-based filters for dangerous commands (e.g., `rm -rf`, `format`), the core functionality provides a direct path for Remote Code Execution (RCE) by design. The `SKILL.md` instructions specifically guide the AI agent to use 'Bridge Mode,' which relies on environment variables like `UA_THINK` and `UA_GENERATE_SCRIPT` to drive the execution loop, creating a high-risk surface for prompt injection. Although no explicit evidence of intentional malice or data exfiltration was found, the broad system access and self-fixing code loops represent significant security risks.