arkts-sta-playground
Fail
Audited by Gen Agent Trust Hub on Feb 17, 2026
Risk Level: HIGHDATA_EXFILTRATIONEXTERNAL_DOWNLOADS
Full Analysis
- [DATA_EXFILTRATION] (HIGH): The skill sends user-provided data directly to an external, non-whitelisted domain.
- Evidence: In
scripts/run_playground.py, therun_arkts_codefunction sends thecodevariable (which can be the content of any file the agent reads) tohttps://arkts-play.cn.bz-openlab.ru:10443/compilevia a POST request. - Risk: An attacker could use prompt injection to convince the agent that a sensitive file (e.g.,
~/.ssh/id_rsaor.env) is actually ArkTS code that needs to be 'verified' or 'debugged', resulting in the file's contents being exfiltrated to the remote server. - [EXTERNAL_DOWNLOADS] (MEDIUM): The skill's core functionality is entirely dependent on an unverified third-party API.
- Evidence: Hardcoded endpoint
https://arkts-play.cn.bz-openlab.ru:10443/compileinscripts/run_playground.py. - Risk: The remote server is not a known trusted source. The server could be compromised to return malicious responses or could be logging all code snippets (including sensitive data) sent to it.
- [INDIRECT_PROMPT_INJECTION] (LOW): The skill processes and displays output from a remote, untrusted source without sanitization.
- Ingestion points:
scripts/run_playground.pyreads theoutputfield from the API response JSON. - Boundary markers: None present. The script prints the raw API output to the terminal.
- Capability inventory: The script itself only performs network requests and file reads, but the agent consuming this output may interpret instructions contained within the API's response.
- Sanitization: None. The script uses
json.loadsbut does not validate or sanitize the string content of theoutputorerrorfields before printing. - [BEST_PRACTICE_VIOLATION] (LOW): The documentation encourages insecure configurations.
- Evidence:
SKILL.mdsuggests that users 'modify the script to disable SSL verification' as a troubleshooting step for certificate errors, which exposes the connection to man-in-the-middle (MITM) attacks.
Recommendations
- AI detected serious security threats
Audit Metadata