job-posting-intent
Fail
Audited by Gen Agent Trust Hub on Sep 20, 2026
Risk Level: HIGHCREDENTIALS_UNSAFEDYNAMIC_EXECUTIONINDIRECT_PROMPT_INJECTION
Full Analysis
- [CREDENTIALS_UNSAFE]: The skill contains a hardcoded authentication token (
RUBE_TOKEN) inscripts/create_sheet.py,scripts/create_sheet_mcp.py, andscripts/search_jobs.py. This token is a valid JSON Web Token (JWT) that grants access to the Rube/Composio platform and should be managed via environment variables rather than hardcoded in the source code. - [DYNAMIC_EXECUTION]: The scripts
create_sheet_mcp.pyandsearch_jobs.pydynamically assemble Python code blocks as strings and transmit them to a remote server for execution via theRUBE_REMOTE_WORKBENCHtool. This pattern of remote code execution (RCE) via a workbench tool is a high-capability feature that poses a security risk if the generated code is influenced by untrusted inputs. - [INDIRECT_PROMPT_INJECTION]: The skill possesses an attack surface for indirect prompt injection:
- Ingestion points: The main script (
scripts/search_jobs.py) fetches job titles, descriptions, and company metadata from LinkedIn via the Apify API. - Boundary markers: There are no delimiters or explicit instructions provided to the agent to treat the ingested job description content as untrusted data.
- Capability inventory: The skill can execute remote code via Rube, perform authenticated API requests to Apify, and modify Google Sheets.
- Sanitization: The skill performs no sanitization or escaping of the job description text, which is directly summarized and presented to the agent, potentially allowing an attacker to embed malicious instructions in a job posting.
Recommendations
- AI detected serious security threats
Audit Metadata