T05 · Unauthorized Access and Privilege Escalation
Error
- Location
- ai_image.py:33
- Finding
- Unrestricted Local File Read and External Upload via Image Tools## Vulnerability Details **File Location**: `ai_image.py`, lines 33–59 **Vulnerability Type**: Arbitrary local file disclosure through unrestricted path input **Risk Level**: High ### Vulnerable Code ```python async def edit_image(self, image_path: str, prompt: str) -> Dict[str, Any]: import requests if not requests: return {"success": False, "error": "requests not available"} url = "https://api.openai.com/v1/images/edits" with open(image_path, "rb") as img: files = {"image": img} data = {"prompt": prompt} try: loop = asyncio.get_event_loop() resp = await loop.run_in_executor(None, lambda: requests.post(url, files=files, data=data, timeout=60)) if resp.status_code == 200: return {"success": True, "url": resp.json().get("data", [{}])[0].get("url")} return {"success": False, "error": "Error"} except Exception as e: return {"success": False, "error": str(e)} async def variations(self, image_path: str, n: int = 1) -> Dict[str, Any]: import requests if not requests: return {"success": False, "error": "requests not available"} url = "https://api.openai.com/v1/images/variations" with open(image_path, "rb") as img: files = {"image": img} data = {"n": n} try: loop = asyncio.get_event_loop() resp = await loop.run_in_executor(None, lambda: requests.post(url, files=files, data=data, timeout=60)) ``` ### Technical Analysis The public `ai_edit_image` and `ai_image_variations` tools accept an arbitrary filesystem path from the caller. That path is passed directly to `open(image_path, "rb")`, and the resulting content is attached to an outbound HTTP request. The implementation does not: - Restrict access to a user-approved media directory. - Canonicalize the path and verify that it ...[truncated 1814 chars]
- Remediation
- ## Remediation Suggestions 1. Restrict file inputs to an explicitly configured, user-approved image directory. 2. Resolve the requested path with `Path.resolve()` and verify that the resolved path is a descendant of the approved directory. 3. Reject symbolic links, non-regular files, device files, and paths containing traversal outside the approved root. 4. Validate content by decoding it with a trusted image library rather than relying on the filename extension or MIME type. 5. Enforce conservative file-size and image-dimension limits before loading or uploading content. 6. Require explicit user confirmation identifying the resolved file and external destination before transmission. 7. Prefer opaque file handles or platform-provided attachment identifiers over caller-controlled filesystem paths. 8. Run the Skill under a sandboxed account with access only to the workspace and approved media files. 9. Add tests covering absolute paths, `..` traversal, symlinks, non-image files, oversized files, and paths outside the permitted directory.