AI Analysis
The package exhibits a moderate level of risk due to its potential for retrieving external resources and the novelty of the author's PyPI account. These factors warrant caution but do not conclusively indicate malicious intent.
- Potential retrieval of external resources
- Author has only one package on PyPI
Per-check LLM notes
- Network: The detected network call pattern suggests the package may be retrieving external resources, which is not inherently malicious but requires further investigation to ensure it's legitimate.
- Shell: No shell execution patterns were detected, indicating a low risk of direct system command execution.
- Metadata: The author has only one package on PyPI, which may indicate a new or less active account, but no other suspicious activities were detected.
Package Quality Overall: Low (1.6/10)
No test suite detected
No test files or test-runner configuration detected
No documentation detected
No documentation URL, doc files, or meaningful description found
No contributing guide or governance files found
Development Status classifier >= Beta
No type annotations detected
No type annotations, py.typed marker, or stub files detected
Unable to verify contributor count: no GitHub repository found
No GitHub repository linked — contributor count unavailable
Heuristic Checks
Found 1 network call pattern(s)
ball_url}...') try: urllib.request.urlretrieve(tarball_url, archive_name_local) except Exce
No obfuscation patterns detected
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
Email domain looks legitimate: tensorflow.org
All external links appear legitimate
No GitHub repository linked
No GitHub repository link found
1 maintainer concern(s) found
Author "Google AI Edge Authors" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a real-time object detection and classification mini-app using the 'ai-edge-litert-sdk-mediatek-nightly' package. This app will run on a device equipped with a MediaTek chip that supports AI Edge LiteRT technology. Your task is to develop an application that captures video from the device's camera, processes each frame to detect and classify objects in real-time, and then displays these detections on top of the live video feed. Additionally, the application should have the following features: 1. User-friendly interface to start/stop the video capture and detection process. 2. Ability to save detected frames to disk for later analysis. 3. A settings menu where users can adjust parameters like confidence threshold and detection classes. 4. Logging of detection results for debugging and performance analysis. To achieve this, you'll need to utilize the 'ai-edge-litert-sdk-mediatek-nightly' package to load a pre-trained model, perform inference on the input video stream, and interpret the output to draw bounding boxes around detected objects along with their labels and confidence scores. The application should demonstrate the efficiency and accuracy of AI Edge LiteRT in real-world scenarios.