AI Analysis
Final verdict: SAFE
The package shows minimal signs of risk with no detected obfuscation, shell execution, or credential harvesting patterns. The network risk is slightly elevated but typical for legitimate packages performing HTTP requests.
- Low risk scores across all categories
- Elevated metadata risk due to author's inexperience or low effort
Per-check LLM notes
- Network: The observed network patterns are typical for packages that perform HTTP requests and do not inherently indicate malicious activity.
- Shell: No shell execution patterns were detected, indicating no immediate risk from this aspect.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The author has only one package and lacks PyPI classifiers, indicating low effort or inexperience.
Package Quality Overall: Low (2.8/10)
○ Low
Test Suite
1.0
No test suite detected
No test files or test-runner configuration detected
◈ Medium
Documentation
5.0
Some documentation present
Detailed PyPI description (1521 chars)
○ Low
Contributing Guide
2.0
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium
Type Annotations
5.0
Partial type annotation coverage
131 type-annotated function signatures detected in source
○ Low
Multiple Contributors
1.0
Unable to verify contributor count: no GitHub repository found
No GitHub repository linked — contributor count unavailable
Heuristic Checks
Outbound Network Calls
score 7.5
Found 5 network call pattern(s)
e: self._client = httpx.Client( base_url=self._base_url, cocontext manager for internal httpx.Client (see httpx docs)""" self.get_httpx_client().__exit__(self._async_client = httpx.AsyncClient( base_url=self._base_url, coontext manager for underlying httpx.AsyncClient (see httpx docs)""" await self.get_async_httpx_clienten self._client = httpx.Client( base_url=self._base_url, co
Code Obfuscation
No obfuscation patterns detected
Shell / Subprocess Execution
No shell execution patterns detected
Credential Harvesting
No credential harvesting patterns detected
Typosquatting
No typosquatting candidates detected
Registered Email Domain
Email domain looks legitimate: arbi.city>
Suspicious Page Links
All external links appear legitimate
Git Repository History
No GitHub repository linked
No GitHub repository link found
Maintainer History
score 4.0
2 maintainer concern(s) found
Author "arbi-dev" appears to have only 1 package on PyPI (new or inactive account)Package has no PyPI classifiers (low effort / metadata quality)
Known CVE Vulnerabilities
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Use this prompt to build a project with arbi-tr
Create a voice-to-text transcription application using the 'arbi-tr' Python package. This application will allow users to upload audio files and receive accurate transcriptions in real-time. Here’s a detailed breakdown of the application's functionality and features: 1. **User Interface**: Develop a simple and intuitive UI where users can upload their audio files. Ensure the interface supports common audio formats such as MP3, WAV, and FLAC. 2. **File Upload**: Implement a feature that allows users to drag and drop or browse for audio files to upload. 3. **Real-Time Transcription**: Use the 'arbi-tr' package to perform real-time transcription on the uploaded audio file. Display the transcription process progress bar to keep users informed about the status. 4. **Transcription Accuracy Check**: Provide an option for users to manually correct any inaccuracies in the transcription. These corrections should be saved for future reference to improve transcription quality. 5. **Export Transcription**: Allow users to export the final transcription in various formats like plain text, Markdown, or PDF. 6. **History and Favorites**: Maintain a history of all transcriptions performed by the user. Users should also be able to mark certain transcriptions as favorites for quick access. 7. **Integration with Cloud Storage**: Optionally, integrate the application with cloud storage services like Google Drive or Dropbox for easy backup and retrieval of transcriptions. 8. **Notifications**: Send email notifications to users when their transcription is ready or if there are any issues during the transcription process. Utilize the 'arbi-tr' package to handle the core functionality of converting audio to text. Specifically, use its API calls to initiate transcription jobs, retrieve transcription results, and manage errors or retries in case of failures. Additionally, explore how the package can be extended to support multiple languages and dialects for broader usability.