AI Analysis
Final verdict: SUSPICIOUS
The package shows moderate risk due to suspicious maintainer history and low repository activity, despite having no direct evidence of malicious activities such as network calls or shell executions.
- Suspicious maintainer history
- Low repository activity
Per-check LLM notes
- Network: No network calls were detected.
- Shell: Shell execution patterns observed may be related to package functionality but require further investigation to confirm legitimacy.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
- Credentials: No credential harvesting patterns detected, suggesting safe handling of sensitive information.
- Metadata: The package has suspicious maintainer history and low activity in its git repository, indicating potential risk.
Heuristic Checks
Outbound Network Calls
No suspicious network call patterns found
Code Obfuscation
No obfuscation patterns detected
Shell / Subprocess Execution
score 10.0
Found 5 shell execution pattern(s)
try: completed = subprocess.run( _build_cli_command(self.run_options),, flush=True) pytest_rc = subprocess.run( [ sys.executable, "-m",sh=True) combine_rc = subprocess.run( [ sys.executable,..", flush=True) xml_rc = subprocess.run( [ sys.executable, "-m",, flush=True) report_rc = subprocess.run( [sys.executable, "-m", "coverage", "report", f"--rc
Credential Harvesting
No credential harvesting patterns detected
Typosquatting
No typosquatting candidates detected
Registered Email Domain
Email domain looks legitimate: gmail.com>
Suspicious Page Links
All external links appear legitimate
Git Repository History
score 2.5
Git history flags: Repository has zero stars and zero forks
Repository has zero stars and zero forks
Maintainer History
score 4.0
2 maintainer concern(s) found
Author name is missing or very shortAuthor "" appears to have only 1 package on PyPI (new or inactive account)
Known CVE Vulnerabilities
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Use this prompt to build a project with Commuted-Telegraphy
Your task is to develop a captivating mini-app called 'Telegraph Tales' that leverages the Python package 'Commuted-Telegraphy'. This app will serve as a storytelling tool, allowing users to generate brief stories set in the rich and immersive world of the Commuted fiction universe. Hereβs how youβll build it: 1. **Setup**: Begin by installing the 'Commuted-Telegraphy' package. Ensure your environment is equipped with Python 3.x. 2. **User Interface**: Create a simple yet elegant user interface where users can input their desired story parameters such as genre, main character type, setting, and key themes. 3. **Story Generation**: Utilize the 'Commuted-Telegraphy' package to generate a short story based on the user inputs. The package should handle the narrative structure, character development, and thematic elements. 4. **Customization Options**: Offer advanced customization options within the app. Users should be able to tweak aspects like story length, complexity of characters, and inclusion of specific plot twists. 5. **Output Format**: Provide the generated story in multiple formatsβplain text, HTML, and PDF. Allow users to save or share their stories directly from the app. 6. **Feedback Loop**: Implement a feature that allows users to rate their generated stories and provide feedback. Use this data to improve the story generation algorithm over time. 7. **Integration with Social Media**: Enable users to share their stories directly to popular social media platforms like Twitter, Facebook, and Reddit. 8. **Testing and Deployment**: Rigorously test the app to ensure smooth operation and engaging output. Once tested, deploy the app either as a web-based application or a desktop application. This project aims to create an engaging and interactive experience for fans of the Commuted fiction universe, while showcasing the capabilities of the 'Commuted-Telegraphy' package in generating compelling narratives.