AI Analysis
Final verdict: SUSPICIOUS
The package is flagged due to its use of shell=True, which poses a significant security risk. However, there are no indications of malicious intent from other checks.
- High shell risk due to use of shell=True
- Maintainer has only one package, raising some suspicion
Per-check LLM notes
- Network: No network calls detected, which is normal if the package does not require internet access.
- Shell: Use of shell=True can be risky as it may allow execution of arbitrary commands, suggesting potential for misuse.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The maintainer has only one package, which might indicate a new or less active account, raising some suspicion but not conclusive evidence of malice.
Heuristic Checks
Outbound Network Calls
No suspicious network call patterns found
Code Obfuscation
No obfuscation patterns detected
Shell / Subprocess Execution
score 4.0
Found 2 shell execution pattern(s)
-print', capture_output=True, shell=True, text=True) #print(cmddata.stdout) #print(-altr', capture_output=True, shell=True, text=True) print(cmddata.stdout)
Credential Harvesting
No credential harvesting patterns detected
Typosquatting
No typosquatting candidates detected
Registered Email Domain
Email domain looks legitimate: outlook.de
Suspicious Page Links
All external links appear legitimate
Git Repository History
Repository ava007/a9x-webstatistics appears legitimate
Maintainer History
score 2.0
1 maintainer concern(s) found
Author "André von Arx" 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 a9x-webstatistics
Create a web analytics dashboard using the Python package 'a9x-webstatistics'. This application will provide real-time statistics about website traffic, user behavior, and popular pages. The dashboard should allow users to visualize data such as unique visitors, page views, bounce rates, and session durations. Additionally, it should include functionality to filter data by date range, display top visited URLs, and show referral sources. Utilize the 'a9x-webstatistics' package to gather and process the necessary data from a sample website. The application should be built using Flask for the backend and integrate with a frontend framework like React or Vue.js for interactive visualizations. Ensure that the design is user-friendly and the data presentation is clear and insightful.