AI Analysis
Final verdict: SUSPICIOUS
The package shows some unusual behaviors such as network calls to external services and moderate obfuscation techniques, which raise concerns about its true intentions.
- Unusual network calls
- Moderate obfuscation techniques
Per-check LLM notes
- Network: The observed network calls to external services like Play Store and APK Mirror seem unusual but could be part of the package's functionality, unless there is a clear misuse of user data.
- Shell: No shell execution patterns were detected.
- Obfuscation: The use of base64 decoding and json parsing may indicate an attempt to obfuscate data processing logic, but without further context, it's hard to determine if this is malicious.
- Credentials: No clear patterns of credential harvesting are present, reducing the likelihood of malicious intent related to secret theft.
- Metadata: The maintainer has an incomplete profile and a new account with only one package, which could indicate potential risk.
Heuristic Checks
Outbound Network Calls
score 9.0
Found 6 network call pattern(s)
ession self.session = requests.Session() self.session.headers.update(headers) if prPlay Store response = requests.get( url="https://play.google.com/store/apps/detailsAPK Mirror response = requests.get( url=( "https://www.apkmirror.cooption. """ session = requests.Session() # End time for checking response endtime = round(Defaults to None. """ requests.post( url="https://ntfy.sh/", json={_tag).decode() response = requests.post( url=f"{URL}/shorten", json={"blob": blob},
Code Obfuscation
score 4.0
Found 2 obfuscation pattern(s)
challenge_data = json.loads(base64.b64decode(challenge_token)) # Parse originKey origin_oads( base64.b64decode(three_ds2_result_base64).decode() )
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: peterschwps.com>
Suspicious Page Links
All external links appear legitimate
Git Repository History
Repository peterschwps/TooGoodToGo-CLI appears legitimate
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 TGTG-CLI
Create a fully-functional mini-app that allows users to monitor 'Too Good To Go' deals using the TGTG-CLI package. This app should enable users to set up alerts for specific stores and deal types, automatically checking for new deals at predefined intervals. Additionally, the app should allow users to reserve a deal directly from the command line interface if it meets their criteria. Hereβs a step-by-step guide on how to develop this application: 1. **Setup**: Begin by installing the TGTG-CLI package and setting up your environment. Ensure you have the necessary credentials (email and password) to authenticate with the 'Too Good To Go' service. 2. **User Interface**: Design a simple and intuitive command-line interface where users can input their preferences such as preferred store locations, deal categories, and alert settings. 3. **Deal Monitoring**: Implement functionality to continuously monitor 'Too Good To Go' for new deals based on user preferences. Use TGTG-CLI to fetch data and filter deals according to the specified criteria. 4. **Alert System**: Develop an alert system that notifies users via email or SMS when a deal matching their preferences becomes available. Utilize external services like Twilio for SMS notifications and SMTP for emails. 5. **Reservation Functionality**: Add a feature that allows users to reserve a deal directly from the command line interface once a suitable deal is found. Ensure that the reservation process is handled securely and efficiently. 6. **Configuration Management**: Provide options for users to save their preferences and configurations persistently. This could involve storing settings in a local file or database. 7. **Testing and Documentation**: Thoroughly test the application to ensure all features work as expected. Document the setup process, usage instructions, and troubleshooting tips for other developers or users. Suggested Features: - Customizable alert frequency and methods (e.g., email, SMS) - Ability to track multiple stores simultaneously - Support for filtering deals by category, price range, or distance - Option to receive historical deal data for analysis - User-friendly error handling and informative feedback messages By following these steps and incorporating the suggested features, you will create a powerful and user-friendly tool that leverages the capabilities of the TGTG-CLI package.