AI Analysis
Final verdict: SUSPICIOUS
The package exhibits moderate network risk due to potential unauthorized data transmission, while other risks like shell execution, obfuscation, and credential harvesting are low. The metadata risk is slightly elevated given the author's limited history on PyPI.
- Moderate network risk due to posting data with a password
- Author has only one package on PyPI
Per-check LLM notes
- Network: The observed network calls include posting data with a password and fetching a file from a remote URL, which may indicate unauthorized data transmission.
- Shell: No shell execution patterns were detected.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The author 'wwf' has only one package on PyPI, which could indicate a new or less active account, raising some suspicion but not definitive evidence of malice.
Heuristic Checks
Outbound Network Calls
score 3.0
Found 2 network call pattern(s)
"password")} r = requests.post( "{}{}".format("host", endpoint), json=data,A file url response = requests.get(self.c.CTA_FILE_URL, headers=headers, timeout=30) #
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: wwf.se
Suspicious Page Links
All external links appear legitimate
Git Repository History
Repository WWF-Sweden/ITR-tool appears legitimate
Maintainer History
score 2.0
1 maintainer concern(s) found
Author "wwf" 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 WWF-ITR
Create a web-based application using Flask (Python framework) that leverages the 'WWF-ITR' package to help financial institutions and companies evaluate their investment and lending portfolios against climate change targets. The app should allow users to input their portfolio data and receive a detailed report on the temperature alignment of their current climate reduction targets and commitments. Additionally, the app should provide guidance on developing new targets that are eligible for validation by the Science-Based Targets initiative (SBTi). Here are the key steps and features your application should include: 1. **User Registration & Authentication**: Implement user registration and login functionality to ensure secure access to portfolio data. 2. **Data Input Form**: Design a form where users can input details about their investment and lending portfolios, including types of investments, amounts invested, and associated emissions data. 3. **Temperature Alignment Assessment**: Utilize the 'WWF-ITR' package to analyze the provided data and generate a score indicating the degree of alignment between the portfolio's current climate reduction targets and global temperature goals. 4. **Target Development Tool**: Offer a feature that suggests adjustments to the portfolio based on the assessment results, guiding users towards setting new targets that meet SBTi standards. 5. **Detailed Reports**: Provide comprehensive reports summarizing the assessment findings, including visualizations and actionable insights. 6. **Dashboard**: Develop a dashboard that allows users to track progress over time and monitor changes in their portfolio's temperature alignment as they implement new strategies. 7. **API Integration**: Consider integrating with external data sources for more accurate assessments and real-time updates. 8. **Documentation**: Ensure all functionalities are well-documented, including API documentation for potential integration into other systems.