🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits a moderate risk due to its network activity, which could potentially be used for data exfiltration or command-and-control activities. However, other risks such as shell execution, obfuscation, and credential harvesting are minimal.

Network risk is moderately high
Maintainer metadata is incomplete or inactive

Per-check LLM notes

Network: The package makes network calls which could be legitimate API interactions but may also indicate potential data exfiltration or C2 activities.
Shell: No shell execution patterns were detected, suggesting low risk for direct system command execution.
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 maintainer's author name is missing or very short and appears to be new or inactive, which raises some concern but does not conclusively indicate malice.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 9.0

Found 6 network call pattern(s)

try: resp = requests.get( api_url, params={**params_b
(request)) response = requests.post( url, self.get_callback_data(request
s None: session = requests.Session() self._session = session url = item['u
try: resp = requests.get( api_url, params={
'' try: request = requests.get( f"https://api.crossref.org/works/{doi}",
'' try: request = requests.get( f"https://api.datacite.org/dois/{doi}",

✓ 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: zib.de>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository MarcoReidelbach/MaRDMO appears legitimate

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

Author name is missing or very short
Author "" 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 MaRDMO

Create a mini-application called 'MathDataDoc' that leverages the MaRDMO package to streamline the documentation and querying of mathematical research data. This application should serve as a user-friendly interface for researchers to manage their data effectively within the MaRDI infrastructure. Here’s a detailed breakdown of what your application should include:

1. **User Registration and Authentication**: Allow users to register and log in securely. Once logged in, they should have access to their personal data management space.
2. **Data Documentation**: Implement a feature where users can document their mathematical datasets. Each dataset entry should include metadata such as title, author, date of creation, and a brief description. Additionally, allow users to upload files associated with these datasets.
3. **Query Functionality**: Provide a search functionality that enables users to query their documented datasets based on various criteria like title, author, or date. This should leverage the querying capabilities provided by MaRDMO.
4. **Integration with MaRDI Infrastructure**: Ensure that all data stored and managed through MathDataDoc is compliant with the MaRDI standards. This includes proper metadata tagging and storage practices recommended by MaRDI.
5. **Visualization Tools**: Integrate basic visualization tools that can help users understand their data better. For instance, if the data is numerical, simple graphs or charts could be generated.
6. **Security and Privacy**: Implement robust security measures to protect user data and privacy. This includes encrypting sensitive information and ensuring that only authorized users can access specific datasets.

To utilize the MaRDMO package effectively, you should explore its documentation and APIs to understand how it handles data documentation and querying. Your application should seamlessly integrate these functionalities to provide a smooth user experience.