TM1py

v2.3.0 safe
4.0
Medium Risk

A python module for TM1.

🤖 AI Analysis

Final verdict: SAFE

The package TM1py v2.3.0 is assessed as safe with a moderate network risk due to its interaction with external services. Other risks such as shell execution, obfuscation, and credential harvesting are all low.

  • Moderate network risk
  • Low risk for shell execution
  • No signs of obfuscation or credential harvesting
Per-check LLM notes
  • Network: Network calls indicate the package likely interacts with external services, which is common but requires scrutiny to ensure proper authorization and data handling.
  • Shell: No shell execution patterns detected.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 9.0

Found 6 network call pattern(s)

  • Instances" response = requests.get(url=url, auth=self._auth_header) return json.loads(r
  • e_name}')" response = requests.get(url=url, auth=self._auth_header) return json.loads(r
  • ance_name} response = requests.post(url=url, json=payload, auth=self._auth_header) retur
  • e_name}')" response = requests.delete(url=url, auth=self._auth_header) return response
  • e_name}')" response = requests.get(url=url, auth=self._auth_header) if response.ok:
  • Databases" response = requests.get(url=url, auth=self._auth_header) return json.loads(r
✓ Code Obfuscation

No obfuscation patterns detected

✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

⚠ Typosquatting score 3.0

Possible typosquat of: mypy

  • "TM1py" is 2 edit(s) from "mypy"
✓ Registered Email Domain

Email domain looks legitimate: cubewise.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository cubewise-code/tm1py 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 TM1py 
Create a fully-functional mini-application using the Python package 'TM1py' that interacts with TM1 (Planning Analytics Workspace). Your task is to develop a utility named 'TM1 Data Fetcher' which will serve as a data retrieval tool from a TM1 instance. This utility should allow users to authenticate with their TM1 instance, browse through cubes, dimensions, and hierarchies, and fetch data based on user-defined parameters. The application should also support exporting fetched data into CSV files for further analysis.

### Features:
- **Authentication**: Implement secure authentication mechanisms to connect to a TM1 instance.
- **Data Browsing**: Provide a user interface to navigate through available cubes, dimensions, and hierarchies.
- **Data Retrieval**: Allow users to specify dimensions and elements to fetch data from selected cubes.
- **CSV Export**: Enable users to export retrieved data into CSV format for easy sharing and analysis.
- **Error Handling**: Ensure robust error handling to manage issues such as invalid input, connection failures, and permission errors.
- **Logging**: Include logging functionality to track operations performed and any errors encountered.

### Utilization of 'TM1py':
- Use 'TM1py' to establish a connection to the TM1 server.
- Leverage 'TM1py' methods to query and retrieve data from TM1 cubes.
- Employ 'TM1py' functionalities to handle authentication and authorization processes.
- Utilize 'TM1py' capabilities to interact with TM1 dimensions and hierarchies for data browsing purposes.