🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows minimal risks in terms of network, shell, obfuscation, and credential handling. However, the metadata risk score is elevated due to the maintainer having only one package and no associated GitHub repository, raising concerns about its legitimacy.

Low risk scores across network, shell, obfuscation, and credential handling
Elevated metadata risk due to lack of maintainer's history and repository

Per-check LLM notes

Network: No network calls detected, which is normal if the package does not require external communication.
Shell: No shell execution patterns detected, indicating no immediate signs of executing system commands.
Obfuscation: No obfuscation patterns detected, indicating likely legitimate use.
Credentials: No credential harvesting patterns detected, suggesting safe handling of secrets.
Metadata: The maintainer has only one package and no associated GitHub repository, which may indicate a less established or potentially suspicious presence.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ 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: aesim.tech

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

Author "AESIM.tech" 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 aesim.simba

Create a mini-application that simulates the performance of a motor drive system using the 'aesim.simba' package. Your application should allow users to input various parameters such as motor type, load conditions, control algorithms, and power supply characteristics. The simulation should output key performance metrics like speed regulation, torque response, efficiency, and thermal behavior over time.

Suggested Features:
1. User-friendly interface for parameter input
2. Real-time visualization of simulation results
3. Comparative analysis of different control algorithms
4. Saving and exporting simulation data
5. Documentation and help section for beginners

How to Utilize 'aesim.simba':
- Use 'aesim.simba' to define the motor model and simulate its dynamic behavior under varying conditions.
- Apply different control strategies available within the package to observe their impact on motor performance.
- Leverage the simulation capabilities to test theoretical concepts in a practical setting.