🤖 AI Analysis

Final verdict: SAFE

The package appears to be safe with no signs of malicious intent. However, there is some suspicion due to incomplete metadata and local execution of shell commands.

Low engagement and incomplete author information
Execution of shell commands like Docker and Blender

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires external services.
Shell: Execution of shell commands like Docker and Blender suggests the package may be performing complex operations locally, but further investigation is needed to confirm benign use.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The package shows low engagement and incomplete author information, raising some suspicion but not strong evidence of malice.

📦 Package Quality Overall: Low (4.6/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

Test runner config found: pyproject.toml

◈ Medium Documentation 5.0

Some documentation present

Detailed PyPI description (5025 chars)

○ Low Contributing Guide 2.0

No contributing guide or governance files found

No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found

◈ Medium Type Annotations 5.0

Partial type annotation coverage

37 type-annotated function signatures detected in source

◈ Medium Multiple Contributors 5.0

Limited contributor diversity

1 unique contributor(s) across 47 commits in danwahl/animasim
Single author but highly active (47 commits)

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 10.0

Found 6 shell execution pattern(s)

c_gltf.stem}.glb" subprocess.run( [_blender_bin(), "--background", "--factory
bool: try: return subprocess.run(["docker", "info"], capture_output=True).returncode == 0
mage() -> None: inspect = subprocess.run(["docker", "image", "inspect", IMAGE], capture_output=True)
r image {IMAGE} ...") subprocess.run( ["docker", "build", "-f", str(DOCKERFILE), "-t"
_path.relative_to(root)}" subprocess.run( ["docker", "run", "--rm", "-v", f"{root}:/work", IM
mtl, work / mtl.name) subprocess.run( ["obj2mjcf", "--obj-dir", str(work), "--save-mj

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: danwahl.net>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 2.5

Git history flags: Repository has zero stars and zero forks

Repository has zero stars and zero forks

⚠ Maintainer History score 6.0

3 maintainer concern(s) found

Author name is missing or very short
Author "" appears to have only 1 package on PyPI (new or inactive account)
Package has no PyPI classifiers (low effort / metadata quality)

✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with animasim

Create a simulation tool using the 'animasim' Python package that allows users to design and simulate various animal behaviors in a robotic environment. This tool should enable users to select different animals (such as birds, fish, and insects), customize their behaviors (e.g., flying patterns, swimming paths, and movement speeds), and observe how these behaviors interact within a virtual ecosystem. Utilize 'animasim' to provide pre-built animal models and animations that can be easily integrated into the simulation. Additionally, include features such as real-time adjustments of environmental factors (like wind speed, water currents, and obstacles) to see how they affect the animals' movements and behaviors. Finally, implement a feature that allows users to export their simulations as videos or shareable files for educational or research purposes.