🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits moderate risks due to its high shell execution risk and average network interaction, which might indicate potential misuse. However, there is no direct evidence of malicious intent.

High shell risk due to command executions
Average network risk with possible legitimate use

Per-check LLM notes

Network: The network patterns include local connections and HTTP requests which could be legitimate depending on the package's functionality.
Shell: Executing shell commands like git clone and container image inspection can pose risks if not properly controlled, suggesting potential for unauthorized access or code execution.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The package shows signs of low maintainer activity and poor metadata quality, raising some suspicion but not conclusive evidence of malice.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 4.5

Found 3 network call pattern(s)

ere.""" try: with socket.create_connection(("localhost", 6000), timeout=0.5): return True
s.""" try: sock = socket.create_connection((host, port), timeout=timeout) except OSError: r
models" try: with urllib.request.urlopen(url, timeout=_TIMEOUT_SECONDS) as resp:

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 10.0

Found 6 shell execution pattern(s)

age: str) -> bool: return subprocess.run( [CONTAINER_RUNTIME, "image", "inspect", image],
e don't normalize.""" p = subprocess.run( [CONTAINER_RUNTIME, "image", "inspect", "--format",
into {cache}\n") rc = subprocess.run(["git", "clone", url, str(cache)]).returncode if rc
es for {url}\n") rc = subprocess.run( ["git", "-C", str(cache), "fetch", "--all", "--
ref is not None: rc = subprocess.run( ["git", "-C", str(cache), "checkout", "--detach
am is gone, leave it. subprocess.run( ["git", "-C", str(cache), "pull", "--ff-only"],

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

No GitHub repository link found

⚠ 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 aetherion

Create a mini-application called 'AI Coding Companion' using the Python package 'aetherion'. This application will serve as a streamlined interface for developers to quickly launch and manage development environments tailored specifically for AI projects. The app should allow users to specify their preferred programming languages, libraries, and tools needed for their AI projects, and then automatically set up a development environment in a Docker container via 'aetherion'. Additionally, the application should include features such as:

1. User-friendly command-line interface (CLI) for easy interaction.
2. Integration with popular cloud storage services (e.g., AWS S3, Google Drive) for saving and restoring development environments.
3. Support for multiple AI frameworks (TensorFlow, PyTorch, etc.).
4. Automatic configuration of version control systems like Git within the containers.
5. Option to run Jupyter Notebooks directly inside the containerized environment.
6. A feature to track and display the status of running containers.
7. Documentation generation for the setup process and available commands.

The core functionality of 'aetherion' should be leveraged to handle the launching and management of these containers, ensuring that developers can focus on coding rather than setting up their environments.