atomchain

v0.3.2 suspicious
4.0
Medium Risk

A library to chain the atomic models with applications

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows some signs of potential risks, particularly concerning network calls and shell executions, though there's no clear indication of malicious intent. The change in maintainer and lack of author information add to the suspicion.

  • Network calls suggest legitimate model downloading but should be verified.
  • Potential file manipulation through shell executions.
  • Absence of author and new maintainer raise concerns.
Per-check LLM notes
  • Network: Network calls suggest legitimate model downloading but should be verified for source authenticity.
  • Shell: Shell executions indicate potential file manipulation and command-line tool usage which may serve intended functionality but pose higher risk for unintended actions.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity related to code obfuscation.
  • Credentials: No credential harvesting patterns detected, suggesting no immediate threat related to secret or credential theft.
  • Metadata: The package has some red flags such as an absent author and a new maintainer, but no concrete evidence of malicious intent.

📦 Package Quality Overall: Low (4.4/10)

✦ High Test Suite 9.0

Test suite present — 14 test file(s) found

  • Test runner config found: conftest.py
  • Test runner config found: pyproject.toml
  • 14 test file(s) detected (e.g. __init__.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (6174 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

  • 180 type-annotated function signatures detected in source
○ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

  • No GitHub repository linked — contributor count unavailable

🔬 Heuristic Checks

⚠ Outbound Network Calls score 4.5

Found 3 network call pattern(s)

  • l_file}..." ) urllib.request.urlretrieve(MACE_R2SCAN_MODEL_URL, mace_model_file) exce
  • "atomchain.init_model.urllib.request.urlretrieve", mock_urlretrieve ) result = _ensure_m
  • "atomchain.init_model.urllib.request.urlretrieve", mock_urlretrieve ) with pytest.raises
✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 10.0

Found 6 shell execution pattern(s)

  • ir, "SUPERCELL0") os.system( "ln -s %s %s" % (
  • ) ) os.system( "cp %s %s" % (
  • ws help. """ result = subprocess.run( ["mlcompare", "--help"], capture_output=Tru
  • comparison.png" result = subprocess.run( [ "mlcompare", str(traj1_pa
  • li_labeled.png" result = subprocess.run( [ "mlcompare", str(traj1_pa
  • normalized.png" result = subprocess.run( [ "mlcompare", str(traj1_pa
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

  • No GitHub repository link found
⚠ 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 atomchain 
Your task is to develop a small, yet powerful, command-line tool called 'AtomicChainVisualizer'. This utility will allow users to visualize and manipulate chains of atomic models using the 'atomchain' Python package. The tool should be designed to provide an interactive experience where users can input commands to create, modify, and analyze atomic chains. Here’s a detailed breakdown of the project requirements and steps to follow:

1. **Project Setup**: Begin by setting up your Python environment and installing the 'atomchain' package. Ensure you have all necessary dependencies installed as well.
2. **Command Line Interface (CLI)**: Develop a CLI interface that allows users to interact with the tool through simple commands. For example, commands like `create`, `modify`, `analyze`, and `visualize` should be available.
3. **Creating Atomic Chains**: Implement functionality within the CLI that enables users to create new atomic chains. Users should be able to specify parameters such as the type of atoms involved, the length of the chain, and any other relevant details.
4. **Modifying Atomic Chains**: Allow users to modify existing atomic chains by adding or removing atoms, changing the properties of specific atoms, or adjusting the overall structure of the chain.
5. **Analyzing Atomic Chains**: Provide analytical tools that allow users to assess various properties of their atomic chains, such as stability, energy levels, or molecular interactions.
6. **Visualization**: Integrate a feature that visualizes the atomic chains in a graphical format. This could involve generating 2D or 3D representations of the chains based on user input.
7. **Saving and Loading Sessions**: Enable users to save their current atomic chain configurations to files and load them later for further manipulation or analysis.
8. **Documentation and Help Commands**: Ensure that your tool comes with comprehensive documentation and includes built-in help commands that guide users through the usage of each feature.

The 'atomchain' package plays a crucial role in this project by providing the underlying framework for chaining atomic models together. It handles the complexities of atomic interactions and provides functions that simplify the creation, modification, and analysis of these chains. Your goal is to leverage this package to create a user-friendly and powerful tool for anyone interested in exploring atomic chains.

💬 Discussion Feed

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