🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits moderate risk due to potential code execution via eval() and minimal metadata. While there are no direct indications of malicious activity, the combination of these factors raises concerns about potential supply-chain risks.

High obfuscation risk due to eval() usage
Minimal package metadata

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires external services.
Shell: No shell execution detected, indicating no immediate risk of command injection or unauthorized system access.
Obfuscation: The use of eval() with untrusted input is highly suspicious and could indicate an attempt to execute arbitrary code.
Credentials: No clear signs of credential harvesting were found.
Metadata: The package shows signs of being newly created with minimal information provided by the author, which raises some suspicion.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 8.0

Found 4 obfuscation pattern(s)

'hidden_layers': eval(tup[1]), 'dropout': tup[2],
nce(hidden_layers, list) else eval(hidden_layers) if -1 in hidden_layers:
x) -> np.array: self.eval() x = torch.from_numpy(x).to(torch.float32)
s / num_batches model.eval() running_vloss = 0.0 if hasattr(val_dat

✓ 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: dkfz-heidelberg.de>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository WALL-E-Lab/Compocyte appears legitimate

⚠ Maintainer History score 6.0

3 maintainer concern(s) found

Only one version has ever been released — brand new package
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 Compocyte

Create a mini-application named 'CellAnnotator' that leverages the 'Compocyte' Python package to automate the annotation of cell types from single-cell RNA sequencing (scRNAseq) datasets. This tool will streamline the process of analyzing complex biological data by providing an intuitive interface for researchers to upload their scRNAseq datasets and receive annotated cell type classifications.

Step 1: Design the User Interface
- Develop a simple, user-friendly web interface using Flask or Django for handling file uploads and displaying results.
- Ensure the UI supports file upload functionality for users to input their scRNAseq data files.

Step 2: Implement Data Processing
- Integrate Compocyte into your application to handle the backend processing of uploaded scRNAseq datasets.
- Utilize Compocyte's hierarchical classifier arrangement to automatically annotate cell types based on the provided dataset.

Step 3: Display Results
- After processing, display the annotated cell types back to the user in a clear, organized manner.
- Include options to visualize the data, such as heatmaps or scatter plots, to help users understand the distribution of different cell types within their dataset.

Suggested Features:
- User authentication system allowing multiple users to save and manage their own datasets.
- Advanced settings panel where users can tweak parameters for the Compocyte classification process.
- Integration with popular bioinformatics tools like Seurat or Scanpy for additional analysis capabilities.
- Export functionalities for saving processed results in various formats (e.g., CSV, Excel).

How to Utilize Compocyte:
- Use Compocyte's core functions to preprocess and classify the uploaded scRNAseq data.
- Leverage its hierarchical structure to ensure accurate and comprehensive cell type annotations.
- Consider implementing Compocyte's training capabilities to allow users to fine-tune classifiers for specific datasets or conditions.