🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has legitimate functionality but contains high-risk elements such as the use of eval which can be exploited. Additionally, there are concerns regarding the package's metadata, suggesting it may not be well-maintained.

High obfuscation risk due to the use of eval
Concerning metadata suggesting low effort or new account

Per-check LLM notes

Network: No network calls detected, indicating low risk.
Shell: Shell execution is present and could indicate legitimate functionality but also poses a risk if scripts are untrusted or have unintended side effects.
Obfuscation: The use of eval with dynamic strings may indicate an attempt to obfuscate code execution, posing a potential risk.
Credentials: No patterns indicative of credential harvesting were detected.
Metadata: Low risk, but concerns about author details and package maintenance suggest potential low effort or new account.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 8.0

Found 4 obfuscation pattern(s)

uttoff # cutoff = eval(f"{type}_cutoff") # data = pl.from_pandas(ccre_d
# 13 # y_label = eval(f"{type}_y_label") # if y_label is not None: #
cuttoff cutoff = eval(f"{type}_cutoff") data = pl.from_pandas(ccre_da
) # 13 y_label = eval(f"{type}_y_label") if y_label is not None:

⚠ Shell / Subprocess Execution score 6.0

Found 3 shell execution pattern(s)

}...") # try: # subprocess.run( # ["bash", script_path], # cwd=p
home}...") try: subprocess.run( ["bash", script_path], cwd=packa
t_path): sys.exit(1) try: subprocess.run(["bash",script_path],cwd=package_home,check=True) except

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: unlv.edu>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository qgenlab/DiffMethylTools appears legitimate

⚠ 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 DiffMethylTools

Create a mini-application called 'DMRVisualizer' that leverages the capabilities of the Python package 'DiffMethylTools' to help researchers analyze and visualize differentially methylated regions (DMRs). This application will allow users to upload their DNA methylation data, process it through 'DiffMethylTools', and generate interactive visualizations of the results.

The application should have the following features:
1. User Interface: Design a simple, intuitive web interface where users can upload their methylation data files (CSV or TSV format).
2. Data Processing: Implement a backend using 'DiffMethylTools' to detect differentially methylated loci and regions from the uploaded data. Users should be able to specify parameters such as the p-value threshold for significance.
3. Visualization: Generate interactive plots and graphs using libraries like Plotly or Bokeh to show the distribution of methylation levels across different samples and highlight significant DMRs.
4. Annotation: Utilize 'DiffMethylTools' to annotate detected DMRs with relevant genomic information (e.g., gene names, chromosome locations).
5. Export Results: Allow users to export the processed data and visualizations as downloadable files (PDF, PNG, CSV).

The goal is to provide researchers with an easy-to-use tool for analyzing and understanding differential methylation patterns in their datasets.