AI Analysis
Final verdict: SUSPICIOUS
The package exhibits a moderate risk level due to the presence of 'eval', which can be leveraged for code injection. However, there are no signs of malicious activity or supply-chain attacks.
- Use of 'eval' indicating potential for code injection.
- Low effort in metadata and author history.
Per-check LLM notes
- Network: No network calls detected, which is normal for a scientific computing library.
- Shell: No shell execution patterns detected, indicating no direct system command risks.
- Obfuscation: The use of 'eval' in the code suggests potential for code injection and obfuscation, raising concerns about its legitimacy.
- Credentials: No clear patterns indicating credential harvesting were detected.
- Metadata: The package shows low effort in metadata and author history, but lacks clear indicators of malicious intent.
Heuristic Checks
Outbound Network Calls
No suspicious network call patterns found
Code Obfuscation
score 8.0
Found 4 obfuscation pattern(s)
wrap_key_data(jnp.array(eval(seed), dtype=jnp.uint32)) ) elif isinstam", gdict) wcs_type = eval("jax_galsim." + wcs_name, gdict) wcs = wcs_type._rea.GSObject): ret_obj = eval(repr(obj)) return ret_obj else: return oentity mapping assert eval(repr(obj)) == obj # pickle is identity mapping
Shell / Subprocess Execution
No shell execution patterns detected
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
Repository GalSim-developers/JAX-GalSim appears legitimate
Maintainer History
score 4.0
2 maintainer concern(s) found
Author "GalSim Developers" 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 JAX-GalSim
Develop a mini-application that simulates and analyzes galaxy images using the JAX-GalSim package. Your application should allow users to input parameters such as galaxy type, size, brightness, and noise level to generate synthetic galaxy images. Additionally, include functionality to perform basic analysis on these images, such as measuring the centroid, ellipticity, and other morphological properties. The app should also provide visualization tools to display the simulated images alongside their analysis results. Use JAX-GalSim's capabilities to ensure that the simulations are efficient and can handle large-scale astronomical data sets. Suggested features include an interactive UI for parameter adjustment, a gallery of pre-defined galaxy types, and export options for the generated images and analysis reports.