🤖 AI Analysis

Final verdict: SAFE

The package appears to be legitimate with no signs of malicious activity. The low scores across all risks suggest that it is not indicative of a supply-chain attack.

Low network, shell, obfuscation, and credential risks.
Metadata risk is slightly elevated due to a single-package maintainer.

Per-check LLM notes

Network: The observed network calls are likely for model management and API interactions, which could be normal for a package named 'EasyRerank' if it involves machine learning models.
Shell: No shell execution patterns were detected.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The maintainer has only one package, which could indicate a new or less active account.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 6.0

Found 4 network call pattern(s)

y: response = requests.get(f'http://{self.host}:{self.port}/v1/models', timeout=5)
try: response = requests.post( self.base_url, json=payload
exists response = requests.get( f'http://{self.host}:{self.port}/v1/models'
try: response = requests.post( self.base_url, headers=head

✓ Code Obfuscation

No obfuscation patterns detected

✓ 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 jon2allen/EasyRerank appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

Author "Jon Allen" 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 EasyRerank

Create a fully-functional mini-app called 'SmartSearch' that leverages the power of the 'EasyRerank' Python package to enhance the relevance of search results for a user query. This app will accept a query from the user and a set of documents or web pages as input, then use EasyRerank to perform semantic reranking on these documents based on their relevance to the query. Here’s how you can structure your project:

1. **Setup**: Begin by installing EasyRerank and any other necessary packages. Ensure that you have a setup.py file for easy installation.
2. **Input Handling**: Design a simple UI where users can input their query and upload a set of documents or URLs. The app should also support bulk uploading of documents.
3. **Processing**: Use EasyRerank to process the uploaded documents. Implement both local and remote reranking functionalities to showcase the flexibility of EasyRerank. For local reranking, ensure that the documents are automatically chunked if they exceed a certain size.
4. **Output Display**: Present the reranked documents back to the user in a sorted manner based on relevance. Each document should include a brief snippet showing how it relates to the query.
5. **Advanced Features** (Optional): Consider adding features such as highlighting relevant keywords within each document snippet, allowing users to filter results by date or source, and providing an option to save the results.
6. **Documentation**: Write comprehensive documentation explaining how to install and use the SmartSearch app, including examples and best practices.

Ensure that your application is user-friendly and efficient, making use of EasyRerank's capabilities to provide a superior search experience.