🤖 AI Analysis

Final verdict: SAFE

The package shows no signs of malicious activity, with all risk categories scoring the lowest possible. There are no indications of a supply-chain attack.

No network calls detected.
No shell execution patterns found.

Per-check LLM notes

Network: No network calls detected, which is normal unless the package's functionality requires external communication.
Shell: No shell execution patterns detected, indicating no immediate signs of malicious activities.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ 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 WillyEverGreen/acon appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

Author "WillyEverGreen" 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 acon-intel

Your task is to create a web scraping utility named 'SmartCrawler' using the Python package 'acon-intel'. This utility will enable users to scrape websites more intelligently by leveraging AI-driven decision-making processes. Here’s a detailed breakdown of what your project should include:

1. **Project Setup**: Begin by setting up your Python environment and installing the necessary packages including 'acon-intel', 'Scrapinghub/Scraping', 'Playwright', and 'httpx'. Make sure you have the required dependencies installed.
2. **User Interface**: Develop a simple command-line interface (CLI) where users can input the URL they wish to scrape and select the type of data they want to extract (e.g., articles, images, contact information).
3. **Intelligent Scraping**: Utilize 'acon-intel' to enhance the scraping process. For instance, use its AI capabilities to automatically identify the most relevant sections of a webpage based on user input. 'Acon-intel' should also help in making decisions about which links to follow and which ones to ignore, based on relevance and depth of navigation.
4. **Data Extraction & Processing**: Once the relevant sections are identified, use 'Scrapinghub/Scraping', 'Playwright', and 'httpx' to extract the desired data. Implement functionality within 'acon-intel' to preprocess this data, such as cleaning text, filtering out irrelevant content, and organizing the extracted data into structured formats like JSON or CSV.
5. **Output & Reporting**: Finally, allow the user to choose how they would like their data outputted (JSON, CSV, etc.) and provide a summary report of the scraping session, including metrics like the number of pages scraped, total data size, and any issues encountered during the process.
6. **Advanced Features** (Optional): Consider adding advanced features such as automated image recognition and extraction, sentiment analysis of scraped text, or even integration with cloud storage services for large datasets.

Ensure your project is well-documented, includes comments in the code, and has a README file explaining how to install and run the application. Your goal is to demonstrate how 'acon-intel' can significantly improve the efficiency and effectiveness of web scraping tasks.