🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits a moderate risk profile due to high shell execution risk and insufficient metadata. While there is no clear evidence of malicious activity, the ability to execute shell commands could be exploited.

High shell execution risk
Insufficient metadata and author information

Per-check LLM notes

Network: Network calls are typical for packages that interact with web services, but the snippet provided is incomplete and does not clearly indicate malicious intent.
Shell: Executing shell commands like 'git ls-files' can be part of version control operations but also poses a higher risk if used improperly, potentially allowing for unauthorized system access or command execution.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent related to code obfuscation.
Credentials: No secret harvesting patterns detected, suggesting the package does not pose a threat regarding credential theft.
Metadata: The package has no associated GitHub repository and the author's information is sparse, indicating potential lack of transparency.

📦 Package Quality Overall: Medium (5.2/10)

✦ High Test Suite 9.0

Test suite present — 8 test file(s) found

Test runner config found: conftest.py
8 test file(s) detected (e.g. conftest.py)

◈ Medium Documentation 5.0

Some documentation present

Detailed PyPI description (11027 chars)

○ Low Contributing Guide 4.0

No contributing guide or governance files found

Development Status classifier >= Beta

◈ Medium Type Annotations 7.0

Partial type annotation coverage

Type checker (mypy / pyright / pytype) referenced in project
35 type-annotated function signatures detected in source

○ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

No GitHub repository linked — contributor count unavailable

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

ed") self._session = requests.Session() self.url = url.rstrip("/") self.headers =

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 2.0

Found 1 shell execution pattern(s)

h): try: result = subprocess.run( ["git", "ls-files", "--cached", "--others", "--

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

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 archivebox-api

Create a Personal Web Archiving Assistant using the 'archivebox-api' package. This application will serve as a personal tool for archiving web content based on user input and queries. The goal is to streamline the process of saving web pages and their metadata for future reference or historical purposes.

Steps to follow:
1. Set up a basic Flask web application to serve as the frontend interface where users can interact with the archiving functionality.
2. Integrate the 'archivebox-api' package into your Flask app to handle the backend operations related to archiving web content.
3. Implement a feature that allows users to submit URLs for archiving through the Flask app's form.
4. Use the 'archivebox-api' to call the necessary functions to archive the submitted URLs, capturing not just the HTML but also associated metadata and assets.
5. Add a search functionality within the Flask app that lets users query previously archived content using keywords or tags.
6. Enhance the application by adding a feature that periodically checks and archives new content from a list of predefined websites.
7. Ensure the application logs all activities, such as successful archiving attempts and any errors encountered during the archiving process.
8. Deploy the final application on a platform like Heroku or AWS to make it accessible online.

Suggested Features:
- User-friendly form submission for URLs
- Real-time feedback on the archiving process
- Searchable database of archived content
- Scheduled archiving tasks for regular updates
- Error logging and handling system
- Integration with popular web services for additional data retrieval

How 'archivebox-api' is Utilized:
- For archiving web content, you'll use the 'archivebox_api.archive()' function provided by the package.
- To manage and retrieve archived content, utilize the 'archivebox_api.list_archives()' and 'archivebox_api.search()' functionalities.
- Leverage the fast MCP server capabilities of 'archivebox-api' for efficient data processing and storage.