b4n1-web

v0.9.0 suspicious
6.0
Medium Risk

B4n1Web Agentic Browser Engine - Ultra-lightweight headless browser for AI agents

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits elevated risks due to the use of shell commands that can modify file permissions and execute binaries with sudo, suggesting potential for privilege escalation. While there are no direct signs of malicious intent like obfuscation or credential harvesting, the incomplete metadata and network calls warrant further scrutiny.

  • High shell risk due to sudo usage
  • Incomplete maintainer metadata
Per-check LLM notes
  • Network: The network calls to external URLs appear to be fetching version and download information which is somewhat common but should be scrutinized for legitimacy.
  • Shell: The use of shell commands to modify file permissions and execute binaries suggests potential risks, especially with sudo usage, indicating elevated privileges which could be exploited.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The maintainer's author name is missing and they seem to be new or inactive, raising some suspicion but not conclusive evidence of malice.

📦 Package Quality Overall: Low (4.6/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (2945 chars)
◈ Medium Contributing Guide 7.0

Some contribution signals present

  • Governance file: security.py
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 71 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 5.0

Limited contributor diversity

  • 1 unique contributor(s) across 29 commits in B4N1-com/b4n1-web
  • Single author but highly active (29 commits)

🔬 Heuristic Checks

⚠ Outbound Network Calls score 4.5

Found 3 network call pattern(s)

  • port requests resp = requests.get(version_url, timeout=10) version_info = resp.json()
  • ...") try: resp = requests.get(download_url, timeout=60) resp.raise_for_status()
  • _agent self.session = requests.Session() self.session.verify = "/etc/ssl/certs/ca-certifica
✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 10.0

Found 5 shell execution pattern(s)

  • t subprocess subprocess.run(["chmod", "+x", str(binary_path)], check=True)
  • sr/bin"): subprocess.run( ["sudo", "chmod", "+x", str(binary_
  • one try: result = subprocess.run( [binary, "--version"], capture_outp
  • try: result = subprocess.run( cmd, capture_output=True,
  • e.""" self._process = subprocess.Popen( [self.binary_path, "mcp"], stdin=su
✓ 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

Repository B4N1-com/b4n1-web appears legitimate

⚠ 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 b4n1-web 
Develop a web-based news aggregator app using the 'b4n1-web' package. This app will allow users to input multiple news sources (websites), and it will automatically scrape headlines from these sites, presenting them in a clean, organized manner. Here are the steps and features you should consider:

1. **Setup**: Install the 'b4n1-web' package and set up a basic Flask or Django backend to handle user inputs and serve the aggregated data.
2. **User Interface**: Design a simple, intuitive UI where users can enter URLs of their preferred news sources.
3. **Headless Browsing**: Use 'b4n1-web' to navigate to each provided URL, extract headline information, and close the browser session without rendering the page visually.
4. **Data Scraping**: Implement a scraping mechanism within 'b4n1-web' to parse HTML and extract relevant headline data (title, link).
5. **Data Presentation**: Store the scraped headlines temporarily and present them on the app’s main page, sorted by source.
6. **Additional Features**: Consider adding filters to sort headlines by date, relevance, or keyword searches; also, include a feature to save favorite sources.
7. **Testing & Deployment**: Test the app thoroughly to ensure reliability and efficiency, then deploy it using a cloud service provider like Heroku or AWS.

This project leverages 'b4n1-web' for its lightweight headless browsing capabilities, enabling efficient scraping of web content without the overhead of a full graphical browser.

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