aisurface

v1.0.2 suspicious
6.0
Medium Risk

Make your open-source project surface in AI search results

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits some unusual behaviors including potential unsafe file handling and a lack of repository activity, which raises suspicion.

  • Potential unsafe handling of sensitive files indicated by PermissionError context
  • Repository is new with no activity
Per-check LLM notes
  • Network: The network call patterns seem to be legitimate requests to fetch information from a package repository, possibly for dependency resolution or version checking.
  • Shell: The shell execution patterns indicate that the package is invoking scripts within its directory structure, likely for internal auditing or fixing purposes. However, without further context, there's a slight risk of unintended command execution.
  • Obfuscation: The use of rot13 is not typical for obfuscation and seems to be used here for string transformation rather than hiding information.
  • Credentials: The use of PermissionError in context with '/etc/passwd' suggests a test scenario but could also indicate potential unsafe handling of sensitive files.
  • Metadata: The repository is new with no activity, and the maintainer has only one package, raising concerns about potential malicious intent.

📦 Package Quality Overall: Medium (6.0/10)

✦ High Test Suite 9.0

Test suite present — 25 test file(s) found

  • Test runner config found: conftest.py
  • 25 test file(s) detected (e.g. conftest.py)
◈ Medium Documentation 7.0

Some documentation present

  • Detailed PyPI description (4334 chars)
  • Classifier: Documentation
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 5.0

Partial type annotation coverage

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

Limited contributor diversity

  • 1 unique contributor(s) across 100 commits in ruijayfeng/aisurface
  • Single author but highly active (100 commits)

🔬 Heuristic Checks

⚠ Outbound Network Calls score 3.0

Found 2 network call pattern(s)

  • own>" try: resp = httpx.get(_PYPI_URL, timeout=_PYPI_TIMEOUT) resp.raise_for_sta
  • try: with httpx.Client(timeout=self.timeout) as client: response =
✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 10.0

Found 6 shell execution pattern(s)

  • arsed report.""" result = subprocess.run( [sys.executable, "-m", "scripts.cli", "audit", str(
  • inimal-cli-tool" result = subprocess.run( [sys.executable, "-m", "scripts.cli", "audit", str(
  • e(src, fixture) result = subprocess.run( [sys.executable, "-m", "scripts.cli", "fix", str(fi
  • ne audit score baseline = subprocess.run( [sys.executable, "-m", "scripts.cli", "audit", str(
  • # Apply fix fix_result = subprocess.run( [sys.executable, "-m", "scripts.cli", "fix", str(fi
  • pect higher score after = subprocess.run( [sys.executable, "-m", "scripts.cli", "audit", str(
⚠ Credential Harvesting score 2.5

Found 1 credential access pattern(s)

  • ror(13, "Permission denied", "/etc/passwd") with pytest.raises(PermissionError): handler
✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 5.0

Git history flags: Repository created very recently: 5 day(s) ago (2026-06-01T13:26:45Z)

  • Repository created very recently: 5 day(s) ago (2026-06-01T13:26:45Z)
  • Repository has zero stars and zero forks
⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Jay Feng" 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 aisurface 
Create a Python-based mini-app that helps developers enhance their GitHub projects' visibility in AI-driven search results. The app, named 'AI-Surface', will use the 'aisurface' package to optimize project metadata such as README content, tags, and descriptions to make them more discoverable by AI search engines. Here’s a step-by-step guide on how to develop this application:

1. **Project Setup**: Initialize a new Python project and install the 'aisurface' package.
2. **User Input Interface**: Design a simple command-line interface (CLI) where users can input the URL of their GitHub repository.
3. **Metadata Extraction**: Develop a function that extracts key metadata from the provided GitHub repository including README content, description, and tags.
4. **Optimization Module**: Implement an optimization module using 'aisurface'. This module will analyze the extracted metadata and suggest improvements to make the project more relevant and searchable by AI algorithms.
5. **Feedback Mechanism**: Create a feedback mechanism that allows users to review the suggested changes before applying them.
6. **Apply Changes**: Once the user approves the changes, the app should automatically update the project's metadata on GitHub.
7. **Logging & Reporting**: Include logging capabilities to track changes made and generate a report summarizing the enhancements applied.

**Suggested Features**:
- Integration with GitHub API for seamless interaction.
- Support for multiple languages in README content.
- Analysis of keyword relevance and density in project descriptions.
- Customizable optimization settings based on specific AI search engine preferences.
- User-friendly CLI with clear instructions and error handling.

By utilizing the 'aisurface' package effectively, 'AI-Surface' aims to simplify the process of making open-source projects more visible and accessible through AI-driven discovery mechanisms.