aion-evolve

v1.4.0 suspicious
6.0
Medium Risk

AION: The Self-Evolving Code Engine. Code Once, Live Forever.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits several high-risk behaviors including direct shell execution and potential code injection through 'eval()', which significantly elevate its risk profile beyond typical benign functionality.

  • High shell risk due to os.system usage
  • Obfuscation risk from eval() function
Per-check LLM notes
  • Network: The presence of network calls to localhost suggests possible internal communication, but without context, it could indicate malicious C2 traffic.
  • Shell: Direct use of os.system for command execution poses significant security risks and is generally discouraged unless absolutely necessary, indicating potential for arbitrary code execution.
  • Obfuscation: The presence of 'eval()' with non-constant arguments suggests potential for code injection and obfuscation.
  • Credentials: The use of 'os.getenv()' to retrieve environment variables may indicate legitimate use but also poses a risk of exposing secrets if not handled properly.
  • Metadata: Low risk due to lack of suspicious elements, but concerns about maintainer history suggest caution.

📦 Package Quality Overall: Medium (6.2/10)

✦ High Test Suite 9.0

Test suite present — 35 test file(s) found

  • Test runner config found: pyproject.toml
  • 35 test file(s) detected (e.g. test_e2e_scenarios.py)
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://shenxianpeng.github.io/aion/
  • Detailed PyPI description (6916 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 454 type-annotated function signatures detected in source
✦ High Multiple Contributors 8.0

Active multi-contributor project

  • 3 unique contributor(s) across 86 commits in shenxianpeng/aion
  • Small but multi-author team (3–4 contributors)

🔬 Heuristic Checks

⚠ Outbound Network Calls score 9.0

Found 6 network call pattern(s)

  • demo.py"}).encode() req = urllib.request.Request( f"http://127.0.0.1:{captured_port[0]}/event
  • method="POST", ) with urllib.request.urlopen(req, timeout=5) as resp: body = json.loads(r
  • de("utf-8") request = urllib.request.Request( f"http://127.0.0.1:{server.server_port}
  • POST", ) with urllib.request.urlopen(request, timeout=5) as response: body =
  • "detection_pattern": "requests.get(", "detection_desc": "requests.get without timeo
  • nding( issue="requests.get() without timeout parameter causes hangs", s
⚠ Code Obfuscation score 10.0

Found 6 obfuscation pattern(s)

  • ion": { "issue": "eval() with user-controlled input enables arbitrary code executio
  • line=self._line_for(content, "eval("), evidence=["eval() called with non-co
  • evidence=["eval() called with non-constant argument"], c
  • tr) -> bool: # Detect eval() where the argument is not a simple string or numeric const
  • summary="Replace eval() with ast.literal_eval() to safely evaluate literal Python
  • "Replace eval( with ast.literal_eval( to prevent arbitrary code execution.
⚠ Shell / Subprocess Execution score 10.0

Found 6 shell execution pattern(s)

  • line=self._line_for(content, "os.system("), evidence=["os.system(f-string)"],
  • evidence=["os.system(f-string)"], confidence=0.95,
  • "quote") return f'os.system(f{quote}{cmd}{{shlex.quote({var})}}{tail}{quote})'
  • name: str) -> int: return os.system(f"generate-report {report_name}") """Generated by Copilot."
  • , ' return os.system(f"cmd {name}")', ] ), encoding="
  • try: result = subprocess.run( ["gh", "pr", "list", "--head", "aion/", "--
⚠ Credential Harvesting score 7.5

Found 3 credential access pattern(s)

  • _content='import os\nSECRET = os.getenv("SECRET", "")', diff="", ) verification = Verificat
  • encoding="utf-8") assert 'os.getenv("API_KEY", "")' in patched assert "sk-live-demo-secret" not in p
  • _content='import os\nSECRET = os.getenv("SECRET", "")', diff="", ) return VerificationResul
✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository shenxianpeng/aion appears legitimate

⚠ Maintainer History score 6.0

3 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" appears to have only 1 package on PyPI (new or inactive account)
  • Package has no PyPI classifiers (low effort / metadata quality)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with aion-evolve 
Your task is to create a futuristic, self-evolving personal finance tracker using the Python package 'aion-evolve'. This tool will allow users to input their financial transactions, categorize them automatically, and receive evolving insights and recommendations based on their spending habits over time. Here’s how you’ll build it:

1. **Setup and Initialization**: Begin by setting up your Python environment and installing 'aion-evolve'. Your goal is to use 'aion-evolve' to make your codebase adaptive and capable of learning from user interactions.
2. **User Interface**: Design a simple command-line interface (CLI) where users can input new transactions, view their current balance, and see categorized expenses.
3. **Transaction Management**: Implement functionality that allows users to add transactions (amount, date, category). Use 'aion-evolve' to write a function that can dynamically update its behavior as more data is added, improving transaction categorization accuracy.
4. **Budgeting Insights**: Utilize 'aion-evolve' to generate evolving budgeting advice. As the system learns from the user’s spending patterns, it should offer personalized tips on saving money and reducing unnecessary expenses.
5. **Data Visualization**: Incorporate basic data visualization features that show monthly expense trends and savings progress. These visualizations should be updated based on the evolving insights provided by 'aion-evolve'.
6. **Testing and Iteration**: Test your application thoroughly to ensure that it accurately reflects the user's financial status and evolves over time. Iterate on the design and functionality based on feedback and observed performance.
7. **Documentation and Deployment**: Document your code and deployment process clearly so that other developers can understand and contribute to the project easily.

By the end of this project, you'll have a powerful, self-improving tool that helps users manage their finances more effectively, all while showcasing the unique capabilities of 'aion-evolve'.

💬 Discussion Feed

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