aurafarmer

v3.4.0 suspicious
6.0
Medium Risk

PRO — Terminal AI Coding Agent by SPRUKY

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits moderate risks due to its network and shell execution capabilities, suggesting potential for misuse. However, there is no concrete evidence of malicious intent.

  • High network risk
  • High shell execution risk
Per-check LLM notes
  • Network: Network calls to an external API suggest potential data exfiltration or C2 communication.
  • Shell: Execution of shell commands can indicate the presence of a backdoor or unintended behavior.
  • Obfuscation: No obfuscation patterns detected.
  • Credentials: The use of getpass suggests user interaction for password input, which could be legitimate but also indicates potential risk for credential harvesting.
  • Metadata: The package shows some signs of low effort and potential inactivity, but there are no clear indicators of malicious intent.

📦 Package Quality Overall: Low (2.8/10)

○ 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 (1764 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

  • 22 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 9.0

Found 6 network call pattern(s)

  • 96, }).encode() req = urllib.request.Request( f"{config.BASE_URL}/chat/completions",
  • method="POST", ) with urllib.request.urlopen(req, timeout=None) as resp: for raw in resp:
  • }).encode() return urllib.request.Request( f"{config.BASE_URL}/chat/completions",
  • try: with urllib.request.urlopen(_make_req(api_key), timeout=None) as resp:
  • .com/?{params}" req = urllib.request.Request(url, headers={"User-Agent": "Aurex/1.0"}) w
  • : "Aurex/1.0"}) with urllib.request.urlopen(req, timeout=15) as resp: data = json.lo
✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 8.0

Found 4 shell execution pattern(s)

  • agent.clear_history() os.system("clear" if os.name == "posix" else "cls") ui.print_b
  • ───────────── def main(): os.system("clear" if os.name == "posix" else "cls") ui.print_banne
  • tr: try: result = subprocess.run( command, shell=True, capture_output=True, text=
  • ess.run( command, shell=True, capture_output=True, text=True, timeout=60 )
⚠ Credential Harvesting score 2.5

Found 1 credential access pattern(s)

  • port getpass pw = getpass.getpass(f" {DIM}Password {BR}❯{RST} ").strip() except (Keyb
✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

  • No GitHub repository link found
⚠ 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 aurafarmer 
Create a terminal-based coding assistance tool called 'AuraHelper' using the 'aurafarmer' package. This tool aims to streamline the process of generating code snippets, fixing bugs, and optimizing existing code for developers. Here are the key functionalities you should implement:

1. **Code Snippet Generation**: Allow users to input a brief description or a problem statement, and the tool should generate relevant code snippets.
2. **Bug Fixing Assistant**: Provide suggestions on how to fix common bugs based on error messages or descriptions provided by the user.
3. **Code Optimization**: Offer recommendations for improving code efficiency and readability.
4. **Interactive Mode**: Implement an interactive mode where the user can ask follow-up questions about the generated code or bug fixes.
5. **Integration with Common IDEs**: Enable the tool to integrate with popular Integrated Development Environments like VS Code, PyCharm, etc., allowing users to directly run the generated code within their preferred IDE.
6. **Customization Options**: Allow users to customize the behavior of the tool, such as setting preferences for language-specific optimizations or snippet styles.
7. **Logging and History**: Maintain a log of all interactions and previous solutions provided by the tool for future reference.

To utilize the 'aurafarmer' package, you will need to leverage its capabilities for understanding natural language inputs, generating appropriate responses, and handling complex coding scenarios efficiently. Ensure that the integration is seamless and that the tool provides accurate and useful outputs for the developer community.

💬 Discussion Feed

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