🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows signs of obfuscation, which is concerning as it might be an attempt to hide malicious activities. However, no direct evidence of harmful behavior was observed.

Unconventional import methods and string manipulations suggest possible evasion techniques.
Single package from the maintainer suggests a potentially new or less active account.

Per-check LLM notes

Network: No network calls detected.
Shell: Shell executions are likely benign, performing Git operations which could be part of version control or dependency management.
Obfuscation: The code uses unconventional import methods and string manipulations which may indicate an attempt to evade detection or analysis.
Credentials: No direct patterns indicative of credential harvesting were found in the provided code snippets.
Metadata: The maintainer has only one package, which may indicate a new or less active account.

📦 Package Quality Overall: Medium (5.4/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

Test runner config found: pyproject.toml

◈ Medium Documentation 7.0

Some documentation present

Documentation URL: "Documentation" -> https://aictx.org/
Detailed PyPI description (13808 chars)

○ 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

765 type-annotated function signatures detected in source

◈ Medium Multiple Contributors 5.0

Limited contributor diversity

1 unique contributor(s) across 100 commits in oldskultxo/aictx
Single author but highly active (100 commits)

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 10.0

Found 6 obfuscation pattern(s)

continue rows.append(__import__("json").loads(line)) return rows def cmd_suggest(args: argpar
else [], } print(__import__("json").dumps(payload, ensure_ascii=False)) return 0 def cmd_
else [], } print(__import__("json").dumps(payload, ensure_ascii=False)) return 0 def _pri
json", False)): print(__import__("json").dumps({"continuity_brief": brief, "ranked_items": context.g
json", False)): print(__import__("json").dumps(payload, ensure_ascii=False)) return 0 pr
json", False)): print(__import__("json").dumps(output, ensure_ascii=False)) return 0 pri

⚠ Shell / Subprocess Execution score 10.0

Found 6 shell execution pattern(s)

tr: try: result = subprocess.run(["git", *args], cwd=repo_root, check=False, capture_output=T
y]: try: inside = subprocess.run( ["git", "-C", repo_root.as_posix(), "rev-parse"
t_git_repo"} branch = subprocess.run( ["git", "-C", repo_root.as_posix(), "branch", "
5, ) commit = subprocess.run( ["git", "-C", repo_root.as_posix(), "rev-parse"
) porcelain = subprocess.run( ["git", "-C", repo_root.as_posix(), "status", "
[] try: tracked = subprocess.run( ["git", "ls-files", *snapshot_paths],

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository oldskultxo/aictx appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

Author "Santi Santamaria" 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 aictx

Create a fully-functional mini-application named 'CodeScribe' using the Python package 'aictx'. CodeScribe is designed to assist developers in writing code by providing context-aware suggestions and snippets based on the current coding environment. Here’s how you will build it:

1. **Project Setup**: Begin by setting up a new Python virtual environment and installing the 'aictx' package along with other necessary libraries such as 'requests' for HTTP operations and 'flask' for web serving.

2. **Core Functionality**: Implement the main functionality of CodeScribe which involves analyzing the developer's current code context and suggesting appropriate code snippets or solutions. Use 'aictx' to maintain state and context across different parts of the code, ensuring that suggestions are relevant to the ongoing development process.

3. **Context Management**: Utilize 'aictx' to manage context effectively. This includes tracking the file being edited, the current line of code, and any recent changes made by the user. Ensure that the context is preserved and updated seamlessly as the user interacts with the application.

4. **Integration with IDEs**: To make CodeScribe more useful, integrate it into popular Integrated Development Environments (IDEs) like VSCode or PyCharm. Provide extensions or plugins that can be installed within these IDEs to enable real-time suggestions and improvements.

5. **User Interface**: Develop a simple yet effective user interface where users can input their code snippet or describe their problem, and receive suggestions or solutions. Optionally, include a feature where users can vote on the usefulness of suggestions to improve future recommendations.

6. **Testing and Validation**: Rigorously test the application to ensure that it accurately understands the context and provides meaningful suggestions. Validate its performance across various programming languages and scenarios to ensure broad applicability.

7. **Documentation and Deployment**: Finally, document the setup process, usage instructions, and API documentation if applicable. Deploy the application on a platform like Heroku or AWS so that it can be easily accessed by developers worldwide.

By following these steps, you will create a powerful tool that leverages 'aictx' to enhance the productivity and efficiency of software developers.