apcore-cli

v0.10.0 suspicious
5.0
Medium Risk

Terminal adapter for apcore — execute AI-Perceivable modules from the command line

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits moderate risks due to potential obfuscation techniques and sparse metadata, suggesting possible attempts to hide data or intentions. However, there is no clear evidence of malicious activities.

  • High obfuscation risk
  • Sparse repository metadata
Per-check LLM notes
  • Network: No network calls detected, which is normal and does not indicate any risk.
  • Shell: Shell execution patterns observed may be related to the package's functionality, but further investigation into the legitimacy and necessity of these executions is advised.
  • Obfuscation: The use of base64 decoding with specific prefixes suggests an attempt to hide or obfuscate data, which could be indicative of malicious activity.
  • Credentials: No direct evidence of credential harvesting is found, but the presence of obfuscated data could potentially be used for storing and retrieving sensitive information.
  • Metadata: The repository has no activity and the maintainer's information is sparse, raising concerns about its legitimacy.

📦 Package Quality Overall: Medium (5.6/10)

✦ High Test Suite 9.0

Test suite present — 26 test file(s) found

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

Some documentation present

  • Documentation URL: "Documentation" -> https://github.com/aiperceivable/apcore-cli-python#readme
  • Detailed PyPI description (24240 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

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

Limited contributor diversity

  • 1 unique contributor(s) across 100 commits in aiperceivable/apcore-cli-python
  • Single author but highly active (100 commits)

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 4.0

Found 2 obfuscation pattern(s)

  • try: data = base64.b64decode(config_value[len("enc:v2:") :]) return self.
  • try: data = base64.b64decode(config_value[len("enc:") :]) return self._ae
⚠ Shell / Subprocess Execution score 10.0

Found 6 shell execution pattern(s)

  • try: result = subprocess.run( cmd, input=roff_bytes,
  • try: subprocess.run( [pager, "-R"], inpu
  • ze = 64 * 1024 proc = subprocess.Popen( [sys.executable, "-m", "apcore_cli._sandbox_run
  • ", ] result = subprocess.run( argv, capture_output=True,
  • honored.""" result = subprocess.run( [ sys.executable,
  • , tmp_path): result = subprocess.run( [sys.executable, "-m", "apcore_cli", "--extensi
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: aiperceivable.com>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 2.5

Git history flags: Repository has zero stars and zero forks

  • Repository has zero stars and zero forks
⚠ 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 apcore-cli 
Create a mini-application called 'AI-Chat' which leverages the 'apcore-cli' package to enable users to interact with AI-perceivable modules via a command-line interface. This application should allow users to input natural language queries and receive responses processed through various AI modules available via the apcore-cli package. Here’s a detailed breakdown of the project requirements:

1. **Setup**: Install and configure the apcore-cli package within your Python environment. Ensure that the necessary dependencies are installed as well.
2. **User Interface**: Develop a simple CLI interface where users can type their queries. The interface should be user-friendly and provide clear instructions on how to use it.
3. **Query Processing**: Implement functionality to process user inputs through the apcore-cli. Users should be able to specify which AI module they want to use for processing their query (e.g., sentiment analysis, text summarization).
4. **Response Handling**: Once the query is processed by the selected AI module, display the results back to the user in a readable format. Consider adding options for formatting the output (text, JSON, etc.).
5. **Customizability**: Allow users to customize the behavior of the AI modules if possible. For example, users could adjust parameters like verbosity level, model settings, etc.
6. **Error Handling**: Implement robust error handling to manage any issues that arise during the execution of queries or when interacting with the apcore-cli package.
7. **Documentation**: Provide clear documentation on how to install, configure, and use the 'AI-Chat' application. Include examples of different types of queries and expected outputs.
8. **Testing**: Write tests to ensure that the application works correctly under various conditions, including edge cases and potential errors.

By completing this project, you will have a fully functional CLI tool that showcases the capabilities of the apcore-cli package and provides a practical way for users to interact with AI modules directly from the terminal.

💬 Discussion Feed

Leave a comment

No discussion yet. Be the first to share your thoughts!