aisquare-pipe

v0.1.0 suspicious
7.0
High Risk

Universal anything-to-anything connector framework

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits significant credential risk and moderate obfuscation risk, suggesting potential malicious intent. While other risks are lower, the combination of accessing sensitive system files and obfuscation techniques warrants further investigation.

  • High credential risk due to attempted access of sensitive system files
  • Moderate obfuscation risk indicated by base64 decoding
Per-check LLM notes
  • Network: The observed network calls appear to be related to OAuth token acquisition and file uploads, which could be legitimate if the package requires authentication and data transfer functionalities.
  • Shell: No shell execution patterns were detected.
  • Obfuscation: Base64 decoding is commonly used for various purposes and alone does not indicate malicious activity, but the pattern suggests potential obfuscation.
  • Credentials: Reading files like '../../etc/passwd' indicates an attempt to access sensitive system files, which is highly suspicious and likely indicative of credential harvesting.
  • Metadata: The package is new with limited maintainer history and no associated GitHub repository, which raises some suspicion but not enough to conclusively indicate malice.

📦 Package Quality Overall: Low (4.4/10)

✦ High Test Suite 9.0

Test suite present — 30 test file(s) found

  • Test runner config found: pyproject.toml
  • Test runner config found: conftest.py
  • Test runner config found: pyproject.toml
  • 30 test file(s) detected (e.g. conftest.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (3704 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

  • 135 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 4.5

Found 3 network call pattern(s)

  • "].rstrip("/") response = requests.post( f"https://{auth_server}/oauth/token", data=
  • } resp = requests.put( upload_url, headers=chunk_h
  • "].rstrip("/") response = requests.post( f"{instance_url}/services/oauth2/token", da
⚠ Code Obfuscation score 4.0

Found 2 obfuscation pattern(s)

  • ntract.pdf" decoded = base64.b64decode(envelope_def.documents[0].document_base64) assert de
  • rgs.args[0] decoded = base64.b64decode(envelope_def.documents[0].document_base64) assert de
✓ Shell / Subprocess Execution

No shell execution patterns detected

⚠ Credential Harvesting score 2.5

Found 1 credential access pattern(s)

  • client.read_file("../../etc/passwd") def test_traversal_blocked_on_write(self, sample_con
✓ 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 4.0

2 maintainer concern(s) found

  • Only one version has ever been released — brand new package
  • Author "A-Square" 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 aisquare-pipe 
Create a mini-application called 'DataConnector' that leverages the 'aisquare-pipe' package to serve as a universal data connector between different services. This application should allow users to easily connect various data sources and destinations, such as databases, APIs, cloud storage services, and more, without needing to write complex integration code.

The application should have the following core functionalities:
1. **User Interface**: A simple and intuitive web-based UI where users can select their data source and destination types from a dropdown menu.
2. **Configuration Wizard**: A wizard-like interface guiding users through setting up connections, including entering necessary credentials and specifying any required parameters.
3. **Real-Time Data Transfer**: Once configured, the application should support real-time data transfer between selected sources and destinations.
4. **Error Handling & Logging**: Robust error handling mechanisms to manage connection issues or data transfer problems, along with logging capabilities to record all actions and errors.
5. **Custom Pipe Creation**: Users should be able to create custom pipes using 'aisquare-pipe', allowing them to define their own transformations and processing steps during data transfer.
6. **Security Measures**: Ensure secure data handling practices, such as encrypting data in transit and at rest, and securely managing user credentials.

To utilize 'aisquare-pipe', you will need to install it via pip and then use its framework to define connectors for each supported service type. Each connector will act as a bridge between the chosen source and destination, leveraging 'aisquare-pipe's ability to handle various data formats and protocols seamlessly. Additionally, explore 'aisquare-pipe's documentation for advanced features like data transformation pipelines and event-driven processing.

💬 Discussion Feed

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