argus-redact

v0.6.11 suspicious
7.0
High Risk

Encrypt PII, not meaning. Locally.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits significant shell and credential risks, with potential for external script execution and credential harvesting. While there are no clear signs of malicious intent, the combination of these risks suggests caution.

  • High shell risk due to subprocess.run usage
  • High credential risk from potential sensitive file access
Per-check LLM notes
  • Network: The network calls appear to be part of an API interaction pattern which could be legitimate, but the destination URL is not specified, raising some concern.
  • Shell: Executing external scripts via subprocess.run can introduce significant risks, including potential code injection and privilege escalation if not properly sanitized.
  • Obfuscation: No obfuscation patterns detected in the code.
  • Credentials: Potential risk of credential harvesting due to redirection and reading sensitive files like /etc/passwd and ~/.ssh/id_rsa.
  • Metadata: The maintainer has only one package, suggesting a new or less active account which could indicate potential risk.

📦 Package Quality Overall: Medium (6.2/10)

✦ High Test Suite 9.0

Test suite present — 1 test file(s) found

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

Some documentation present

  • 1 documentation file(s) (e.g. local-cli-proxy.py)
  • Detailed PyPI description (18793 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

  • 89 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 100 commits in wan9yu/argus-redact
  • Two distinct contributors found

🔬 Heuristic Checks

⚠ Outbound Network Calls score 4.5

Found 3 network call pattern(s)

  • try: resp = requests.post( f"{self._base_url}/api/generate",
  • gen(): async with httpx.AsyncClient(timeout=300) as client: async with client.st
  • streaming path async with httpx.AsyncClient(timeout=300) as client: upstream_resp = await client
✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 2.0

Found 1 shell execution pattern(s)

  • c_docs_version.py" return subprocess.run( [sys.executable, str(script_in_fake_repo), *args],
⚠ Credential Harvesting score 5.0

Found 2 credential access pattern(s)

  • mlink could redirect to ``/etc/passwd``, ``~/.ssh/id_rsa``, etc. POSIX: uses ``O_NOFOLLOW``
  • edirect to ``/etc/passwd``, ``~/.ssh/id_rsa``, etc. POSIX: uses ``O_NOFOLLOW`` — read fails with `
✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository wan9yu/argus-redact appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Wang Yu" 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 argus-redact 
Create a Python-based mini-application called 'PrivacyGuard' that leverages the 'argus-redact' package to protect Personally Identifiable Information (PII) within text documents while preserving the overall meaning and readability of the content. This application will serve as a tool for individuals and organizations to safeguard sensitive information in their documents without compromising the context.

Step-by-Step Development Plan:
1. **Setup Environment**: Install necessary packages including 'argus-redact', 'pandas' for data handling, and 'tkinter' for a simple GUI interface.
2. **Input Handling**: Design a function that accepts text input from a file or clipboard. Ensure the application supports common text formats like .txt, .docx, and .pdf.
3. **Identification & Redaction**: Use 'argus-redact' to identify and encrypt PII such as names, addresses, phone numbers, and email addresses within the text. Ensure that the encryption does not alter the sentence structure or overall meaning.
4. **Output Generation**: Develop functionality to save the redacted text back into a new file or clipboard. Provide options to choose output format and location.
5. **User Interface**: Implement a user-friendly GUI using 'tkinter'. The interface should allow users to easily upload files, view the redacted text, and download the result.
6. **Testing & Validation**: Write test cases to validate the redaction process on various types of documents and ensure no PII leaks.
7. **Documentation**: Prepare comprehensive documentation explaining how to use PrivacyGuard, including installation instructions, usage examples, and API references if applicable.

Suggested Features:
- Real-time preview of redacted text within the GUI.
- Option to specify which types of PII to redact (e.g., only names, only emails).
- Support for batch processing multiple documents at once.
- Integration with cloud storage services for easy document sharing post-redaction.
- Detailed logs of redaction activities for audit purposes.

How 'argus-redact' is Utilized:
- 'argus-redact' will be integrated into the identification and redaction steps where it will scan through the uploaded text, detect PII, and apply local encryption techniques to mask these details. The package ensures that the encrypted form of PII retains enough context so that the overall meaning and flow of the text remain intact.

💬 Discussion Feed

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