amox

v0.0.3 suspicious
6.0
Medium Risk

Schema on read based logging

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows low risks in direct malicious activities but has a high metadata risk due to its low popularity and new maintainer status. Additionally, it appears to be a typosquatting attempt targeting 'tox'.

  • High metadata risk
  • Typosquatting attempt
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package's functionality requires external communication.
  • Shell: No shell execution patterns detected, indicating no immediate signs of malicious shell command execution.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The low star and fork count, coupled with the maintainer's limited history on PyPI, suggest potential risk.
  • ⚠ Typosquatting target: tox

📦 Package Quality Overall: Medium (5.2/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • Test runner config found: pyproject.toml
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (1456 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 7.0

Partial type annotation coverage

  • Classifier: Typing :: Typed
  • 25 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 7 commits in kmontocam/amox
  • Two distinct contributors found

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

⚠ Typosquatting score 9.0

Possible typosquat of: nox, tox, amqp

  • "amox" is 2 edit(s) from "nox"
  • "amox" is 2 edit(s) from "tox"
  • "amox" is 2 edit(s) from "amqp"
✓ Registered Email Domain

Email domain looks legitimate: kmontocam.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 2.0

1 maintainer concern(s) found

  • Author "Kevin Montoya" 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 amox 
Create a Python-based mini-application named 'LogAnalyzer' that leverages the 'amox' library to perform schema-on-read logging for various types of log files. This tool will allow users to upload different log file formats (such as JSON, CSV, and plain text), and it will dynamically infer the schema of each file during the reading process. The application should then provide several useful functionalities:

1. **Schema Inference**: Automatically detect and display the schema of the uploaded log file.
2. **Log Parsing**: Parse the log entries according to the inferred schema and categorize them.
3. **Filtering Options**: Allow users to filter logs based on specific criteria such as timestamp range, log level, or custom keywords.
4. **Visualization**: Provide basic visualizations of log data, such as time-series graphs of log entries over time or pie charts showing distribution of log levels.
5. **Export Functionality**: Enable users to export parsed and filtered log data into different formats (JSON, CSV).

The application should have a simple command-line interface for ease of use and integration into existing workflows. Use the 'amox' package to handle the schema-on-read functionality for parsing and understanding the structure of the incoming log files. Additionally, include error handling to manage cases where the log files might not conform to expected formats.

💬 Discussion Feed

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