This code block performs a security analysis of a project using the Snyk command-line interface (CLI) and then uses an Isolation Forest model to detect potential anomalies in the reported vulnerabilities. The goal is to automate a security check that fails the build process if critical vulnerabilities are found or if the vulnerability characteristics are deemed anomalous by the machine learning model.
Here's a breakdown of the key parts:
Library Imports and Setup The code starts by importing necessary libraries.
json: For parsing the JSON output from the Snyk CLI. subprocess: To run the Snyk CLI command from within the notebook. requests: To make HTTP requests, specifically to get package age information. numpy: For numerical operations, particularly for handling the feature data for the Isolation Forest. IsolationForest from sklearn.ensemble: This is the machine learning model used for anomaly detection. os: To interact with the operating system, used here to potentially modify the system's PATH.