🐛 severity mapping, ✨ defender performance improvement

[manuel-sommer]

No description provided.

[dryrunsecurity]

Hi there 👋, @DryRunSecurity here, below is a summary of our analysis and findings.

DryRun Security	Status	Findings
Configured Codepaths Analyzer	✅	0 findings
Sensitive Files Analyzer	✅	0 findings
AppSec Analyzer	✅	0 findings
Authn/Authz Analyzer	✅	0 findings
Secrets Analyzer	✅	0 findings

Note

🟢 Risk threshold not exceeded.

Change Summary (click to expand)

The following is a summary of changes in this pull request made by me, your security buddy 🤖. Note that this summary is auto-generated and not meant to be a definitive list of security issues but rather a helpful summary from a security perspective.

Summary:

The code changes in this pull request are focused on improving the reliability and robustness of the MSDefenderParser class, which is responsible for parsing and processing findings from Microsoft Defender security scans. The key changes include more efficient handling of machine information and ensuring that the severity of findings is properly classified. These improvements are important from an application security perspective, as they enhance the ability to accurately correlate vulnerability data with the corresponding machine information and prioritize remediation efforts based on the severity of the identified vulnerabilities.

Files Changed:

• dojo/tools/ms_defender/parser.py: The changes in this file are related to the MSDefenderParser class, which is responsible for parsing and processing findings from Microsoft Defender security scans. The key changes include:

  1. Vulnerability and Machine Data Handling: The code was modified to store machine information in a dictionary (machines) instead of a list, allowing for more efficient lookup of machine data by the machineId when processing vulnerabilities.

  2. Severity Handling: The severity_check function was added to ensure that the severity of a finding is always one of the expected values ('Informational', 'Low', 'Medium', 'High', 'Critical'). If the severity value from the input data is not one of these, it is set to 'Informational'.

These changes are focused on improving the reliability and robustness of the parser, which is an important component for integrating security findings into a security management or vulnerability management system. The ability to accurately correlate vulnerability data with the corresponding machine information and properly classify the severity of findings are crucial for effective security analysis and prioritization of remediation efforts.

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[mtesauro]

Approved