ml-explore CVE Vulnerabilities & Metrics

Focus on ml-explore vulnerabilities and metrics.

Last updated: 03 Dec 2025, 23:25 UTC

About ml-explore Security Exposure

This page consolidates all known Common Vulnerabilities and Exposures (CVEs) associated with ml-explore. We track both calendar-based metrics (using fixed periods) and rolling metrics (using gliding windows) to give you a comprehensive view of security trends and risk evolution. Use these insights to assess risk and plan your patching strategy.

For a broader perspective on cybersecurity threats, explore the comprehensive list of CVEs by vendor and product. Stay updated on critical vulnerabilities affecting major software and hardware providers.

Global CVE Overview

Total ml-explore CVEs: 2
Earliest CVE date: 21 Nov 2025, 19:16 UTC
Latest CVE date: 21 Nov 2025, 19:16 UTC

Latest CVE reference: CVE-2025-62609

Rolling Stats

30-day Count (Rolling): 2
365-day Count (Rolling): 2

Calendar-based Variation

Calendar-based Variation compares a fixed calendar period (e.g., this month versus the same month last year), while Rolling Growth Rate uses a continuous window (e.g., last 30 days versus the previous 30 days) to capture trends independent of calendar boundaries.

Variations & Growth

Month Variation (Calendar): 0%
Year Variation (Calendar): 0%

Month Growth Rate (30-day Rolling): 0.0%
Year Growth Rate (365-day Rolling): 0.0%

Monthly CVE Trends (current vs previous Year)

Annual CVE Trends (Last 20 Years)

Critical ml-explore CVEs (CVSS ≥ 9) Over 20 Years

CVSS Stats

Average CVSS: 0.0

Max CVSS: 0

Critical CVEs (≥9): 0

CVSS Range vs. Count

Range Count
0.0-3.9 2
4.0-6.9 0
7.0-8.9 0
9.0-10.0 0

CVSS Distribution Chart

Top 5 Highest CVSS ml-explore CVEs

These are the five CVEs with the highest CVSS scores for ml-explore, sorted by severity first and recency.

All CVEs for ml-explore

CVE-2025-62609 ml-explore vulnerability CVSS: 0 21 Nov 2025, 19:16 UTC

MLX is an array framework for machine learning on Apple silicon. Prior to version 0.29.4, there is a segmentation fault in mlx::core::load_gguf() when loading malicious GGUF files. Untrusted pointer from external gguflib library is dereferenced without validation, causing application crash. This issue has been patched in version 0.29.4.

CVE-2025-62608 ml-explore vulnerability CVSS: 0 21 Nov 2025, 19:16 UTC

MLX is an array framework for machine learning on Apple silicon. Prior to version 0.29.4, there is a heap buffer overflow in mlx::core::load() when parsing malicious NumPy .npy files. Attacker-controlled file causes 13-byte out-of-bounds read, leading to crash or information disclosure. This issue has been patched in version 0.29.4.