xiangshan CVE Vulnerabilities & Metrics

Focus on xiangshan vulnerabilities and metrics.

Last updated: 16 Jan 2026, 23:25 UTC

About xiangshan Security Exposure

This page consolidates all known Common Vulnerabilities and Exposures (CVEs) associated with xiangshan. 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 xiangshan CVEs: 1
Earliest CVE date: 10 Dec 2025, 18:16 UTC
Latest CVE date: 10 Dec 2025, 18:16 UTC

Latest CVE reference: CVE-2025-63094

Rolling Stats

30-day Count (Rolling): 0
365-day Count (Rolling): 1

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): -100.0%
Year Variation (Calendar): 0%

Month Growth Rate (30-day Rolling): -100.0%
Year Growth Rate (365-day Rolling): 0.0%

Monthly CVE Trends (current vs previous Year)

Annual CVE Trends (Last 20 Years)

Critical xiangshan 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 1
4.0-6.9 0
7.0-8.9 0
9.0-10.0 0

CVSS Distribution Chart

Top 5 Highest CVSS xiangshan CVEs

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

All CVEs for xiangshan

CVE-2025-63094 xiangshan vulnerability CVSS: 0 10 Dec 2025, 18:16 UTC

XiangShan Nanhu V2 and XiangShan Kunmighu V3 were discovered to use speculative execution and indirect branch prediction, allowing attackers to access sensitive information via side-channel analysis of the data cache.