keplerwallpapers CVE Vulnerabilities & Metrics

Focus on keplerwallpapers vulnerabilities and metrics.

Last updated: 16 Apr 2026, 22:25 UTC

About keplerwallpapers Security Exposure

This page consolidates all known Common Vulnerabilities and Exposures (CVEs) associated with keplerwallpapers. 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 keplerwallpapers CVEs: 1
Earliest CVE date: 21 Mar 2026, 16:16 UTC
Latest CVE date: 21 Mar 2026, 16:16 UTC

Latest CVE reference: CVE-2019-25576

Rolling Stats

30-day Count (Rolling): 1
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): 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 keplerwallpapers 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 keplerwallpapers CVEs

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

All CVEs for keplerwallpapers

Kepler Wallpaper Script 1.1 contains an SQL injection vulnerability that allows unauthenticated attackers to execute arbitrary SQL queries by injecting malicious code into the category parameter. Attackers can send GET requests to the category endpoint with URL-encoded SQL UNION statements to extract database information including usernames, database names, and MySQL version details.