Focus on readarr vulnerabilities and metrics.
Last updated: 25 Nov 2025, 23:25 UTC
This page consolidates all known Common Vulnerabilities and Exposures (CVEs) associated with readarr. 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.
Total readarr CVEs: 1
Earliest CVE date: 27 Aug 2025, 16:15 UTC
Latest CVE date: 27 Aug 2025, 16:15 UTC
Latest CVE reference: CVE-2025-50983
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.
Month Variation (Calendar): 0%
Year Variation (Calendar): 0%
Month Growth Rate (30-day Rolling): 0.0%
Year Growth Rate (365-day Rolling): 0.0%
Average CVSS: 0.0
Max CVSS: 0
Critical CVEs (≥9): 0
| Range | Count |
|---|---|
| 0.0-3.9 | 1 |
| 4.0-6.9 | 0 |
| 7.0-8.9 | 0 |
| 9.0-10.0 | 0 |
These are the five CVEs with the highest CVSS scores for readarr, sorted by severity first and recency.
SQL Injection vulnerability exists in the sortKey parameter of the GET /api/v1/wanted/cutoff API endpoint in readarr 0.4.15.2787. The endpoint fails to properly sanitize user-supplied input, allowing attackers to inject and execute arbitrary SQL commands against the backend SQLite database. Sqlmap confirmed exploitation via stacked queries, demonstrating that the parameter can be abused to run arbitrary SQL statements. A heavy query was executed using SQLite's RANDOMBLOB() and HEX() functions to simulate a time-based payload, indicating deep control over database interactions.