CVE-2026-61465 in ImageMagick
Summary
by MITRE • 07/11/2026
ImageMagick before 7.1.2-26 and 6.9.13-51 is missing a check for the allowed memory allocation limit in matrix-backed operations such as -canny. An attacker can supply a crafted image that causes ImageMagick to allocate more memory than permitted by the configured policy, resulting in a denial of service.
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Analysis
by VulDB Data Team • 07/11/2026
ImageMagick versions prior to 7.1.2-26 and 6.9.13-51 contain a critical memory allocation vulnerability that affects matrix-backed operations including the -canny edge detection feature. This flaw stems from insufficient validation of memory limits during image processing operations, allowing malicious actors to exploit the system through crafted input files. The vulnerability specifically targets the policy enforcement mechanisms that should restrict memory consumption during complex mathematical operations on image matrices. When an attacker provides a specially constructed image file, the software bypasses configured memory allocation limits and allocates excessive memory resources, potentially leading to system instability or complete denial of service conditions.
The technical nature of this vulnerability aligns with CWE-122, which describes insufficient memory protection mechanisms in software systems. The flaw operates at the intersection of resource management and input validation, where the application fails to enforce proper boundaries during mathematical operations on image data structures. During matrix-backed processing such as edge detection using -canny, ImageMagick performs calculations that require significant memory allocation for temporary data storage and computation results. The absence of checks against configured policy limits allows these operations to consume unlimited memory resources until system resources are exhausted.
This vulnerability impacts systems where ImageMagick is used for image processing, particularly in web applications, content management systems, or any environment where user-supplied images are processed without proper sanitization. Attackers can exploit this weakness by uploading maliciously crafted images that trigger the vulnerable code path during image analysis operations. The operational impact includes system resource exhaustion, application crashes, and potential service disruption for legitimate users. In high-traffic environments, such attacks could result in cascading failures affecting multiple services dependent on ImageMagick functionality.
Mitigation strategies should focus on immediate patching to versions 7.1.2-26 or 6.9.13-51 which contain the necessary memory limit enforcement. Additionally, administrators should implement strict resource limits through policy configurations that restrict memory allocation for image processing operations. The implementation of input validation and sanitization measures can help prevent malicious files from reaching the vulnerable code paths. Organizations should also consider deploying intrusion detection systems to monitor for unusual memory consumption patterns during image processing operations. This vulnerability demonstrates the importance of proper resource management in image processing libraries and aligns with ATT&CK technique T1499.004, which covers network disruption through resource exhaustion attacks against software applications.