CVE-2026-61868
ImageMagick vulnerability analysis and mitigation

Overview

CVE-2026-61868 is a memory leak vulnerability in the YUV decoder of ImageMagick that occurs when opening a blob fails. Affected versions include ImageMagick before 7.1.2-26 (7.x branch) and 6.9.x before 6.9.13-51. The vulnerability was published on July 15, 2026, with the GitHub Security Advisory (GHSA-h7f2-f9cc-h2gv) authored by maintainer dlemstra on June 26, 2026. It carries a CVSS v3.1 base score of 3.7 (Low) and a CVSS v4.0 base score of 6.3 (Medium) (GitHub Advisory, Github Advisory DB).

Technical details

The root cause is classified as CWE-401 (Missing Release of Memory after Effective Lifetime): when the YUV decoder in ImageMagick attempts to open a blob and the operation fails, allocated memory is not properly released, resulting in a memory leak (GitHub Advisory). The attack vector is network-based, requiring no privileges or user interaction, but with high attack complexity and specific attack requirements (e.g., the blob open must fail under particular conditions). An attacker can repeatedly submit specially crafted or malformed YUV image files to a service backed by a vulnerable ImageMagick version, causing cumulative memory exhaustion over time (Github Advisory DB). No public proof-of-concept exploit code has been identified as of the disclosure date.

Impact

The sole impact of this vulnerability is availability degradation — there is no confidentiality or integrity impact. By repeatedly triggering the memory leak through malformed YUV image submissions, an unauthenticated remote attacker can exhaust system memory resources, potentially causing the ImageMagick process or the hosting service to become unresponsive or crash (denial of service) (GitHub Advisory, Github Advisory DB). The impact is limited to the vulnerable system itself, with no lateral movement or data exposure risk noted.

Exploitation steps

  1. Reconnaissance: Identify services or web applications that accept YUV image uploads and process them using a vulnerable version of ImageMagick (before 7.1.2-26 or 6.9.x before 6.9.13-51).
  2. Craft malformed YUV file: Prepare a YUV image file specifically designed to cause blob-open failure within ImageMagick's YUV decoder, triggering the error path where memory is not released.
  3. Repeated submission: Repeatedly upload or submit the malformed YUV file to the target service (e.g., via HTTP file upload endpoints), causing each request to leak a small amount of memory.
  4. Resource exhaustion: After sufficient repeated triggering, system memory is exhausted, causing the ImageMagick process or the hosting application to slow down, crash, or become unavailable (denial of service) (GitHub Advisory).

Indicators of compromise

  • Network: Repeated HTTP requests uploading YUV image files to image-processing endpoints from the same or rotating source IPs; unusually high volume of image processing requests in a short time window.
  • Logs: Application or web server logs showing repeated failed image processing attempts involving YUV files; error messages from ImageMagick related to blob open failures.
  • Process/System: Steadily increasing memory consumption by the ImageMagick process or the application invoking it without corresponding release; eventual out-of-memory (OOM) events or process crashes visible in system logs (e.g., /var/log/syslog, dmesg).
  • File System: Presence of multiple malformed or unusually small YUV files in upload directories.

Mitigation and workarounds

Update ImageMagick to version 7.1.2-26 or later for the 7.x branch, or to version 6.9.13-51 or later for the 6.9.x branch, as these releases contain the fix for the memory leak (GitHub Advisory). As interim mitigations, restrict network access to services that invoke ImageMagick, implement rate limiting on image processing endpoints to slow repeated exploitation attempts, and monitor system memory usage for signs of gradual exhaustion. Disabling YUV image processing if not required by the application is also an effective workaround.

Additional resources


SourceThis report was generated using AI

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