CVE-2025-43264: macOS Sequoia Buffer Overflow Vulnerability

CVE-2025-43264 Overview

CVE-2025-43264 is a memory corruption vulnerability in macOS Sequoia that occurs when processing maliciously crafted images. The vulnerability stems from improper memory handling within the image processing components of the operating system. An attacker could exploit this flaw to corrupt process memory, potentially leading to arbitrary code execution or system compromise.

Critical Impact
Processing a maliciously crafted image may corrupt process memory, potentially enabling attackers to execute arbitrary code with the privileges of the targeted application.

Affected Products

macOS Sequoia versions prior to 15.6

Discovery Timeline

2026-04-02 - CVE CVE-2025-43264 published to NVD
2026-04-02 - Last updated in NVD database

Technical Details for CVE-2025-43264

Vulnerability Analysis

This vulnerability is classified under CWE-119 (Improper Restriction of Operations within the Bounds of a Memory Buffer), indicating that the flaw involves operations that exceed defined memory boundaries during image processing. When macOS Sequoia processes a specially crafted image file, the system fails to properly validate memory boundaries, leading to memory corruption.

The vulnerability requires user interaction—specifically, the victim must open or process a malicious image file. This could occur through various attack vectors including malicious email attachments, compromised websites serving malformed images, or files shared through messaging applications.

Root Cause

The root cause lies in improper memory handling within the image parsing and rendering components of macOS Sequoia. When the system encounters a maliciously crafted image with unexpected or malformed data structures, the image processing routines fail to properly validate input boundaries before performing memory operations. This allows an attacker-controlled image to write data outside of allocated memory regions, corrupting adjacent memory structures.

Attack Vector

The attack vector is network-based, meaning an attacker can deliver the malicious payload remotely without requiring prior access to the target system. The most likely attack scenarios include:

Email-based attacks: Sending malicious image attachments that trigger the vulnerability when previewed or opened
Web-based attacks: Hosting malformed images on websites that corrupt memory when loaded by the victim's browser
File sharing attacks: Distributing malicious images through messaging apps or file-sharing services

The vulnerability mechanism involves specially crafted image files that exploit insufficient boundary checking in the image processing pipeline. When such an image is processed, the malformed data causes memory operations to exceed their intended boundaries, corrupting process memory and potentially allowing arbitrary code execution.

For technical details regarding this vulnerability, refer to the Apple Support Article.

Detection Methods for CVE-2025-43264

Indicators of Compromise

Unexpected application crashes when processing or viewing image files
Anomalous memory usage patterns in image rendering processes
System logs indicating memory corruption errors in graphics or image processing services
Suspicious image files with malformed headers or unexpected data structures

Detection Strategies

Monitor for abnormal crashes in image processing applications and system services
Implement endpoint detection rules to identify suspicious image file characteristics
Deploy memory protection monitoring to detect out-of-bounds memory access attempts
Review system logs for memory corruption indicators related to image handling

Monitoring Recommendations

Enable crash reporting and analyze crash dumps for memory corruption signatures
Monitor network traffic for delivery of unusually structured image files
Implement file integrity monitoring on systems processing user-submitted images
Track image processing service behavior for anomalous resource consumption

How to Mitigate CVE-2025-43264

Immediate Actions Required

Update all macOS Sequoia systems to version 15.6 or later immediately
Exercise caution when opening image files from untrusted sources
Disable automatic image preview features in email clients until patched
Implement network-level filtering for potentially malicious image files

Patch Information

Apple has addressed this vulnerability in macOS Sequoia version 15.6 with improved memory handling. The fix implements proper boundary validation during image processing operations to prevent memory corruption. Organizations should prioritize deployment of this update across all affected systems.

For official patch details and download information, refer to the Apple Support Article.

Workarounds

Restrict automatic image loading in email clients and web browsers
Implement application sandboxing to limit the impact of potential exploitation
Use network security appliances to scan and filter incoming image files
Configure systems to require explicit user approval before processing images from external sources

Organizations unable to immediately apply the patch should implement defense-in-depth measures including enhanced monitoring, user awareness training regarding suspicious attachments, and network-level content filtering.