CVE-2026-96394 in Affinity
Summary
by MITRE • 10/09/2026
The Affinity by Canva application for macOS before 3.3.1 (October 2026 release) did not validate image dimensions against the size of the pixel data when generating QuickLook thumbnails and previews of Affinity document files, leading to an out-of-bounds heap read. A threat actor could craft an Affinity document that, when displayed or previewed by a user in Finder, could disclose the contents of adjacent heap memory in the rendered thumbnail or preview image, or cause the thumbnail or preview extension to crash.
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Analysis
by VulDB Data Team • 10/09/2026
The vulnerability identified in Affinity by Canva for macOS prior to version 3.3.1 represents a critical security flaw rooted in improper input validation during the generation of QuickLook thumbnails and previews. This issue specifically affects how the application handles image dimensions relative to the actual size of pixel data within Affinity document files. When a user interacts with an Affinity file, such as by selecting it in Finder or opening its preview pane, the system invokes thumbnail generation routines that fail to verify whether the declared image dimensions are consistent with the allocated buffer for pixel data. This lack of validation creates a scenario where the application may attempt to read memory locations beyond the bounds of the intended heap allocation, resulting in an out-of-bounds heap read condition.
From a technical perspective, this flaw is classified under CWE-125, which denotes Out-of-Bounds Read vulnerabilities. The root cause lies in the absence of rigorous boundary checks before accessing array elements or buffer regions based on user-supplied metadata within the document file. In macOS environments, QuickLook extensions operate as separate processes that render previews for various file types. When an Affinity document is processed, the thumbnail generator reads pixel data to construct a visual representation. If the dimensions specified in the file header exceed the actual size of the embedded image data, the rendering engine continues reading from adjacent memory addresses on the heap. This behavior violates fundamental principles of safe memory management and exposes internal application state that was not intended for external consumption.
The operational impact of this vulnerability is significant due to its potential for information disclosure and service disruption. A threat actor can craft a malicious Affinity document containing carefully constructed metadata that triggers the out-of-bounds read when previewed by an unsuspecting user. Upon viewing such a file in Finder, the QuickLook extension may leak contents of adjacent heap memory into the rendered thumbnail or preview image. This could result in the exposure of sensitive data residing in nearby memory locations, potentially including cryptographic keys, authentication tokens, or other confidential information from the application's runtime environment. Furthermore, if the accessed memory regions are unmapped or protected, the operation can cause a segmentation fault, leading to the crash of the thumbnail extension process and degrading system stability for the user.
This vulnerability aligns with ATT&CK technique T1083, which covers File and Directory Discovery, as it exploits standard file browsing behaviors in macOS to execute malicious code paths without requiring direct execution by the victim. The attack vector is primarily local or remote via social engineering if a malicious document is distributed through email or web downloads. Once opened or previewed, the vulnerability activates automatically due to how QuickLook integrates with the Finder interface. This passive activation mechanism lowers the barrier for exploitation compared to vulnerabilities that require explicit user interaction beyond opening a file.
Mitigation strategies must focus on both immediate remediation and long-term defensive coding practices. The primary solution is to upgrade Affinity by Canva to version 3.3.1 or later, where this validation logic has been corrected to ensure image dimensions are strictly checked against pixel data size before rendering operations commence. For organizations deploying the software at scale, patch management protocols should be updated to prioritize this update given its potential for information leakage. Additionally, developers implementing similar preview functionalities in other applications should enforce strict input validation and implement bounds checking routines that verify array indices against allocated buffer sizes prior to access. Utilizing memory-safe languages or static analysis tools during development can further reduce the likelihood of such out-of-bounds errors occurring in future releases.