CVE-2026-96395 (GCVE-0-2026-96395)

Vulnerability from cvelistv5 – Published: 2026-10-09 12:40 – Updated: 2026-10-09 16:47
VLAI
Summary
The Affinity by Canva app for macOS before 3.3.1 (October 2026 release) did not perform adequate bounds checking 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, including memory addresses, in the rendered thumbnail or preview image.
SSVC
Exploitation: none Automatable: no Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-10-09 16:15 UTC
CWE
Impacted products
Vendor Product Version
canva affinity Affected: 0 , < 3.3.1 (semver)
    cpe:2.3:a:canva:affinity:*:*:*:*:*:macos:*:*
Create a notification for this product.
Credits
Show details on NVD website

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Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.

Sightings

Author Source Type Date Other

Nomenclature

  • Seen: The vulnerability was mentioned, discussed, or observed by the user.
  • Confirmed: The vulnerability has been validated from an analyst's perspective.
  • Published Proof of Concept: A public proof of concept is available for this vulnerability.
  • Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
  • Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
  • Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
  • Not confirmed: The user expressed doubt about the validity of the vulnerability.
  • Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.

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Related by attack behaviour

Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.


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