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CVE-2026-21490 (GCVE-0-2026-21490)

Vulnerability from cvelistv5 – Published: 2026-01-06 19:04 – Updated: 2026-01-06 19:59
VLAI
Title
iccDEV has heap buffer overflow in CIccTagLut16::Validate()
Summary
iccDEV provides a set of libraries and tools that allow for the interaction, manipulation, and application of International Color Consortium (ICC) color management profiles. A vulnerability present in versions prior to 2.3.1.2 affects users of the iccDEV library who process ICC color profiles. It results in heap buffer overflow in `CIccTagLut16::Validate()`. Version 2.3.1.2 contains a patch. No known workarounds are available.
SSVC
Exploitation: poc Automatable: no Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-01-06 19:59 UTC
CWE
Impacted products
Vendor Product Version CPE status
InternationalColorConsortium iccDEV Affected: < 2.3.1.2
guessed Create a notification for this product.
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

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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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