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CVE-2026-90681 (GCVE-0-2026-90681)

Vulnerability from cvelistv5 – Published: 2026-09-14 04:15 – Updated: 2026-09-14 14:58
VLAI
Title
Matthias-Wandel jhead EXIF Parsing exif.c Get16u out-of-bounds
Summary
A weakness has been identified in Matthias-Wandel jhead up to 3.3. This affects the function Get16u of the file exif.c of the component EXIF Parsing. This manipulation causes out-of-bounds read. The attack requires local access. The exploit has been made available to the public and could be used for attacks. The project was informed of the problem early through an issue report but has not responded yet.
SSVC
Exploitation: poc Automatable: no Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-09-14 14:58 UTC
CWE
Impacted products
Vendor Product Version CPE status
Matthias-Wandel jhead Affected: 3.0
Affected: 3.1
Affected: 3.2
Affected: 3.3
    cpe:2.3:a:matthias-wandel:jhead:*:*:*:*:*:*:*:*
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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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