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CVE-2023-32284 (GCVE-0-2023-32284)

Vulnerability from cvelistv5 – Published: 2023-09-25 15:22 – Updated: 2025-11-04 19:16
VLAI
Summary
An out-of-bounds write vulnerability exists in the tiff_planar_adobe functionality of Accusoft ImageGear 20.1. A specially crafted malformed file can lead to memory corruption. An attacker can provide a malicious file to trigger this vulnerability.
Severity
8.1 (High)
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:H
SSVC
Exploitation: poc Automatable: no Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-02-27 20:32 UTC
CWE
  • CWE-119 - Improper Restriction of Operations within the Bounds of a Memory Buffer
Assigner
References
Impacted products
Vendor Product Version CPE status
Accusoft ImageGear Affected: 20.1
guessed Create a notification for this product.
Credits
Discovered by Emmanuel Tacheau of Cisco Talos.
Show details on NVD website
To clipboard 

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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.


Detection rules are retrieved from Rulezet.


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.