CVE-2025-53113 (GCVE-0-2025-53113)

Vulnerability from cvelistv5 – Published: 2025-07-30 14:16 – Updated: 2025-07-30 19:30
VLAI
Title
GLPI technicians can access unauthorized information through external links
Summary
GLPI, which stands for Gestionnaire Libre de Parc Informatique, is a Free Asset and IT Management Software package, that provides ITIL Service Desk features, licenses tracking and software auditing. In versions 0.65 through 10.0.18, a technician can use the external links feature to fetch information on items they do not have the right to see. This is fixed in version 10.0.19.
SSVC
Exploitation: none Automatable: no Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-07-30 19:30 UTC
CWE
References
Impacted products
Vendor Product Version CPE status
glpi-project glpi Affected: >= 0.65, < 10.0.19
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

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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