CVE-2022-31068 (GCVE-0-2022-31068)

Vulnerability from cvelistv5 – Published: 2022-06-28 17:50 – Updated: 2025-04-23 18:05
VLAI
Title
Sensitive Data Exposure on Refused Inventory Files in GLPI
Summary
GLPI is a Free Asset and IT Management Software package, Data center management, ITIL Service Desk, licenses tracking and software auditing. In affected versions all GLPI instances with the native inventory used may leak sensitive information. The feature to get refused file is not authenticated. This issue has been addressed in version 10.0.2 and all affected users are advised to upgrade.
SSVC
Exploitation: none Automatable: yes Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-04-23 15:53 UTC
CWE
  • CWE-200 - Exposure of Sensitive Information to an Unauthorized Actor
References
Impacted products
Vendor Product Version CPE status
glpi-project glpi Affected: >=10.0.0, < 10.0.2
guessed Create a notification for this product.
Show details on NVD website

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}



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Tags
Taxonomy of the tags.


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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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