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CVE-2024-52973 (GCVE-0-2024-52973)

Vulnerability from cvelistv5 – Published: 2025-01-21 11:04 – Updated: 2025-01-21 16:25
VLAI
Title
Kibana allocation of resources without limits or throttling leads to crash
Summary
An allocation of resources without limits or throttling in Kibana can lead to a crash caused by a specially crafted request to /api/log_entries/summary. This can be carried out by users with read access to the Observability-Logs feature in Kibana.
Severity
6.5 (Medium)
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
SSVC
Exploitation: none Automatable: no Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-01-21 16:25 UTC
CWE
  • CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
References
Impacted products
Vendor Product Version CPE status
Elastic Kibana Affected: 7.17.0, 8.0.0 , < 7.17.23, 8.14.2 (semver)
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.


Detection rules are retrieved from Rulezet.


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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.