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CVE-2026-35549 (GCVE-0-2026-35549)

Vulnerability from cvelistv5 – Published: 2026-04-03 05:00 – Updated: 2026-04-03 14:34
VLAI
Summary
An issue was discovered in MariaDB Server before 11.4.10, 11.5.x through 11.8.x before 11.8.6, and 12.x before 12.2.2. If the caching_sha2_password authentication plugin is installed, and some user accounts are configured to use it, a large packet can crash the server because sha256_crypt_r uses alloca.
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 2026-04-03 14:33 UTC
CWE
  • CWE-789 - Memory Allocation with Excessive Size Value
Assigner
References
Impacted products
Vendor Product Version CPE status
MariaDB MariaDB Affected: 0 , < 11.4.10 (semver)
Affected: 11.5.0 , < 11.8.6 (semver)
Affected: 12.0.0 , < 12.2.2 (semver)
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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.