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CVE-2026-46862 (GCVE-0-2026-46862)

Vulnerability from cvelistv5 – Published: 2026-06-16 19:27 – Updated: 2026-06-17 14:52
VLAI
Summary
Vulnerability in the MySQL Router product of Oracle MySQL (component: Router: General). Supported versions that are affected are 8.4.0-8.4.9 and 9.0.0-9.7.0. Easily exploitable vulnerability allows unauthenticated attacker with network access via TLS to compromise MySQL Router. Successful attacks of this vulnerability can result in unauthorized ability to cause a hang or frequently repeatable crash (complete DOS) of MySQL Router. CVSS 3.1 Base Score 7.5 (Availability impacts). CVSS Vector: (CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H).
SSVC
Exploitation: none Automatable: yes Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-06-17 14:49 UTC
CWE
  • Easily exploitable vulnerability allows unauthenticated attacker with network access via TLS to compromise MySQL Router. Successful attacks of this vulnerability can result in unauthorized ability to cause a hang or frequently repeatable crash (complete DOS) of MySQL Router.
  • CWE-400 - Uncontrolled Resource Consumption
References
Impacted products
Vendor Product Version CPE status
Oracle Corporation MySQL Router Affected: 8.4.0 , ≤ 8.4.9 (custom)
Affected: 9.0.0 , ≤ 9.7.0 (custom)
    cpe:2.3:a:oracle:mysql_router:*:*:*:*:*:*:*:*
    cpe:2.3:a:oracle:mysql_router:*:*:*:*:*:*:*:*
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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.
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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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