CVE-2026-23924 (GCVE-0-2026-23924)

Vulnerability from cvelistv5 – Published: 2026-03-24 18:30 – Updated: 2026-03-25 19:25
VLAI
Title
Agent 2 Docker plugin arbitrary file read via Docker API injection
Summary
Zabbix Agent 2 Docker plugin does not properly sanitize the 'docker.container_info' parameters when forwarding them to the Docker daemon. An attacker capable of invoking Agent 2 can read arbitrary files from running Docker containers by injecting them via the Docker archive API.
Severity
6.1 (Medium)
CVSS:4.0/AV:N/AC:L/AT:N/PR:H/UI:N/VC:N/VI:N/VA:N/SC:H/SI:N/SA:N
SSVC
Exploitation: none Automatable: no Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-03-25 19:25 UTC
CWE
  • CWE-88 - Improper Neutralization of Argument Delimiters in a Command ('Argument Injection')
Assigner
Zabbix CNA under the mitre root
CNA scorecard B 79/100 over 20 records in the last 180 days details
References
Impacted products
Vendor Product Version CPE status
Zabbix Zabbix Affected: 6.0.0 , ≤ 6.0.43 (git)
Affected: 7.0.0 , ≤ 7.0.22 (git)
Affected: 7.4.0 , ≤ 7.4.6 (git)
guessed Create a notification for this product.
Credits
Zabbix wants to thank kelsier from clocktwice.com for submitting this report on the HackerOne bug bounty platform.
Show details on NVD website
To clipboard 

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  • 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.
Vulnerability timeline

Sightings and recorded dates, grouped by day · UTC

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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.