CVE-2026-23934
Zabbix Server vulnerability analysis and mitigation

Overview

CVE-2026-23934 is a denial-of-service vulnerability in the Zabbix Frontend component, specifically in the validate.api.exists action. An authenticated user can send specially crafted HTTP requests to this endpoint, causing disproportionate CPU load on the Frontend web server. The vulnerability affects Zabbix versions 7.4.0 through 7.4.11, with a fix available in version 7.4.12. It carries a CVSS v4.0 base score of 5.1 (Medium) (Zabbix Advisory).

Technical details

The root cause is classified as CWE-405 (Asymmetric Resource Consumption / Amplification), where a low-cost attacker request triggers disproportionately high server-side CPU processing. The attack vector is adjacent network (AV:A), requires low privileges (an authenticated user account), and no user interaction. An attacker crafts specific HTTP requests targeting the validate.api.exists Frontend action, which causes the web server to consume excessive CPU resources relative to the input provided (Zabbix Advisory).

Impact

Successful exploitation results in degraded availability of the Zabbix Frontend web server due to excessive CPU consumption, potentially rendering the monitoring interface unresponsive or slow for legitimate users. There is no impact on confidentiality or integrity — the vulnerability is limited to an availability impact classified as Low at the vulnerable component level. Because Zabbix is a monitoring platform, disruption of its Frontend could impair visibility into infrastructure health during an attack (Zabbix Advisory).

Exploitability

No public proof-of-concept exploit code or in-the-wild exploitation has been reported as of the disclosure date. The NVD SSVC assessment indicates exploitation status as "none" and the vulnerability is not listed in the CISA Known Exploited Vulnerabilities catalog. The EPSS score is 0.0, reflecting a very low probability of near-term exploitation. Exploitation requires a valid authenticated session on the Zabbix Frontend, limiting the attack surface to users with existing credentials (Zabbix Advisory).

Exploitation steps

  1. Obtain credentials: Acquire valid Zabbix Frontend credentials (e.g., through phishing, credential stuffing, or use of a low-privileged account).
  2. Authenticate: Log in to the Zabbix Frontend web interface to obtain a valid session token or cookie.
  3. Craft malicious requests: Construct specifically crafted HTTP requests targeting the validate.api.exists Frontend action endpoint.
  4. Send repeated requests: Repeatedly send the crafted requests to the endpoint to amplify CPU load on the web server, exploiting the asymmetric resource consumption behavior.
  5. Achieve DoS: Sustain the request volume until the Frontend web server becomes unresponsive or severely degraded for legitimate users (Zabbix Advisory).

Indicators of compromise

  • Network: High volume of HTTP requests to the Zabbix Frontend validate.api.exists endpoint from a single authenticated session or IP address.
  • Logs: Zabbix Frontend access logs showing repeated, rapid requests to the validate.api.exists action with unusual or crafted parameters.
  • System: Sustained high CPU utilization on the Zabbix Frontend web server process (e.g., Apache/Nginx/PHP-FPM) without a corresponding increase in legitimate user activity.

Mitigation and workarounds

Zabbix has released version 7.4.12 as the fixed release for affected versions 7.4.0 through 7.4.11. Administrators should upgrade the Zabbix Frontend to version 7.4.12 or later as the primary remediation. No official workarounds are provided by the vendor; upgrading is the recommended and only documented mitigation (Zabbix Advisory).

Community reactions

The vulnerability was reported to Zabbix through the HackerOne bug bounty platform by researcher "kang999" and was acknowledged by Zabbix in their official issue tracker. No significant broader media coverage or notable community commentary has been identified beyond the vendor's advisory (Zabbix Advisory).

Additional resources


SourceThis report was generated using AI

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