CVE-2026-48548: 
Nagios vulnerability analysis and mitigation

Overview

CVE-2026-48548 is a Cross-Site Request Forgery (CSRF) vulnerability in Nagios Core's cmd.cgi component where the CSRF protection mechanism incorrectly passes validation when the NagFormId cookie is absent. This flaw allows unauthenticated attackers to craft malicious cross-site POST requests that execute arbitrary Nagios commands on behalf of an authenticated user without their knowledge or consent. All versions of Nagios Core before 4.5.12 are affected. The vulnerability was published on August 26, 2026, with a fix released in version 4.5.12 (March 25, 2026). It carries a CVSS v3.1 score of 6.5 (Medium) and a CVSS v4.0 score of 6.9 (Medium) (Github Advisory, Feedly).

Technical details

The root cause is classified as CWE-352 (Cross-Site Request Forgery), stemming from a flawed CSRF token validation logic in cmd.cgi. Specifically, the CSRF protection mechanism — which relies on the NagFormId cookie — incorrectly passes validation when that cookie is entirely absent, rather than rejecting the request. This means an attacker can craft a cross-origin POST request without supplying any CSRF token, and the server will process it as legitimate. Exploitation requires the victim to be currently authenticated to Nagios and to interact with attacker-controlled content (e.g., visiting a malicious webpage or clicking a crafted link) (Github Advisory, Nagios Changelog).

Impact

Successful exploitation allows an attacker to execute arbitrary Nagios commands with the privileges of the authenticated victim user, resulting in a high integrity impact. An attacker could abuse this to disable monitoring checks, acknowledge alerts, schedule downtime, or manipulate host/service configurations — effectively undermining the integrity of the monitoring infrastructure. There is no direct confidentiality or availability impact per the CVSS scoring, but disruption of monitoring visibility could mask ongoing attacks or outages (Github Advisory, Feedly).

Exploitability

There is no public proof-of-concept exploit and no evidence of in-the-wild exploitation at this time, according to both NVD SSVC assessment and Feedly threat intelligence (Feedly). The vulnerability is not listed in the CISA Known Exploited Vulnerabilities (KEV) catalog. The EPSS score is approximately 0.139%, placing it in the 4th percentile for exploitation likelihood within 30 days (Github Advisory). Exploitation is not automatable as it requires active user interaction (a victim must be authenticated and interact with attacker-controlled content).

Exploitation steps

  1. Reconnaissance: Identify internet-facing or network-accessible Nagios Core instances running versions prior to 4.5.12 using tools like Shodan or Censys, or through internal network scanning.
  2. Identify target user: Determine or wait for an authenticated Nagios administrator or operator to be logged into the Nagios web interface.
  3. Craft malicious POST request: Create an HTML page or form that submits a cross-origin POST request to the target Nagios cmd.cgi endpoint (e.g., https://nagios.target.com/nagios/cgi-bin/cmd.cgi) with desired Nagios command parameters, deliberately omitting the NagFormId cookie.
  4. Deliver payload: Trick the authenticated Nagios user into visiting the attacker-controlled page (e.g., via phishing email, malicious link, or injected content on another site).
  5. Command execution: When the victim's browser submits the forged POST request, the Nagios server — due to the flawed CSRF validation — processes the request as legitimate, executing the specified Nagios command (e.g., disabling host checks, scheduling downtime, or acknowledging alerts) with the victim's privileges (Github Advisory, Feedly).

Indicators of compromise

  • Network: Unexpected cross-origin POST requests to /nagios/cgi-bin/cmd.cgi originating from unusual referrer domains or with missing/empty NagFormId cookie headers in web server access logs.
  • Logs: Nagios web server access logs showing POST requests to cmd.cgi with no NagFormId cookie value, particularly from IP addresses not associated with known administrators; unexpected Nagios command submissions (e.g., mass acknowledgements, bulk downtime scheduling, or check disabling) in the Nagios command log.
  • Application: Unexpected changes in Nagios monitoring state — such as hosts/services suddenly placed in downtime, checks disabled, or alerts acknowledged — without corresponding administrator activity.

Mitigation and workarounds

Upgrade Nagios Core to version 4.5.12 or later, which contains the fix for the CSRF cookie validation flaw in cmd.cgi (Nagios Changelog, Github Advisory). Note that version 4.5.13 and 4.5.14 include additional CSRF-related fixes and are recommended as the most current patched releases. As interim workarounds: restrict access to the Nagios web interface to trusted internal networks only; enforce SameSite=Strict or SameSite=Lax cookie policies at the web server or application level to mitigate cross-origin request risks; and educate Nagios users to avoid clicking untrusted links while authenticated to the Nagios interface (Feedly).

Community reactions

The vulnerability was credited to researcher SeungMyung Lee, who was acknowledged in the Nagios Core 4.5.12 and 4.5.13 changelogs for reporting CSRF cookie vulnerabilities in cmd.cgi (Nagios Changelog). VulnCheck published an advisory covering the issue. Community reaction has been limited, consistent with the moderate severity rating and absence of public exploit code.

Additional resources

Linux Distribution fix status

Fix availability across major Linux distributions and their releases.

Debian

Fixed

bookworm

nagios4: 4.4.6-4+deb12u1

Fixed

sid

nagios4: 4.5.12+ds-1

Fixed

trixie

nagios4: 4.4.6-4.1+deb13u1

Fixed

Ubuntu

Unknown

devel

nagios4

Unknown

focal (esm-apps)

nagios4

Unknown

jammy

nagios4

Unknown

jammy (esm-apps)

nagios4

Unknown

noble

nagios4

Unknown

noble (esm-apps)

nagios4

Unknown

resolute

nagios4

Unknown

resolute (esm-apps)

nagios4

Unknown

Source: This report was generated using AI

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