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CVE-2026-18602 – Unauthenticated Command Injection (RCE) – GL.iNet GL-MT3000 firmware 4.4.0 through

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Summary

CVE-2026-18602 is an unauthenticated OS command injection vulnerability (CWE-77) in the GL.iNet GL-MT3000 router. An attacker can reach the device’s RPC interface over the network and execute arbitrary commands as root without authentication or user interaction, making this a critical-severity remote code execution flaw.

Technical details

  • Root cause: The ovpn-client native plugin (ovpn-client.so, loaded via /usr/lib/oui-httpd/rpc/) embeds the attacker-supplied hostname value directly into a shell command via sprintf() without sanitization or escaping.
  • Trigger conditions: A crafted RPC request to the /cgi-bin/glc endpoint invoking the ovpn-client object’s get_recommend_config method, supplying a hostname value containing shell command-substitution syntax (e.g. $(...)).
  • Attack vector: Network (NETWORK). The /cgi-bin/glc RPC handler processes the request without any authentication check.
  • Impact: Injected commands execute with root privileges, resulting in full remote code execution and complete compromise of the device.

Affected software

  • GL.iNet GL-MT3000 firmware versions 4.4.0, 4.4.1, 4.4.2, 4.4.3, 4.4.4, and 4.4.5.

Severity

  • CVSS v3.1 base score: 9.8 (Critical) — vector CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H.
  • The CNA also assigned a CVSS v4.0 base score of 9.3 (Critical) — vector CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N.

Mitigation and recommended actions

  • Immediate: No fixed firmware version is identified in the CVE record. Monitor the GL.iNet security-updates page and upgrade GL-MT3000 devices to the latest available firmware as soon as a fix is published.
  • If no patch: Do not expose the router’s web/administration interface to the internet. Restrict access to the management interface (and the /cgi-bin/glc endpoint) to trusted internal networks via firewall rules or ACLs, and disable remote/WAN-side administration.

How IONIX identifies potentially affected assets

IONIX matches the following signals against data already collected when it crawled the asset; identifying the technology sends no request beyond that crawl.

  • Page title: GL.iNet, GL-MT3000, Beryl AX, GL.iNet Admin Panel

References

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How IONIX’s External Exposure Management Platform Detects and Validates
Zero-Days to Shrink MTTR

1

Map your entire attack surface (continously)

IONIX uses multi-factor discovery methods, including DNS analysis, certificate mapping, metadata inspection, and more, to automatically map every internet-facing asset across your environment. This includes cloud instances, third-party platforms, shadow IT, and even forgotten infrastructure that traditional tools miss.

2

Monitor for new CVEs

Dozens of threat intel feeds using agentic technology are continuously analyzed to detect the appearance of proof-of-concept code, exploit kits, and indicators of active targeting. IONIX goes further by applying AI to proactively evaluate whether emerging vulnerabilities are likely to be exploited, even before PoCs go public.

3

Identify Potential External Exposures

Not all CVEs matter. IONIX filters vulnerabilities by asking attacker-centric questions: Can it be reached from the internet? Does it require authentication? Is it being exploited in the wild? This dramatically reduces noise and focuses teams on threats that can actually be weaponized.

4

Create Safe, Scalable Exploit Validations

IONIX transforms real-world PoCs into safe, non-intrusive test payloads that can be run in production environments without disruption. These simulations are precisely targeted to the systems that are vulnerable, ensuring rapid validation without unnecessary load.

5

Execute Exploit Validations

By combining context about software stack, versioning, exposure status, and reachability, IONIX ensures that only the right payloads are executed against the right assets, maximizing efficiency and minimizing risk.

6

Drive Fast and Actionable Remediation

Results are routed through integrations with ticketing, SOAR, and SIEM tools. Issues are written in plain language, bundled into remediation clusters, and prioritized based on asset criticality, exploitability, and blast radius. This shortens mean time to remediation (MTTR) and empowers teams to act with confidence.

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