CVE-2026-62184 openwrt CVE debrief

Who should care

Users of luci-app-banip should be aware of this vulnerability and take steps to mitigate it. Affected operators should review their deployments and consider updating to the latest version of luci-app-banip. Vulnerability management teams should prioritize this vulnerability due to its high CVSS score of 8.7. Security teams should monitor logs for suspicious activity and implement input validation and sanitization for log inputs.

Technical summary

The luci-app-banip package contains a log parsing vulnerability. The awk-based parser extracts the first IPv4 address from log lines regardless of field position. This allows attackers to inject arbitrary IPs via attacker-controlled fields like usernames. An unauthenticated remote attacker can inject an IP address into the login username field, causing banIP to block the wrong target while the real attacker remains unblocked. The vulnerability is caused by the lack of proper input validation and sanitization in the log parsing mechanism.

Defensive priority

High

Recommended defensive actions

• Update to the latest version of luci-app-banip
• Implement input validation and sanitization for log inputs
• Monitor logs for suspicious activity
• Consider using a more robust log parsing solution
• Review compensating controls for exposed systems while remediation is scheduled and verified
• Track exceptions, retest remediated assets, and close the item only after evidence is documented
• Confirm whether affected product deployments exist in managed environments and assign an owner for follow-up

Evidence notes

The CVE record was published on 2026-07-13T22:16:49.310Z and has not been modified since then. The NVD entry is currently Received. There is limited information available about the vulnerability, and defenders should verify the affected scope and severity with the vendor. The CVE record does not provide specific details about the vulnerability, but it mentions that the awk-based parser extracts the first IPv4 address from log lines regardless of field position.

Sources and references

Methodology and review provenance

AI-assisted synthesis based on stored public vulnerability evidence. System validation, approval state, and publication status do not by themselves establish human review of this revision. PatchSiren helps prioritize defensive review and does not prove exposure or remediation on any system.