CVE-2026-10819 Mattermost CVE debrief

Who should care

Administrators and users of Mattermost versions 11.6.x <= 11.6.5, 10.11.x <= 10.11.20, 11.8.x <= 11.8.1, and 11.7.x <= 11.7.4 should apply patches or mitigations to prevent potential denial of service attacks. Additionally, security teams and vulnerability management teams should review the vulnerability and assess the risk to their deployments.

Technical summary

The vulnerability exists due to Mattermost's failure to limit the number of frames and enforce the file size cap on animated GIF uploads. An authenticated attacker can exploit this by uploading a crafted animated GIF as a custom emoji, potentially causing a denial of service. This issue affects Mattermost versions 11.6.x <= 11.6.5, 10.11.x <= 10.11.20, 11.8.x <= 11.8.1, and 11.7.x <= 11.7.4. The vulnerability can be mitigated by applying patches or updates to affected Mattermost versions.

Defensive priority

Medium

Recommended defensive actions

• Apply patches or updates to affected Mattermost versions
• Implement compensating controls to monitor and limit large file uploads
• Enforce strict access controls and authentication mechanisms
• Review compensating controls for exposed systems while remediation is scheduled and verified
• Check relevant monitoring, detection, and logs for exposed assets that need extra review
• 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 2026-07-27T15:16:46.770Z and last modified on 2026-07-27T20:37:16.927Z. The NVD entry is currently Awaiting Analysis. This vulnerability affects Mattermost versions 11.6.x <= 11.6.5, 10.11.x <= 10.11.20, 11.8.x <= 11.8.1, and 11.7.x <= 11.7.4. The vulnerability allows an authenticated attacker to cause a denial of service via a crafted animated GIF uploaded as a custom emoji due to insufficient limits on the number of frames and file size. Evidence of exploitation is limited, and defenders should verify affected deployments and apply patches or mitigations.

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.