CVE-2026-112269
Deferred Deferred - Pending Action

SGLang Mooncake Backend Memory Exhaustion via ZMQ

Vulnerability report for CVE-2026-112269, including description, CVSS score, EPSS score, affected products, exploitability, helpful resources, and attack-flow context.

Publication date: 2026-10-19

Last updated on: 2026-10-19

Assigner: VulnCheck

Description

SGLang through 0.5.22 with the Mooncake disaggregation backend accepts unauthenticated decode registration messages on the Prefill rank ZMQ PULL socket, allowing denial of service. Network-adjacent attackers can send many registrations with unique mooncake_session_id values and large nested-buffer frames to exhaust Prefill memory until the scheduler is OOM-killed.

CVSS Scores

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Meta Information

Published
2026-10-19
Last Modified
2026-10-19
Generated
2026-10-19
AI Q&A
2026-10-19
EPSS Evaluated
N/A
NVD
EUVD

Affected Vendors & Products

Showing 1 associated CPE
Vendor Product Version / Range
sgl-project sglang 0

Helpful Resources

Exploitability

CWE
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KEV
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CWE ID Description
CWE-770 The product allocates a reusable resource or group of resources on behalf of an actor without imposing any intended restrictions on the size or number of resources that can be allocated.

Attack-Flow Graph

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Executive Summary

CVE-2026-112269 is a memory exhaustion vulnerability in SGLang through version 0.5.22. It allows network-adjacent attackers to send unauthenticated decode registration messages with unique session IDs and large nested-buffer frames to the Prefill rank ZMQ PULL socket. This exhausts Prefill memory until the scheduler is terminated due to out-of-memory conditions, causing a denial of service.

Detection Guidance

Monitor ZMQ PULL socket traffic on the Prefill rank for unauthenticated decode registration messages with unique mooncake_session_id values and large nested-buffer frames. Check for memory exhaustion events in the Prefill scheduler logs.

Impact Analysis

This vulnerability can cause system downtime by crashing the Prefill scheduler due to memory exhaustion. It may disrupt services relying on SGLang, such as AI inference workloads, until the system is restarted. Attackers can exploit it without authentication if they are on the same network as the vulnerable system.

Mitigation Strategies

Restrict network access to the Prefill rank ZMQ PULL socket, implement authentication for incoming messages, and set memory limits for the Prefill scheduler to prevent OOM conditions.

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