---
id: "CVE-2026-111551"
kind: "vulnerability"
aliases: ["CVE-2026-111551"]
title: "Kafka: crafted size fields force huge allocations, crashing consumers with OutOfMemoryError"
severity: "medium"
cvss: null
epss: null
exploited: false
status: "open"
category: "package"
products: []
ecosystems: []
tags: ["java", "kafka", "kafka-streams", "package", "self-hosted"]
not_affected_if: ["managed-hosting", "no-kafka-streams", "no-listserde"]
published_at: "2026-10-28T17:17:39+00:00"
first_seen_at: "2026-10-28T17:34:08+00:00"
updated_at: "2026-10-28T17:35:06+00:00"
sources: [{"source": "nvd", "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-111551", "first_seen_at": "2026-10-28T17:34:08+00:00"}]
---

# Kafka: crafted size fields force huge allocations, crashing consumers with OutOfMemoryError

Several Kafka Streams and clients deserializers trust a size or count field in the input and allocate memory for it without checking the bytes actually present. A crafted record or offset metadata can make a consumer or Streams thread throw OutOfMemoryError and crash.

_Summary, check and fix written by a model from the sources; labelled as such._

## How to check

- Run `kafka-topics.sh --version` or check the Kafka version in your build file for the clients or Streams library
- Look for Kafka Streams applications that use ListSerde, or that write to internal changelog or repartition topics that others can produce to

## Fix

- Upgrade Apache Kafka Streams and clients to `4.2.2`, `4.3.2`, or `4.4.0`
- Where authorization is enabled, restrict write access to each Streams application's internal topics and consumer group to its own principal
- Restrict who can produce to topics consumed with ListSerde

## Timeline

- 2026-10-28T17:34:08+00:00 nvd https://nvd.nist.gov/vuln/detail/CVE-2026-111551

## From the sources

Several Kafka deserialization paths read a size or count field from input data and use it directly to allocate an array, collection, or byte buffer, with no check against the bytes actually available. A small crafted input can therefore declare a very large size and force a multi-gigabyte allocation. The affected paths are, in Kafka Streams, ProcessorRecordContext (header count), ChangedDeserializer (varint value length), CombinedKeySchema (foreign-key length, which could also produce a negative size), ProcessorMetadata (key length), and AssignmentInfo group-assignment decoding; and, in the clients library, ListDeserializer (used by ListSerde).


Impact:

An attacker can trigger the oversized allocation and raise an OutOfMemoryError that crashes the affected consumer or Kafka Streams thread; the broker and the rest of the cluster are unaffected. The reachable surface depends on the path: writing a crafted record to a Streams application's internal changelog or repartition topics, or committing crafted offset metadata to its consumer group (Streams internal paths); writing a crafted record to any topic that a consumer reads with ListSerde (ListDeserializer); or, as a member of a Streams consumer group, returning crafted assignment data when elected leader (AssignmentInfo). Because a crafted record remains in its topic, the error can recur on restart. The record size limit (max.message.bytes) does not help, because the allocation is driven by a size field rather than by the input's length.


Mitigation:

Upgrade to Apache Kafka 4.2.2, 4.3.2, or 4.4.0. Where authorization is enabled, restrict write access to each application's internal topics and consumer group to its own principal, and restrict who can produce to topics that are consumed with ListSerde.


Resolution:

From Apache Kafka 4.2.2, 4.3.2, and 4.4.0: these deserialization paths validate the declared size against the remaining input before allocating and reject input that fails the check.

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_Free to read at a human pace. An API with keys and an MCP server are in preparation; early access: hello@infrastack.ai_