Copyright © 2012 Red Hat, Inc. All rights reserved. Moderate 2026-07-06T15:42:04 org.apache.opennlp/opennlp-tools: Apache OpenNLP SvmDoccatModel: Remote code execution via untrusted Java deserialization 7.3 CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:L CWE-502

Untrusted Java Deserialization in Apache OpenNLP SvmDoccatModel Versions Affected:   before 3.0.0-M4 (libsvm document categorization module; introduced in   OPENNLP-1808 and only present on the 3.x line) Description: SvmDoccatModel.deserialize(InputStream) reads an attacker-controlled stream with java.io.ObjectInputStream and calls readObject() without an ObjectInputFilter installed. ObjectInputStream materialises every class referenced in the stream before the resulting object is cast to SvmDoccatModel, so the cast that follows readObject() executes only after the foreign object graph has already been deserialised in full. If a Java deserialization gadget chain is available on the consumer's classpath, a crafted payload supplied to deserialize() executes arbitrary code in the JVM that loads it. Apache OpenNLP itself does not ship a known gadget chain, so the realistic risk is to downstream applications that embed the libsvm module alongside vulnerable transitive dependencies. The method is public and static, so any caller can pass an untrusted stream to it directly. The practical impact is remote code execution against processes that load SvmDoccatModel instances from untrusted or semi-trusted origins. Mitigation: 3.x users should upgrade to 3.0.0-M4. Users who cannot upgrade immediately should treat all serialized SvmDoccatModel streams as untrusted input unless their provenance is verified, and should avoid invoking SvmDoccatModel.deserialize() on streams supplied by end users or fetched from third-party sources without integrity checks.

A flaw was found in Apache OpenNLP SvmDoccatModel. This vulnerability allows a remote attacker to achieve arbitrary code execution by supplying a specially crafted payload to the deserialize() method. The method processes untrusted Java deserialization streams without proper validation, enabling the execution of malicious code within the Java Virtual Machine (JVM) that loads it.

This Moderate flaw in Apache OpenNLP SvmDoccatModel, which allows for remote code execution through untrusted Java deserialization, does not affect Red Hat products. The vulnerable code is not present in Red Hat's supported offerings. Mitigation for this issue is either not available or the currently available options do not meet the Red Hat Product Security criteria comprising ease of use and deployment, applicability to widespread installation base, or stability. Red Hat Data Grid 8 Under investigation opennlp-tools Red Hat JBoss Enterprise Application Platform Expansion Pack Under investigation opennlp-tools Red Hat OpenShift AI (RHOAI) Not affected rhoai/odh-trustyai-service-rhel9 Red Hat OpenShift AI (RHOAI) Not affected rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9 https://www.cve.org/CVERecord?id=CVE-2026-43825 https://nvd.nist.gov/vuln/detail/CVE-2026-43825 https://lists.apache.org/thread/c7kom0pgk9cbpfnbooh5m3g85ndf50hn