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Fencer Vulns
high 7.3

CVE-2026-43825 in the critical feed json

Apache OpenNLP :: Core :: ML :: LibSVM: Unsafe Java Deserialization in SvmDoccatModel

published 2026-07-06 4 mo ago modified 2026-10-25 14 d ago also EUVD-2026-41885

cvss
7.3
version 3.1, CNA
cisa kev
Not listed
not in CISA's catalog
epss
13.9%
EPSS 13.9% chance of exploitation in 30 days, percentile 96%
public exploits
0
none known

Summary

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.

Patch / fix

  • Apache Software Foundation Apache OpenNLP :: Core :: ML :: LibSVM 3.0.0-M4

Vendor advisories

What the vendors themselves say about their products: affected, fixed or not affected, and what to do.

red hat product security vex CVE-2026-43825 updated cvss 7.3

org.apache.opennlp/opennlp-tools: Apache OpenNLP SvmDoccatModel: Remote code execution via untrusted Java deserialization

  • Red Hat Data Grid 8 opennlp-tools 1.9.4 Red Hat JBoss Enterprise Application Platform Expansion Pack opennlp-tools 1.9.4 Red Hat OpenShift AI (RHOAI) rhoai/odh-trustyai-service-rhel9, rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9
    not affected: vulnerable code not present

Red Hat CSAF VEX © Red Hat, Inc., from https://security.access.redhat.com/data/csaf/v2/vex/; changed: reduced to product statuses and remediations. CC BY 4.0 · csaf

CISA SSVC

Exploitation
none
Automatable
yes
Technical impact
partial
Assessed
4 mo ago

Exploit prediction

13.92% chance of exploitation in the next 30 days, higher than 96% of all scored CVEs (FIRST EPSS, 2026-11-08).

CVSS scores

assigned by version score vector
CISA ADP 3.1 7.3 CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:L
CNA 3.1 7.3 CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:L

Affected products

  • Apache Software Foundation Apache OpenNLP :: Core :: ML :: LibSVM

Classification

Weakness
  • CWE-502 Deserialization of Untrusted Data

References

Sources

Fencer Vulns keeps one entry per vulnerability: the CVE id wins, then GHSA, and records that alias each other are merged, except that two CVEs always keep separate entries. The same data is available as JSON.