SOC status:Duty analyst on shift

UK Cyber Defence
VulnerabilityAnalyzed

CVE-2026-43825

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)…

HIGH 7.3EPSS 13.9%

Does this matter?

EPSS puts the probability of exploitation in the next 30 days at 13.9%, higher than 97% of all known CVEs. Patch or mitigate before the next change window.

Description

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.

CVSS 3.1
7.3 HIGHCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:L
EPSS
13.92% probability · 97th percentile
Public exploits
None in Exploit-DB
CISA KEV
Not listed
Weakness
CWE-502
Affected
apache/opennlp
Source
security@apache.org
EPSS trend
0%8%15%30 October 2026: 13.92%30 October 202630 October 2026

EPSS 13.9% since 30 October 2026; no change recorded yet. The dashed line is the ten per cent mark our analysts treat as “patch before the next change window”. Points are recorded when the score first appears and whenever it moves by a percentage point or more.

Source: NVD record, EPSS from FIRST.org, KEV from CISA, exploits from Exploit-DB. Refreshed daily. Download this record as JSON.