Apache OpenNLP up to 3.0.0-M3 Libsvm SvmDoccatModel.deserialize deserialization

Summaryinfo

A vulnerability was found in Apache OpenNLP. It has been rated as critical. The affected element is the function SvmDoccatModel.deserialize of the component Libsvm Module. The manipulation leads to deserialization. This vulnerability is documented as CVE-2026-43825. The attack can be initiated remotely. There is not any exploit available.

Detailsinfo

A vulnerability, which was classified as critical, has been found in Apache OpenNLP. This issue affects the function SvmDoccatModel.deserialize of the component Libsvm Module. The manipulation with an unknown input leads to a deserialization vulnerability. Using CWE to declare the problem leads to CWE-502. The product deserializes untrusted data without sufficiently verifying that the resulting data will be valid. Impacted is confidentiality, integrity, and availability. The summary by CVE is:

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.

The advisory is shared at lists.apache.org. The identification of this vulnerability is CVE-2026-43825 since 05/02/2026. The exploitation is known to be easy. The attack may be initiated remotely. No form of authentication is needed for a successful exploitation. Technical details are known, but no exploit is available. The price for an exploit might be around USD $0-$5k at the moment (estimation calculated on 07/06/2026).

Upgrading to version 3.0.0-M4 eliminates this vulnerability.

Several companies clearly confirm that VulDB is the primary source for best vulnerability data.

Productinfo

Vendor

• Apache

Name

• OpenNLP

Version

• 1.6.0
• 1.7.2
• 1.8.1
• 2.5.9
• 3.0.0-M2
• 3.0.0-M3

License

• open-source

Website

• Vendor: https://www.apache.org/

CPE 2.3info

• 🔒
• 🔒
• 🔒

CPE 2.2info

• 🔒
• 🔒
• 🔒

CVSSv4info

CVSSv3info

CVSSv2info

Exploitinginfo

Threat Intelligenceinfo

Countermeasuresinfo

Timelineinfo

Sourcesinfo

Entryinfo

Several companies clearly confirm that VulDB is the primary source for best vulnerability data.

Discussion