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) 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.
Ce que ça veut dire
- Exposition
- Exploitable à distance depuis le réseau, sans authentification et sans action de la victime.
- Impact
- Un attaquant peut lire certaines données, altérer certaines données et dégrader le service.
- Faiblesse
- L’application reconstruit un objet depuis une donnée contrôlée par l’attaquant, ce qui mène souvent à l’exécution de code.
- Probabilité
- Le score EPSS situe l’exploitation à court terme dans une zone intermédiaire : ni négligeable, ni imminente.
À faireÀ intégrer au prochain cycle de correctifs. Commencer par les instances exposées à Internet.
Lecture automatique du vecteur CVSS, du type de faiblesse (CWE) et du score EPSS. La description technique ci-dessus reste celle publiée par le NIST, en anglais.