CVE-2026-63317
MediumCVSS 5.6Exploitation Probability (EPSS)
Low risk41th percentile - higher than 41% of all known CVEs
Summary
In Apache OpenNLP before versions 2.5.10 and 3.0.0-M5, a vulnerability allows arbitrary class instantiation. An attacker can supply a crafted model or format name, leading to loading and executing code from dangerous classes.
Risk Assessment
The risk is potential remote code execution (RCE) by an attacker with access to models or format parameters. This could lead to system compromise, data exfiltration, or service disruption.
Recommendation
Upgrade Apache OpenNLP to version 2.5.10 or 3.0.0-M5 immediately. If upgrade is not possible, restrict trusted sources for models and format parameters, and audit the classpath for dangerous classes.
Other vulnerabilities in Apache OpenNLP
See all- CVE-2026-43825High
In Apache OpenNLP, the libsvm document categorization module (3.x line) is vulnerable to untrusted Java deserialization. The SvmDoccatModel.deserialize(InputStream) method uses java.io.ObjectInputStream without a filter, allowing an attacker to execute arbitrary code via a crafted stream.
- CVE-2026-42027Critical
In Apache OpenNLP before versions 1.9.5, 2.5.9, and 3.0.0-M3, the ExtensionLoader.instantiateExtension() method loads a class by name from a model archive's manifest.properties using Class.forName() before checking type compatibility. This allows an attacker to execute the static initializer of any class on the classpath during model loading, potentially causing harmful side effects.
- CVE-2026-40682Critical
An XML External Entity (XXE) vulnerability was found in Apache OpenNLP's DictionaryEntryPersistor class. The class initializes a SAX parser without enabling secure processing or disabling DTD handling, allowing an attacker to inject a malicious DOCTYPE declaration in a dictionary file. This can lead to local file disclosure via file:// entity references or server-side request forgery via http:// entity references during XML parsing.
- CVE-2026-42440High
In Apache OpenNLP before versions 1.9.5, 2.5.9, and 3.0.0-M3, a denial-of-service vulnerability exists due to unbounded array allocation in AbstractModelReader. The methods getOutcomes(), getOutcomePatterns(), and getPredicates() allocate arrays based on a 32-bit integer from the model file without validation, allowing an attacker to set the value to Integer.MAX_VALUE and trigger an OutOfMemoryError.
Original NVD description (English source)
Arbitrary Class Instantiation via XML Feature Generator Descriptor and Format Name in Apache OpenNLP Versions Affected: - before 2.5.10 - before 3.0.0-M5 Description: Three code paths in Apache OpenNLP load a class by its fully-qualified name via Class.forName() and invoke its no-arg constructor without any prior validation of the class name or its type. The affected paths are: (1) GeneratorFactory, which reads the class attribute of generator elements in an XML feature generator descriptor; such descriptors are embedded as artifacts in model archives (e.g. TokenNameFinder and POSTagger models) and are parsed during model loading, so an attacker who can supply a crafted model archive controls the class name directly. (2) StreamFactoryRegistry.getFactory(Class, String), which falls back to interpreting an unregistered format name as the fully-qualified class name of an ObjectStreamFactory; this is exploitable in applications that pass untrusted format names (e.g. exposing the -format parameter of the command-line tooling to external input). (3) StringInterners, which instantiates the interner implementation named by the opennlp.interner.class system property; this value is normally deployer-controlled, so it is hardened as defense in depth rather than being independently attacker-reachable. Exploitation requires a class with attacker-useful side effects in its static initializer or no-arg constructor (JNDI lookup, outbound network I/O, filesystem access) to be present on the classpath, so this is not drop-in remote code execution. T Mitigation: Upgrade to a fixed release. The fix routes all three paths through ExtensionLoader.instantiateExtension(...), which consults a package-prefix allowlist before Class.forName() is invoked, so a disallowed class is never loaded, initialized, or constructed. Classes under the opennlp. prefix remain permitted by default. Deployments that load models referencing feature generator factories, object stream factories, or string interners outside opennlp.* must opt those packages in, either programmatically via ExtensionLoader.registerAllowedPackage(String) before the first model load, or by setting the OPENNLP_EXT_ALLOWED_PACKAGES system property to a comma-separated list of allowed package prefixes. Users who cannot upgrade immediately should ensure all model files and format names are sourced from trusted origins and should audit their classpath for classes with side-effecting static initializers or constructors.