CVE-2026-63317 (GCVE-0-2026-63317)
Vulnerability from cvelistv5 – Published: 2026-07-24 08:07 – Updated: 2026-07-24 18:04
VLAI
EPSS
VEX
Title
Apache OpenNLP: Arbitrary Class Instantiation in GeneratorFactory via Feature Descriptor XML
Summary
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.
Severity
5.6 (Medium)
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-07-24 18:03 UTC
CWE
- CWE-470 - Use of Externally-Controlled Input to Select Classes or Code ('Unsafe Reflection')
Assigner
References
2 references
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Apache Software Foundation | Apache OpenNLP |
Affected:
3.0.0-M1 , < 3.0.0-M4
(semver)
Affected: 0 , < 2.5.11 (semver) |
guessed |
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"value": "\u003cb\u003eArbitrary Class Instantiation via XML Feature Generator Descriptor and Format Name in Apache OpenNLP\u003c/b\u003e\u003cbr\u003e\u003cbr\u003eVersions Affected: \u003cbr\u003e\u003cbr\u003e- before 2.5.10\u003cbr\u003e- before 3.0.0-M5\u003cbr\u003e\u003cbr\u003e\u003cb\u003eDescription:\u003c/b\u003e \u003cbr\u003e\u003cbr\u003eThree 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.\u0026nbsp;\u003cbr\u003e\u003cbr\u003eThe affected paths are: \u003cbr\u003e\u003cbr\u003e(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. \u003cbr\u003e\u003cbr\u003e(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). \u003cbr\u003e\u003cbr\u003e(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.\u003cbr\u003e\u003cbr\u003eExploitation 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\u003cbr\u003e\u003cbr\u003e\u003cb\u003eMitigation:\u003c/b\u003e \u003cbr\u003e\u003cbr\u003eUpgrade to a fixed release. \u003cbr\u003e\u003cbr\u003eThe 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. \u003cbr\u003eClasses 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. \u003cbr\u003e\u003cbr\u003eUsers 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.\u003cbr\u003e\u003cbr\u003e"
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"value": "Arbitrary Class Instantiation via XML Feature Generator Descriptor and Format Name in Apache OpenNLP\n\nVersions Affected: \n\n- before 2.5.10\n- before 3.0.0-M5\n\nDescription: \n\nThree 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.\u00a0\n\nThe affected paths are: \n\n(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. \n\n(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). \n\n(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.\n\nExploitation 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\n\nMitigation: \n\nUpgrade to a fixed release. \n\nThe 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. \nClasses 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. \n\nUsers 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."
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"text": "moderate"
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"descriptions": [
{
"cweId": "CWE-470",
"description": "CWE-470 Use of Externally-Controlled Input to Select Classes or Code (\u0027Unsafe Reflection\u0027)",
"lang": "en",
"type": "CWE"
}
]
}
],
"providerMetadata": {
"dateUpdated": "2026-07-24T08:07:57.463Z",
"orgId": "f0158376-9dc2-43b6-827c-5f631a4d8d09",
"shortName": "apache"
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"tags": [
"vendor-advisory"
],
"url": "https://lists.apache.org/thread/myr446n8t3gv8gq8wbpxm41olx16d8yj"
}
],
"source": {
"defect": [
"OPENNLP-1890"
],
"discovery": "EXTERNAL"
},
"title": "Apache OpenNLP: Arbitrary Class Instantiation in GeneratorFactory via Feature Descriptor XML",
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"cveId": "CVE-2026-63317",
"datePublished": "2026-07-24T08:07:57.463Z",
"dateReserved": "2026-07-16T13:23:13.170Z",
"dateUpdated": "2026-07-24T18:04:05.691Z",
"state": "PUBLISHED"
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Nomenclature
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
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They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
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The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.