CVE-2026-42027: CWE-470 Use of Externally-Controlled Input to Select Classes or Code ('Unsafe Reflection') in Apache Software Foundation Apache OpenNLP
Arbitrary Class Instantiation via Model Manifest in Apache OpenNLP ExtensionLoader Versions Affected: before 1.9.5, before 2.5.9, before 3.0.0-M3 Description: The ExtensionLoader.instantiateExtension(Class, String) method loads a class by its fully-qualified name via Class.forName() and invokes its no-arg constructor, with the class name sourced from the manifest.properties entry of a model archive. The existing isAssignableFrom check correctly rejects classes that are not subtypes of the expected extension interface (BaseToolFactory for factory=, ArtifactSerializer for serializer-class-*), but the check runs after Class.forName() has already loaded and initialized the named class. Class.forName() with default initialization semantics executes the target class's static initializer before returning, so an attacker who can supply a crafted model archive can cause the static initializer of any class on the classpath to run during model loading, regardless of whether that class passes the subsequent type check. Exploitation requires a class with attacker-useful side effects in its static initializer (for example, JNDI lookup, outbound network I/O, or filesystem access) to be present on the classpath, so this is not a drop-in remote code execution; however, the attack surface grows as third-party model distribution becomes more common (community model repositories, Hugging Face-style sharing), where users routinely load model files from origins they do not control. A secondary, narrower vector affects deployments that ship legitimate BaseToolFactory or ArtifactSerializer subclasses with side-effecting no-arg constructors: a malicious manifest can name such a class and force its constructor to run during model load. Mitigation: * 2.x users should upgrade to 2.5.9. * 3.x users should upgrade to 3.0.0-M3. Note: The fix introduces a package-prefix allowlist that is consulted before Class.forName() is invoked, so the static initializer of a disallowed class is never executed. Classes under the opennlp. prefix remain permitted by default. Deployments that load models referencing factories or serializers 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 that all model files are sourced from trusted origins and should audit their classpath for classes with side-effecting static initializers or constructors, particularly any that perform JNDI lookups, network requests, or filesystem operations during class initialization.
AI Analysis
Technical Summary
The vulnerability in Apache OpenNLP's ExtensionLoader.instantiateExtension(Class, String) method arises because it loads classes by name using Class.forName() before verifying that the loaded class is a subtype of the expected interface. Since Class.forName() initializes the class, its static initializer runs before the type check, allowing an attacker who controls the model manifest to trigger static initializers of arbitrary classes on the classpath. This can lead to unintended side effects such as network communication or filesystem access if such classes exist. The vulnerability is not direct remote code execution but increases attack surface especially when loading models from untrusted sources. The fix in versions 2.5.9 and 3.0.0-M3 adds a package-prefix allowlist to block unauthorized class loading. Users must explicitly allow packages outside the default opennlp.* prefix if needed.
Potential Impact
An attacker supplying a malicious model archive can cause the static initializer of any class on the classpath to execute during model loading, potentially triggering side effects like network requests or filesystem operations. This can lead to confidentiality, integrity, and availability impacts depending on the classes present. The vulnerability is rated critical with a CVSS score of 9.8, reflecting high impact on confidentiality, integrity, and availability. However, exploitation requires the presence of classes with side-effecting static initializers or constructors, so it is not a straightforward remote code execution.
Mitigation Recommendations
A fix is available in Apache OpenNLP versions 2.5.9 and 3.0.0-M3, which implement a package-prefix allowlist to prevent execution of static initializers for disallowed classes. Users should upgrade to these fixed versions. For users who cannot upgrade immediately, it is recommended to only load model files from trusted sources and audit the classpath for classes with side-effecting static initializers or constructors, especially those performing JNDI lookups, network I/O, or filesystem access. Deployments that require loading classes outside the opennlp.* package must explicitly register allowed packages via ExtensionLoader.registerAllowedPackage(String) or the OPENNLP_EXT_ALLOWED_PACKAGES system property before model loading.
CVE-2026-42027: CWE-470 Use of Externally-Controlled Input to Select Classes or Code ('Unsafe Reflection') in Apache Software Foundation Apache OpenNLP
Description
Arbitrary Class Instantiation via Model Manifest in Apache OpenNLP ExtensionLoader Versions Affected: before 1.9.5, before 2.5.9, before 3.0.0-M3 Description: The ExtensionLoader.instantiateExtension(Class, String) method loads a class by its fully-qualified name via Class.forName() and invokes its no-arg constructor, with the class name sourced from the manifest.properties entry of a model archive. The existing isAssignableFrom check correctly rejects classes that are not subtypes of the expected extension interface (BaseToolFactory for factory=, ArtifactSerializer for serializer-class-*), but the check runs after Class.forName() has already loaded and initialized the named class. Class.forName() with default initialization semantics executes the target class's static initializer before returning, so an attacker who can supply a crafted model archive can cause the static initializer of any class on the classpath to run during model loading, regardless of whether that class passes the subsequent type check. Exploitation requires a class with attacker-useful side effects in its static initializer (for example, JNDI lookup, outbound network I/O, or filesystem access) to be present on the classpath, so this is not a drop-in remote code execution; however, the attack surface grows as third-party model distribution becomes more common (community model repositories, Hugging Face-style sharing), where users routinely load model files from origins they do not control. A secondary, narrower vector affects deployments that ship legitimate BaseToolFactory or ArtifactSerializer subclasses with side-effecting no-arg constructors: a malicious manifest can name such a class and force its constructor to run during model load. Mitigation: * 2.x users should upgrade to 2.5.9. * 3.x users should upgrade to 3.0.0-M3. Note: The fix introduces a package-prefix allowlist that is consulted before Class.forName() is invoked, so the static initializer of a disallowed class is never executed. Classes under the opennlp. prefix remain permitted by default. Deployments that load models referencing factories or serializers 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 that all model files are sourced from trusted origins and should audit their classpath for classes with side-effecting static initializers or constructors, particularly any that perform JNDI lookups, network requests, or filesystem operations during class initialization.
CVSS v3.1
Score 9.8critical
Affected software
Apache Software Foundation
Apache OpenNLP
pkg:maven/org.apache.opennlp/opennlppkg:maven/Apache Software Foundation/org.apache.opennlp:opennlp-toolsRun on your own infrastructure? Check whether these packages are installed with threat-finder — our free open-source scanner.
AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
The vulnerability in Apache OpenNLP's ExtensionLoader.instantiateExtension(Class, String) method arises because it loads classes by name using Class.forName() before verifying that the loaded class is a subtype of the expected interface. Since Class.forName() initializes the class, its static initializer runs before the type check, allowing an attacker who controls the model manifest to trigger static initializers of arbitrary classes on the classpath. This can lead to unintended side effects such as network communication or filesystem access if such classes exist. The vulnerability is not direct remote code execution but increases attack surface especially when loading models from untrusted sources. The fix in versions 2.5.9 and 3.0.0-M3 adds a package-prefix allowlist to block unauthorized class loading. Users must explicitly allow packages outside the default opennlp.* prefix if needed.
Potential Impact
An attacker supplying a malicious model archive can cause the static initializer of any class on the classpath to execute during model loading, potentially triggering side effects like network requests or filesystem operations. This can lead to confidentiality, integrity, and availability impacts depending on the classes present. The vulnerability is rated critical with a CVSS score of 9.8, reflecting high impact on confidentiality, integrity, and availability. However, exploitation requires the presence of classes with side-effecting static initializers or constructors, so it is not a straightforward remote code execution.
Mitigation Recommendations
A fix is available in Apache OpenNLP versions 2.5.9 and 3.0.0-M3, which implement a package-prefix allowlist to prevent execution of static initializers for disallowed classes. Users should upgrade to these fixed versions. For users who cannot upgrade immediately, it is recommended to only load model files from trusted sources and audit the classpath for classes with side-effecting static initializers or constructors, especially those performing JNDI lookups, network I/O, or filesystem access. Deployments that require loading classes outside the opennlp.* package must explicitly register allowed packages via ExtensionLoader.registerAllowedPackage(String) or the OPENNLP_EXT_ALLOWED_PACKAGES system property before model loading.
Technical Details
- Data Version
- 5.2
- Assigner Short Name
- apache
- Date Reserved
- 2026-04-23T14:21:25.317Z
- State
- PUBLISHED
- Vendor Advisory Urls
- [{"url":"https://access.redhat.com/security/cve/CVE-2026-42027","vendor":"Red Hat"}]
Threat ID: 69f8d216cbff5d8610397044
Added to database: 05/04/2026, 17:06:30 UTC
Last enriched: 08/15/2026, 17:17:21 UTC
Last updated: 09/17/2026, 22:01:35 UTC
Views: 113
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