Apache OpenNLP vulnerabilities

The built-in name-finder patterns EMAIL and URL in Apache OpenNLP contain ambiguous nested quantifiers, enabling a ReDoS attack. A crafted input can trigger super-linear backtracking or unbounded matcher recursion, leading to CPU exhaustion or StackOverflowError. The issue affects versions 2.0.0 through 2.5.11 and 3.0.0-M1 through 3.0.0-M5.

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.

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.

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.

A vulnerability in Apache OpenNLP (opennlp-spellcheck extension, versions 3.0.0-M4 and 3.0.0-M5) allows an Out-of-Memory Denial of Service. The SymSpellModelSerializer.create() method reads unigram and bigram count fields from a model file and passes them directly to map pre-sizing without an upper bound, causing a crafted .bin file to attempt a 4–8 GB allocation and fail with OutOfMemoryError.

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.

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.