CVE-2026-82617
CriticalCVSS 10.0Summary
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.
Risk Assessment
An attacker who can supply text for analysis can pin a thread's CPU for seconds to minutes or cause abrupt thread death, resulting in denial of service to the embedding application. No authentication, special configuration, or model file is required beyond the application using one of the two built-in finders.
Recommendation
Upgrade Apache OpenNLP to version 2.5.12 or 3.0.0-M6 (for the 3.0.0 milestone line), which fix the issue. Until patched, avoid processing untrusted text with the built-in EMAIL and URL finders.
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-2026-63317Medium
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.
- 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)
The two built-in name-finder patterns exposed by opennlp.tools.namefind.RegexNameFinderFactory - DEFAULT_REGEX_NAME_FINDER.EMAIL and DEFAULT_REGEX_NAME_FINDER.URL - contain ambiguous nested quantifiers. An application that obtains these finders through RegexNameFinderFactory.getDefaultRegexNameFinders(...) and then applies them to untrusted text through RegexNameFinder.find(String[]) or RegexNameFinder.find(String) can be driven into super-linear backtracking or into unbounded matcher recursion by a small crafted input. For the EMAIL pattern, a long run of local-part characters that is never followed by an @ forces the matcher to re-scan to end-of-input from every starting offset. Cost grows quadratically with input length: an input of approximately 32 KB consumes several seconds of CPU in a single find() call and returns no match, and each doubling of the input multiplies the cost roughly four-fold. For the URL pattern, the query-string sub-expression nests a capturing repetition inside an outer repetition. The JDK matcher recurses once per query token, so an input of approximately 4 KB containing many &-separated tokens exhausts the thread stack and causes java.lang.StackOverflowError to propagate out of find(), terminating the calling thread. On a thread created with a smaller stack (for example -Xss512k, typical of server worker pools) approximately 1 KB is sufficient. In both cases an attacker who can supply text for analysis can convert a single request into seconds to minutes of pinned CPU, or into an abrupt thread death, denying service to the embedding application. No authentication, special configuration, or model file is required beyond the application having selected one of the two built-in finders. This issue affects Apache OpenNLP: from 2.0.0 through 2.5.11; from 3.0.0-M1 through 3.0.0-M5. Users are recommended to upgrade to version 2.5.12, or to 3.0.0-M6 for users tracking the 3.0.0 milestone line, which fix the issue.