CVE-2026-82617— Apache OpenNLP, Apache OpenNLP: ReDoS / stack exhaustion in RegexNameFinderFactory built-in EMAIL and URL patterns

Apache OpenNLP, Apache OpenNLP: ReDoS / stack exhaustion in RegexNameFinderFactory built-in EMAIL and URL patterns

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.

CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:H/SI:H/SA:H

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Apache OpenNLP 资源管理错误漏洞

Apache OpenNLP是美国Apache基金会的一款服务端软件产品。 Apache OpenNLP 2.0.0版本至2.5.11版本和3.0.0-M1版本至3.0.0-M5版本存在资源管理错误漏洞，该漏洞源于内置名称查找器EMAIL和URL的正则表达式模式包含模糊嵌套量词，攻击者可通过特制输入触发超线性回溯或无界匹配器递归，导致CPU资源大量消耗或线程栈溢出，从而造成拒绝服务。

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