Apache OpenNLP: Inefficient Regular Expression Complexity
CVE-2026-82617 is a critical-severity inefficient regular expression complexity vulnerability in Apache OpenNLP from Apache, with a CVSS 3.1 base score of 9.8 out of 10. It can be exploited remotely over the network by an unauthenticated attacker, without any action from a user. The record lists versions 3.0.0-M6, 2.5.12 as the first without the flaw, so updating Apache OpenNLP to one of those releases or later removes the exposure. There is no confirmed exploitation so far. EPSS estimates a 0.77% chance of exploitation within 30 days, higher than 56% of scored CVEs.
Critical severity: a successful attack would have severe impact.
What to do
- Update Apache OpenNLP to 3.0.0-M6 or 2.5.12, whichever matches your release line, or a later version.
- Update Opennlp to 2.5.12 or a later version.
- Read the advisory on lists.apache.org for workarounds and exact fixed builds.
- Until you can update, restrict network access to the affected service so it is not reachable from untrusted networks.
Affected products and versions
| Vendor | Product | Affected versions | Fixed in |
|---|---|---|---|
| Apache | Apache OpenNLP | 3.0.0-M1 up to, but not including, 3.0.0-M6; 2.0.0 up to, but not including, 2.5.12 | 3.0.0-M6, 2.5.12 |
| Apache | Opennlp | 2.0.0 up to, but not including, 2.5.12; 3.0.0 | 2.5.12 |
Version data comes from the organisation that assigned the CVE. Confirm against the vendor advisory before deciding you are unaffected.
How the severity score breaks down
- Attack vector
- NetworkCan be exploited remotely over a network, including the internet.
- Attack complexity
- LowNo special conditions are needed; the attack works reliably.
- Privileges required
- NoneNo account or login is needed.
- User interaction
- NoneNo action by a victim is required.
- Scope
- UnchangedImpact stays within the vulnerable component.
- Confidentiality
- HighAll data handled by the component can be read.
- Integrity
- HighData or code can be modified at will.
- Availability
- HighThe component can be taken down completely.
Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H. Scored by NVD.
| Scoring system | Score | Severity | Scored by |
|---|---|---|---|
| CVSS 4.0 | 10.0 | Critical | CNA (apache.org) |
| CVSS 3.1 | 9.8 | Critical | NVD |
Official description
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.
Source: the CVE record as published by its numbering authority, via NVD and CVE.org.
The underlying weakness: Inefficient Regular Expression Complexity
The product uses a regular expression with a worst-case computational complexity that is inefficient and possibly exponential.
How developers prevent this class of flaw
- Use regular expressions that do not support backtracking, e.g. by removing nested quantifiers.
- Set backtracking limits in the configuration of the regular expression implementation, such as PHP's pcre.backtrack_limit. Also consider limits on execution time for the process.
- Do not use regular expressions with untrusted input. If regular expressions must be used, avoid using backtracking in the expression.
More Inefficient Regular Expression Complexity vulnerabilities (CWE-1333)
Timeline
- CVE record published.
- CISA published its SSVC assessment (exploitation: none, automatable: yes, technical impact: total).
- Record last changed materially (score, affected products, status or references).
References
Advisories
Third-party and government advisories
- openwall.com/lists/oss-security/2026/09/11/10Mailing List, Third Party Advisory
Other vulnerabilities in Apache OpenNLP
- 7.5 High severity
- 7.5 High severity
- 7.5 High severity
- 7.5 High severity
Recent Inefficient Regular Expression Complexity vulnerabilities
- 7.5 High severity
- 7.1 High severity
- 7.5 High severity
- 7.5 High severity
- 7.5 High severity
- 7.5 High severity
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