Remote code execution via unfiltered Java deserialization
Published Jul 6, 2026 · Updated Jul 6, 2026
Unsafe Java deserialization in Apache OpenNLP ML LibSVM before 3.0.0-M4 allows remote attackers to execute code via a crafted model stream. SvmDoccatModel.deserialize(InputStream) calls ObjectInputStream.readObject() without an ObjectInputFilter, materializing the supplied object graph before checking its type. Reachability requires an embedding application to load an attacker-controlled stream and an exploitable gadget chain to exist on that application's classpath.
Summary
What happened
Unsafe Java deserialization in Apache OpenNLP ML LibSVM before 3.0.0-M4 allows remote attackers to execute code via a crafted model stream. SvmDoccatModel.deserialize(InputStream) calls ObjectInputStream.readObject() without an ObjectInputFilter, materializing the supplied object graph before checking its type. Reachability requires an embedding application to load an attacker-controlled stream and an exploitable gadget chain to exist on that application's classpath.
The record
- CVE
- CVE-2026-43825
- Published
- Jul 6, 2026
- Updated
- Jul 6, 2026
- Vendor
- The Apache Software Foundation
- Product
- Apache OpenNLP ML LibSVM
- Classifications
- CWE-502, T1203
- Attack vector
- network
- Privileges
- unauthenticated
Timeline
How it unfolded
- Jul 6, 2026CVE publishedPublication date reported by the CVE source.
- Jul 6, 2026Record updatedLatest update available in the CVE record.
Exploitability
Present is not the same as exploitable
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Is a vulnerable build present?
Compare these published version ranges with your installed build and any vendor patches.
- Affected versionversion=3.0.0-M1 <3.0.0-M4
What conditions does exploitation require?
What is affected?
Published CVSS scores
CVSS describes severity. EPSS estimates exploitation probability.
Attacks
What attackers are doing with it
Daily unique IPs observed by Shadowserver honeypots for known exploited vulnerabilities (KEVs). Missing observations do not establish an absence of attacks.
Weakness, pattern, technique
Public exploit references
- REPRO-2026-00279 Apache OpenNLP deserialization reproductionfunctional · validated
Labels summarize the accepted research assessment. They do not indicate a test against your environment.
Technologies
Your stack
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Your stack
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