Evidence used
- No CISA KEV confirmation is currently recorded.
- The selected CVSS metric records a network-reachable, unauthenticated path with no user interaction.
- EPSS is 13.92% for the current model date.
BlackTreeCVE IntelligenceFull vulnerability report · 2026
CVE-2026-43825High confidence
Apache OpenNLP :: Core :: ML :: LibSVM: Unsafe Java Deserialization in SvmDoccatModel
Apache Software Foundation · Apache OpenNLP :: Core :: ML :: LibSVM
7.3HighCVSS 3.1
Within 7 days
Fix not verifiedHigh technical severity; prioritise exposed affected systems while verifying vendor guidance.
R
Open reassessment dashboard →Operational reassessment
Published severity in operational context
Published severityHigh→Operational priority:Critical, raised one band.upgradedsince 5 Oct 2026
Compensating controls
- Restrict the affected network interface to trusted sources where business-safe.
- Monitor vendor guidance and exploitation sources for a material change.
Verification
- Confirm that the asset runs Apache Software Foundation Apache OpenNLP :: Core :: ML :: LibSVM and falls inside the recorded affected range.
- Recheck the vendor advisory before scheduling a change because no verified fixed version is currently retained.
- Validate exposure, authentication requirements and compensating controls in the actual environment.
- Reopen this reassessment when CVSS, KEV, EPSS, exploit evidence or remediation changes.
Distribution package intelligence
5 package statesRelease-specific package status
Debian, ubuntu findings are scoped to the named distribution, release and source package. An absent finding does not mean a package is unaffected.
Repository candidate not checked
A published vendor fix does not prove that a matching update is enabled and installable on a particular asset. Confirm the local package candidate before scheduling remediation.
| Distribution release | Source package | Vendor state | Fixed version | Evidence |
|---|---|---|---|---|
| Debian trixietrixie · source | apache-opennlp | Not affectedDebian marks this release not affected (fixed-version marker 0). | Not published in this feed | Debian Security Tracker ↗Source updated 5 Oct 2026 |
| Debian bookwormbookworm · source | apache-opennlp | Not affectedDebian marks this release not affected (fixed-version marker 0). | Not published in this feed | Debian Security Tracker ↗Source updated 5 Oct 2026 |
| Debian forkyforky · source | apache-opennlp | Not affectedDebian marks this release not affected (fixed-version marker 0). | Not published in this feed | Debian Security Tracker ↗Source updated 5 Oct 2026 |
| Debian sidsid · source | apache-opennlp | Not affectedDebian marks this release not affected (fixed-version marker 0). | Not published in this feed | Debian Security Tracker ↗Source updated 5 Oct 2026 |
| Ubuntu 24.04 LTSnoble · standard archive | apache-opennlp | Under evaluationCanonical reports that the package might be affected and still needs evaluation or fixing. | Not published in this feed | Canonical Ubuntu Security ↗Source updated 5 Oct 2026 |
High technical severity; prioritise exposed affected systems while verifying vendor guidance.
Fix not verified01
What, why and how
Untrusted Java Deserialization in Apache OpenNLP SvmDoccatModel Versions Affected: before 3.0.0-M4 (libsvm document categorization module; introduced in OPENNLP-1808 and only present on the 3.x line) Description: SvmDoccatModel.deserialize(InputStream) reads an attacker-controlled stream with java.io.ObjectInputStream and calls readObject() without an ObjectInputFilter installed. ObjectInputStream materialises every class referenced in the stream before the resulting object is cast to SvmDoccatModel, so the cast that follows readObject() executes only after the foreign object graph has already been deserialised in full. If a Java deserialization gadget chain is available on the consumer's classpath, a crafted payload supplied to deserialize() executes arbitrary code in the JVM that loads it. Apache OpenNLP itself does not ship a known gadget chain, so the realistic risk is to downstream applications that embed the libsvm module alongside vulnerable transitive dependencies. The method is public and static, so any caller can pass an untrusted stream to it directly. The practical impact is remote code execution against processes that load SvmDoccatModel instances from untrusted or semi-trusted origins. Mitigation: 3.x users should upgrade to 3.0.0-M4. Users who cannot upgrade immediately should treat all serialized SvmDoccatModel streams as untrusted input unless their provenance is verified, and should avoid invoking SvmDoccatModel.deserialize() on streams supplied by end users or fetched from third-party sources without integrity checks.
What
Untrusted Java Deserialization in Apache OpenNLP SvmDoccatModel Versions Affected: before 3.0.0-M4 (libsvm document categorization module; introduced in OPENNLP-1808 and only present on the 3.x line) Description: SvmDoccatModel.deserialize(InputStream) reads an attacker-controlled stream with java.io.ObjectInputStream and calls readObject() without an ObjectInputFilter installed. ObjectInputStream materialises every class referenced in the stream before the resulting object is cast to SvmDoccatModel, so the cast that follows readObject() executes only after the foreign object graph has already been deserialised in full. If a Java deserialization gadget chain is available on the consumer's classpath, a crafted payload supplied to deserialize() executes arbitrary code in the JVM that loads it. Apache OpenNLP itself does not ship a known gadget chain, so the realistic risk is to downstream applications that embed the libsvm module alongside vulnerable transitive dependencies. The method is public and static, so any caller can pass an untrusted stream to it directly. The practical impact is remote code execution against processes that load SvmDoccatModel instances from untrusted or semi-trusted origins. Mitigation: 3.x users should upgrade to 3.0.0-M4. Users who cannot upgrade immediately should treat all serialized SvmDoccatModel streams as untrusted input unless their provenance is verified, and should avoid invoking SvmDoccatModel.deserialize() on streams supplied by end users or fetched from third-party sources without integrity checks.
Why
Attacker-influenced serialised data is reconstructed as trusted objects, which can invoke dangerous application behaviour.
How
An attacker operating through a network path may attempt exploitation without authentication or user interaction. If successful, the issue may execute code or commands in the affected security context.
What
Untrusted Java Deserialization in Apache OpenNLP SvmDoccatModel Versions Affected: before 3.0.0-M4 (libsvm document categorization module; introduced in OPENNLP-1808 and only present on the 3.x line) Description: SvmDoccatModel.deserialize(InputStream) reads an attacker-controlled stream with java.io.ObjectInputStream and calls readObject() without an ObjectInputFilter installed. ObjectInputStream materialises every class referenced in the stream before the resulting object is cast to SvmDoccatModel, so the cast that follows readObject() executes only after the foreign object graph has already been deserialised in full. If a Java deserialization gadget chain is available on the consumer's classpath, a crafted payload supplied to deserialize() executes arbitrary code in the JVM that loads it. Apache OpenNLP itself does not ship a known gadget chain, so the realistic risk is to downstream applications that embed the libsvm module alongside vulnerable transitive dependencies. The method is public and static, so any caller can pass an untrusted stream to it directly. The practical impact is remote code execution against processes that load SvmDoccatModel instances from untrusted or semi-trusted origins. Mitigation: 3.x users should upgrade to 3.0.0-M4. Users who cannot upgrade immediately should treat all serialized SvmDoccatModel streams as untrusted input unless their provenance is verified, and should avoid invoking SvmDoccatModel.deserialize() on streams supplied by end users or fetched from third-party sources without integrity checks.
Why
Attacker-influenced serialised data is reconstructed as trusted objects, which can invoke dangerous application behaviour.
How
An attacker operating through a network path may attempt exploitation without authentication or user interaction. If successful, the issue may execute code or commands in the affected security context.
02
Exploit reality and attack path
CVSS severity, EPSS forecast probability, public exploit material and CISA-confirmed exploitation are separate signals.
Observed exploitation No confirmed evidence
?
Confirmed exploitation and public exploit material are separate signals. Attacks can occur without public proof-of-concept or exploit code.No CISA KEV match was present at the last successful refresh. This means no confirmation from that source, not proof of no exploitation.
Public PoC / exploit material None recorded
?
Confirmed exploitation and public exploit material are separate signals. Attacks can occur without public proof-of-concept or exploit code.No exploit-tagged reference or CISA SSVC proof-of-concept state is currently recorded. Research may still exist outside the structured feeds.
- Likely attack path
- a network path → Deserialization of Untrusted Data → execute code or commands in the affected security context
- Attack surface
- Network
- Privileges required
- None: unauthenticated exploitation is possible
- User interaction
- None
- Attack complexity
- Low: no specialised conditions are recorded
- Security boundary
- Unchanged: impact remains within the vulnerable component's security authority
- Weakness
?
CWE means Common Weakness Enumeration: a standard category for the underlying weakness. - CWE-502 ↗
CWE-502: Deserialization of Untrusted Data. The product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid.
- CVSS vector
?
CVSS means Common Vulnerability Scoring System. The vector records the metric values used to calculate technical severity. CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:LCommon Vulnerability Scoring System 3.1: the compact vector below is decoded into plain language.
AVNetworkAttack vector: The vulnerable component can be reached over a network.ACLowAttack complexity: No specialised conditions are required beyond attacker-controlled input.PRNonePrivileges required: The attacker does not need an account or existing privileges.UINoneUser interaction: No action by another user is required.SUnchangedScope: The security impact remains within the vulnerable component's authority.CLowConfidentiality impact: A successful attack can cause a limited loss.ILowIntegrity impact: A successful attack can cause a limited loss.ALowAvailability impact: A successful attack can cause a limited loss.- Post-exploitation / living off the land
- After compromise, an attacker may use built-in shells, scripting engines, scheduled tasks and native network utilities for discovery, persistence or movement. This is a plausible LoTL path, not evidence that it has occurred for every attack.
03
Patch and workaround
Operational remediation based on structured source evidence.
- Status
?
Patch availability is based on structured fixed-version fields and authoritative update references. If no fix is verified, check the vendor advisory before making a change. - Fix not verified
- Affected
- Apache OpenNLP :: Core :: ML :: LibSVM: 3.0.0-M1 < 3.0.0-M4
- Fixed
- No fixed version is explicitly recorded in the structured CVE data.
- Action
- No verified patch reference is present in the current structured sources. Check the vendor advisory before making a change.
- Workaround
- No verified workaround is recorded. If business-safe, reduce exposure to the affected interface and allow only trusted sources until authoritative guidance is available.
04
Evidence and provenance
Published 6 Jul 2026 · Last source change 6 Jul 2026, 20:38 UTC · CWE-502 · Deserialization of Untrusted Data
CVE recordCVE.org · 5.2
CVSS sourceCISA ADP
EPSS source FIRST · tracked since 2026-08-14
?
The date BlackTree first stored a score for this CVE from the daily FIRST EPSS feed.European sourceENISA EUVD · EUVD-2026-41885
Product sourceCNA
Remediation sourceCVE/CNA references
CWE sourceCNA
NVD statusNVD enriched
Core structured fields are present and their contributing authorities are shown above.
Material change intelligence
View recent updates ↗What changed after publication
No material field changes have been recorded since change tracking began. Routine source refreshes and cosmetic edits are intentionally excluded.
Technical terms and abbreviations used in this report
- CVE
- Common Vulnerabilities and Exposures: the public identifier for one disclosed vulnerability.
- CVSS
- Common Vulnerability Scoring System: a technical severity framework; it is not patching priority by itself.
- EPSS
- Exploit Prediction Scoring System: FIRST's estimate of the probability that exploitation activity will be observed in the next 30 days; it is a forecast, not confirmation.
- CWE
- Common Weakness Enumeration: the standard category describing the underlying software or hardware weakness.
- CNA
- CVE Numbering Authority: an organisation authorised to assign and publish CVE records.
- CISA ADP
- Cybersecurity and Infrastructure Security Agency Authorized Data Publisher: structured enrichment added to a CVE record.
- NVD
- National Vulnerability Database: NIST's enrichment service for CVE records.
- CERT / CSIRT
- A computer security incident response team that publishes warnings or coordinates incident response.
- PoC
- Proof of concept: public material that demonstrates or helps reproduce exploitation.
- CSAF
- Common Security Advisory Framework: a machine-readable format for security advisories.
- LoTL
- Living off the land: abuse of legitimate tools or system functions during an attack.