FKIE_CVE-2026-102508
Vulnerability from fkie_nvd - Published: 2026-09-30 08:16 - Updated: 2026-09-30 16:14
Severity
Summary
Improper Verification of Cryptographic Signature and Improper Certificate Validation in the OPC UA driver of Apache PLC4X (PLC4J) allows an attacker in a network position between client and server to impersonate the OPC UA server and to read, forge or modify secure-channel traffic, including user credential ssent by the client.
The defect manifests differently depending on the version:
- In 0.9.0 through 0.11.0 a failed message-signature check is only logged and never enforced, and there is no mechanism to verify the server certificate: it is taken from the unauthenticated GetEndpoints discovery response and used to encrypt the user's password.
- In 0.12.0 through 0.13.1 the signature check is inverted (valid signatures are rejected, invalid ones accepted), and server certificates are accepted without a trust anchor by default.
- In all affected versions the default security policy is None. Starting with 0.12.0 the driver additionally continues silently at a weaker security policy than the one configured, and starting with 0.13.0 endpoint selection prefers the weakest matching endpoint.
Users checking only for one of these mechanisms may wrongly conclude they are unaffected.
This issue affects Apache PLC4X: from 0.9.0 before 1.0.0.
Users are recommended to upgrade to version 1.0.0, which fixes the issue. Version 1.0.0 verifies message signatures correctly, refuses to connect unless the server certificate can be verified against a configured trust store or pinned certificate, defaults to Basic256Sha256 with SignAndEncrypt, and fails the
connection if the negotiated security policy is weaker than the configured one.
References
Impacted products
| Vendor | Product | Version |
|---|
{
"affected": [
{
"affectedData": [
{
"collectionURL": "https://repo.maven.apache.org/maven2",
"defaultStatus": "unaffected",
"packageName": "org.apache.plc4x:plc4j-driver-opcua",
"packageURL": "pkg:maven/org.apache.plc4x/plc4j-driver-opcua",
"product": "Apache PLC4X",
"vendor": "Apache Software Foundation",
"versions": [
{
"lessThan": "1.0.0",
"status": "affected",
"version": "0.9.0",
"versionType": "semver"
},
{
"status": "unaffected",
"version": "1.0.0",
"versionType": "semver"
}
]
}
],
"source": "security@apache.org"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "Improper Verification of Cryptographic Signature and Improper Certificate Validation in the OPC UA driver of Apache PLC4X (PLC4J) allows an attacker in a network position between client and server to impersonate the OPC UA server and to read, forge or modify secure-channel traffic, including user credential ssent by the client.\n\nThe defect manifests differently depending on the version:\n- In 0.9.0 through 0.11.0 a failed message-signature check is only logged and never enforced, and there is no mechanism to verify the server certificate: it is taken from the unauthenticated GetEndpoints discovery response and used to encrypt the user\u0027s password.\n- In 0.12.0 through 0.13.1 the signature check is inverted (valid signatures are rejected, invalid ones accepted), and server certificates are accepted without a trust anchor by default.\n- In all affected versions the default security policy is None. Starting with 0.12.0 the driver additionally continues silently at a weaker security policy than the one configured, and starting with 0.13.0 endpoint selection prefers the weakest matching endpoint.\n\nUsers checking only for one of these mechanisms may wrongly conclude they are unaffected.\n\nThis issue affects Apache PLC4X: from 0.9.0 before 1.0.0.\n\nUsers are recommended to upgrade to version 1.0.0, which fixes the issue. Version 1.0.0 verifies message signatures correctly, refuses to connect unless the server certificate can be verified against a configured trust store or pinned certificate, defaults to Basic256Sha256 with SignAndEncrypt, and fails the\nconnection if the negotiated security policy is weaker than the configured one."
}
],
"id": "CVE-2026-102508",
"lastModified": "2026-09-30T16:14:10.347",
"metrics": {
"cvssMetricV40": [
{
"cvssData": {
"Automatable": "NOT_DEFINED",
"Recovery": "NOT_DEFINED",
"Safety": "NOT_DEFINED",
"attackComplexity": "LOW",
"attackRequirements": "PRESENT",
"attackVector": "NETWORK",
"availabilityRequirement": "NOT_DEFINED",
"baseScore": 9.2,
"baseSeverity": "CRITICAL",
"confidentialityRequirement": "NOT_DEFINED",
"exploitMaturity": "NOT_DEFINED",
"integrityRequirement": "NOT_DEFINED",
"modifiedAttackComplexity": "NOT_DEFINED",
"modifiedAttackRequirements": "NOT_DEFINED",
"modifiedAttackVector": "NOT_DEFINED",
"modifiedPrivilegesRequired": "NOT_DEFINED",
"modifiedSubAvailabilityImpact": "NOT_DEFINED",
"modifiedSubConfidentialityImpact": "NOT_DEFINED",
"modifiedSubIntegrityImpact": "NOT_DEFINED",
"modifiedUserInteraction": "NOT_DEFINED",
"modifiedVulnAvailabilityImpact": "NOT_DEFINED",
"modifiedVulnConfidentialityImpact": "NOT_DEFINED",
"modifiedVulnIntegrityImpact": "NOT_DEFINED",
"privilegesRequired": "NONE",
"providerUrgency": "NOT_DEFINED",
"subAvailabilityImpact": "NONE",
"subConfidentialityImpact": "NONE",
"subIntegrityImpact": "NONE",
"userInteraction": "NONE",
"valueDensity": "NOT_DEFINED",
"vectorString": "CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X",
"version": "4.0",
"vulnAvailabilityImpact": "HIGH",
"vulnConfidentialityImpact": "HIGH",
"vulnIntegrityImpact": "HIGH",
"vulnerabilityResponseEffort": "NOT_DEFINED"
},
"source": "security@apache.org",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2026-102508",
"options": [
{
"exploitation": "none"
},
{
"automatable": "no"
},
{
"technicalImpact": "total"
}
],
"role": "CISA Coordinator",
"timestamp": "2026-09-30T14:39:20.327319Z",
"version": "2.0.3"
}
}
]
},
"published": "2026-09-30T08:16:31.903",
"references": [
{
"source": "security@apache.org",
"url": "https://lists.apache.org/thread.html/o076mcnsx6wnqpdy780m7s6hddbbnjfw"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"url": "http://www.openwall.com/lists/oss-security/2026/09/30/4"
}
],
"sourceIdentifier": "security@apache.org",
"vulnStatus": "Awaiting Analysis",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-295"
},
{
"lang": "en",
"value": "CWE-347"
},
{
"lang": "en",
"value": "CWE-757"
}
],
"source": "security@apache.org",
"type": "Secondary"
}
]
}
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Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
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- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
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- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.
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