CVE-2026-100730 (GCVE-0-2026-100730)
Vulnerability from cvelistv5 – Published: 2026-10-09 13:44 – Updated: 2026-10-09 13:44
VLAI
EPSS
VEX
Title
Grid Protection Alliance openPDC and openHistorian Deserialization of Untrusted Data
Summary
A service console interface on openPDC and openHistorian deserializes a client-supplied data structure. On systems using Windows Authentication, an attacker must already be authenticated to reach this function; on systems without Windows Authentication, this is reachable by an unauthenticated network attacker. This allows an attacker to trigger deserialization of an arbitrary object graph, which could allow remote code execution under the privileges of the affected service account.
Severity
9.8 (Critical)
CWE
Assigner
References
Impacted products
3 products
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Grid Protection Alliance | openPDC |
Affected:
0 , < 2.9.477
(custom)
Affected: 0 , < 2.9.482 (custom) Unaffected: 2.9.482 |
guessed | |
| Grid Protection Alliance | openPDC (Docker image) |
Affected:
0 , < 2.9.477
(custom)
Affected: 0 , < 2.9.482 (custom) |
guessed | |
| Grid Protection Alliance | openHistorian |
Affected:
0 , < 2.8.580
(custom)
Affected: 0 , < 2.8.585 (custom) Unaffected: 2.8.585 |
guessed |
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"providerMetadata": {
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"orgId": "7d14cffa-0d7d-4270-9dc0-52cabd5a23a6",
"shortName": "icscert"
},
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},
{
"url": "https://github.com/cisagov/CSAF/blob/develop/csaf_files/OT/white/2026/icsa-26-281-02.json"
}
],
"solutions": [
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}
],
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},
"title": "Grid Protection Alliance openPDC and openHistorian Deserialization of Untrusted Data",
"workarounds": [
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}
],
"value": "Grid Protection Alliance does not recommend production use of published Docker images in any case. The fix for this vulnerability has not been published to the Docker image."
}
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"datePublished": "2026-10-09T13:44:39.190Z",
"dateReserved": "2026-10-05T16:54:01.616Z",
"dateUpdated": "2026-10-09T13:44:39.190Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.2",
"vulnerability-lookup:meta": {
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"date": "2026-10-10",
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"percentile": "0.48438"
},
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
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
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- 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.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- 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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