VAR-202009-0219
Vulnerability from variot - Updated: 2025-12-19 22:48SQL injection vulnerability exists in the CHaD.asmx web service functionality of eDNA Enterprise Data Historian 3.0.1.2/7.5.4989.33053. Specially crafted SOAP web requests can cause SQL injections resulting in data compromise. Parameter ClassName in CHaD.asmx is vulnerable to unauthenticated SQL injection attacks. Aveva eDNA Enterprise Data Historian is a real-time historical data management software from AVEVA (Aveva) in the UK. The software can collect, store, process, and display asset-related information to provide better information for decision-making. The vulnerability stems from the lack of validation of externally input SQL statements in database-based applications. An attacker can exploit this vulnerability to execute illegal SQL commands. A remote attacker could send specially-crafted SQL statements, which could allow the malicious user to view, add, modify or delete information in the back-end database
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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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