VAR-201801-1458
Vulnerability from variot - Updated: 2023-12-18 13:33SonicWall SonicOS on Network Security Appliance (NSA) 2016 Q4 devices has XSS via the Configure SSO screens. SonicWall SonicOS Contains a cross-site scripting vulnerability.Information may be obtained and information may be altered. Dell SonicWall SonicOS NSA is prone to HTML-Injection vulnerability. Successful exploits will allow attacker-supplied HTML and script code to run in the context of the affected browser, potentially allowing the attacker to steal cookie-based authentication credentials or to control how the site is rendered to the user. Other attacks are also possible. SonicWall SonicOS is a system that runs on it. A remote attacker could exploit this vulnerability to inject malicious code
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"id": "JVNDB-2018-001385"
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"trust": 0.8
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"type": {
"@context": {
"@vocab": "https://www.variotdbs.pl/ref/type#",
"sources": {
"@container": "@list",
"@context": {
"@vocab": "https://www.variotdbs.pl/ref/sources#"
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"data": "XSS",
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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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