VAR-201801-1459

Vulnerability from variot - Updated: 2023-12-18 14:01

SonicWall SonicOS on Network Security Appliance (NSA) 2017 Q4 devices has XSS via the CFS Custom Category and Cloud AV DB Exclusion Settings 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 multiple HTML-Injection vulnerabilities . 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. All versions of Dell SonicWall SonicOS are vulnerable. SonicWall SonicOS is a system that runs on it. A remote attacker could exploit this vulnerability to bypass throttling mechanisms or filter protections

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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

  • 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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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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