VAR-201504-0079

Vulnerability from variot - Updated: 2025-04-12 23:04

Inductive Automation Ignition 7.7.2 does not terminate a session upon a logout action, which allows remote attackers to bypass intended access restrictions by leveraging an unattended workstation. Supplementary information : CWE Vulnerability type by CWE-254: Security Features ( Security function ) Has been identified. http://cwe.mitre.org/data/definitions/254.htmlAccess restrictions may be avoided by using an unattended workstation by a third party. Ignition is an updated version of FactoryPMI, Human Interface/SCADA, from Inductive Automation. Ignition does not delete the session after the user quits, which allows the attacker to reuse the current session. Successful exploits may allow an attacker to gain unauthorized access to the affected application

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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.
Vulnerability timeline

Sightings and recorded dates, grouped by day · UTC

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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.