VAR-201810-0494

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

LAquis SCADA Versions 4.1.0.3870 and prior has several stack-based buffer overflow vulnerabilities, which may allow remote code execution. LAquis SCADA Contains a buffer error vulnerability.Information is obtained, information is altered, and service operation is disrupted (DoS) There is a possibility of being put into a state. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file.The specific flaw exists within aq.exe. The issue results from the lack of proper validation of the length of user-supplied data prior to copying it to a fixed-length stack-based buffer. An attacker can leverage this functionality to execute code in the context of the current process. LAquis SCADA is a suite of SCADA software for monitoring and data acquisition

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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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Detection rules are retrieved from Rulezet.

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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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