Vulnerability-Lookup

VAR-202202-0283

Vulnerability from variot - Updated: 2022-05-04 08:51

A CWE-79: Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting') vulnerability exists that could cause a web session compromise when an attacker injects and then executes arbitrary malicious JavaScript code inside the target browser. Affected Product: spaceLYnk (V2.6.2 and prior), Wiser for KNX (formerly homeLYnk) (V2.6.2 and prior), fellerLYnk (V2.6.2 and prior)

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CVE-2022-22812 (GCVE-0-2022-22812)

Vulnerability from cvelistv5 – Published: 2022-02-09 22:05 – Updated: 2024-08-03 03:21

Summary

Severity

No CVSS data available.

CWE

CWE-79 - Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')

Assigner

schneider mitre root

References

1 reference

URL	Tags
https://download.schneider-electric.com/files?p_D…	x_refsource_MISC

Impacted products

1 product

Vendor	Product	Version
n/a	spaceLYnk (V2.6.2 and prior), Wiser for KNX (formerly homeLYnk) (V2.6.2 and prior), fellerLYnk (V2.6.2 and prior)	Affected: spaceLYnk (V2.6.2 and prior), Wiser for KNX (formerly homeLYnk) (V2.6.2 and prior), fellerLYnk (V2.6.2 and prior)

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JSON

To clipboard

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              "value": "A CWE-79: Improper Neutralization of Input During Web Page Generation (\u0027Cross-site Scripting\u0027) vulnerability exists that could cause a web session compromise when an attacker injects and then executes arbitrary malicious JavaScript code inside the target browser. Affected Product: spaceLYnk (V2.6.2 and prior), Wiser for KNX (formerly homeLYnk) (V2.6.2 and prior), fellerLYnk (V2.6.2 and prior)"
            }
          ]
        },
        "problemtype": {
          "problemtype_data": [
            {
              "description": [
                {
                  "lang": "eng",
                  "value": "CWE-79: Improper Neutralization of Input During Web Page Generation (\u0027Cross-site Scripting\u0027)"
                }
              ]
            }
          ]
        },
        "references": {
          "reference_data": [
            {
              "name": "https://download.schneider-electric.com/files?p_Doc_Ref=SEVD-2022-039-04",
              "refsource": "MISC",
              "url": "https://download.schneider-electric.com/files?p_Doc_Ref=SEVD-2022-039-04"
            }
          ]
        }
      }
    }
  },
  "cveMetadata": {
    "assignerOrgId": "076d1eb6-cfab-4401-b34d-6dfc2a413bdb",
    "assignerShortName": "schneider",
    "cveId": "CVE-2022-22812",
    "datePublished": "2022-02-09T22:05:09.000Z",
    "dateReserved": "2022-01-07T00:00:00.000Z",
    "dateUpdated": "2024-08-03T03:21:49.155Z",
    "state": "PUBLISHED"
  },
  "dataType": "CVE_RECORD",
  "dataVersion": "5.1"
}

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.

Detection rules are retrieved from Rulezet.

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.

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.