Vulnerability-Lookup

VAR-202212-1032

Vulnerability from variot - Updated: 2023-12-18 13:55

Improper neutralization of input during web page generation [CWE-79] in FortiSOAR 7.0.0 through 7.0.3 and 7.2.0 may allow an authenticated attacker to inject HTML tags via input fields of various components within FortiSOAR. fortinet's FortiSOAR Exists in a cross-site scripting vulnerability.Information may be obtained and information may be tampered with

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CVE-2022-38379 (GCVE-0-2022-38379)

Vulnerability from cvelistv5 – Published: 2022-12-06 16:00 – Updated: 2024-10-22 20:51

Summary

Severity

3.4 (Low)


                        
                          CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:U/C:N/I:L/A:N/E:F/RL:X/RC:X

SSVC

Exploitation: none Automatable: no Technical Impact: partial

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2024-10-22 20:18 UTC

CWE

CWE-79 - Execute unauthorized code or commands

Assigner

fortinet mitre root

References

1 reference

URL	Tags
https://fortiguard.com/psirt/FG-IR-22-220

Impacted products

1 product

Vendor	Product	Version
Fortinet	FortiSOAR	Affected: 7.2.0 Affected: 7.0.0 , ≤ 7.0.3 (semver)

Show details on NVD website

JSON

To clipboard

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          "value": "Improper neutralization of input during web page generation [CWE-79] in FortiSOAR 7.0.0 through 7.0.3 and 7.2.0 may allow an authenticated attacker to inject HTML tags via input fields of various components within FortiSOAR."
        }
      ],
      "metrics": [
        {
          "cvssV3_1": {
            "attackComplexity": "LOW",
            "attackVector": "NETWORK",
            "availabilityImpact": "NONE",
            "baseScore": 3.4,
            "baseSeverity": "LOW",
            "confidentialityImpact": "NONE",
            "integrityImpact": "LOW",
            "privilegesRequired": "LOW",
            "scope": "UNCHANGED",
            "userInteraction": "REQUIRED",
            "vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:U/C:N/I:L/A:N/E:F/RL:X/RC:X",
            "version": "3.1"
          },
          "format": "CVSS"
        }
      ],
      "problemTypes": [
        {
          "descriptions": [
            {
              "cweId": "CWE-79",
              "description": "Execute unauthorized code or commands",
              "lang": "en",
              "type": "CWE"
            }
          ]
        }
      ],
      "providerMetadata": {
        "dateUpdated": "2022-12-06T16:00:58.746Z",
        "orgId": "6abe59d8-c742-4dff-8ce8-9b0ca1073da8",
        "shortName": "fortinet"
      },
      "references": [
        {
          "name": "https://fortiguard.com/psirt/FG-IR-22-220",
          "url": "https://fortiguard.com/psirt/FG-IR-22-220"
        }
      ],
      "solutions": [
        {
          "lang": "en",
          "value": "Please upgrade to FortiSOAR version 7.2.1 or above "
        }
      ]
    }
  },
  "cveMetadata": {
    "assignerOrgId": "6abe59d8-c742-4dff-8ce8-9b0ca1073da8",
    "assignerShortName": "fortinet",
    "cveId": "CVE-2022-38379",
    "datePublished": "2022-12-06T16:00:58.746Z",
    "dateReserved": "2022-08-16T14:17:48.481Z",
    "dateUpdated": "2024-10-22T20:51:29.381Z",
    "requesterUserId": "a0475cc0-be89-4a25-97b3-d1b8023a8677",
    "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.