Vulnerability-Lookup

VAR-202203-1172

Vulnerability from variot - Updated: 2023-12-18 13:46

BigAnt Software BigAnt Server v5.6.06 was discovered to be vulnerable to directory traversal attacks. BigAnt Software BigAnt Server is a server of Australia's BigAnt Studios.

BigAnt Software BigAnt Server v5.6.06 has security vulnerabilities, and no detailed vulnerability details are currently provided

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CVE-2022-23347 (GCVE-0-2022-23347)

Vulnerability from cvelistv5 – Published: 2022-03-21 19:23 – Updated: 2026-07-09 00:16

Summary

BigAnt Software BigAnt Server v5.6.06 was discovered to be vulnerable to directory traversal attacks.

Severity

No CVSS data available.

CWE

Assigner

mitre mitre root

References

2 references

URL	Tags
https://github.com/bzyo/cve-pocs/tree/master/CVE-…
https://www.bigantsoft.com/

Show details on NVD website

JSON

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                },
                "vendor_name": "n/a"
              }
            ]
          }
        },
        "data_format": "MITRE",
        "data_type": "CVE",
        "data_version": "4.0",
        "description": {
          "description_data": [
            {
              "lang": "eng",
              "value": "BigAnt Software BigAnt Server v5.6.06 was discovered to be vulnerable to directory traversal attacks."
            }
          ]
        },
        "problemtype": {
          "problemtype_data": [
            {
              "description": [
                {
                  "lang": "eng",
                  "value": "n/a"
                }
              ]
            }
          ]
        },
        "references": {
          "reference_data": [
            {
              "name": "http://bigant.com",
              "refsource": "MISC",
              "url": "http://bigant.com"
            },
            {
              "name": "https://github.com/bzyo/cve-pocs/tree/master/CVE-2022-23347",
              "refsource": "MISC",
              "url": "https://github.com/bzyo/cve-pocs/tree/master/CVE-2022-23347"
            },
            {
              "name": "https://www.bigantsoft.com/",
              "refsource": "MISC",
              "url": "https://www.bigantsoft.com/"
            }
          ]
        }
      }
    }
  },
  "cveMetadata": {
    "assignerOrgId": "8254265b-2729-46b6-b9e3-3dfca2d5bfca",
    "assignerShortName": "mitre",
    "cveId": "CVE-2022-23347",
    "datePublished": "2022-03-21T19:23:37.000Z",
    "dateReserved": "2022-01-18T00:00:00.000Z",
    "dateUpdated": "2026-07-09T00:16:51.092Z",
    "state": "PUBLISHED"
  },
  "dataType": "CVE_RECORD",
  "dataVersion": "5.2"
}

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.