CVE-2024-32480 (GCVE-0-2024-32480)

Vulnerability from cvelistv5 – Published: 2024-04-22 22:10 – Updated: 2024-08-02 02:13
VLAI
Title
LibreNMS's Time-Based Blind SQL injection leads to database extraction
Summary
LibreNMS is an open-source, PHP/MySQL/SNMP-based network monitoring system. Versions prior to 24.4.0 are vulnerable to SQL injection. The `order` parameter is obtained from `$request`. After performing a string check, the value is directly incorporated into an SQL statement and concatenated, resulting in a SQL injection vulnerability. An attacker may extract a whole database this way. Version 24.4.0 fixes the issue.
SSVC
Exploitation: none Automatable: yes Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2024-04-23 00:21 UTC
CWE
  • CWE-89 - Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')
References
Impacted products
Vendor Product Version CPE status
librenms librenms Affected: < 24.4.0
guessed Create a notification for this product.
librenms librenms Affected: *
    cpe:2.3:a:librenms:librenms:*:*:*:*:*:*:*:*
Create a notification for this product.
Show details on NVD website

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              "name": "https://github.com/librenms/librenms/commit/83fe4b10c440d69a47fe2f8616e290ba2bd3a27c",
              "tags": [
                "x_refsource_MISC"
              ],
              "url": "https://github.com/librenms/librenms/commit/83fe4b10c440d69a47fe2f8616e290ba2bd3a27c"
            }
          ],
          "source": {
            "advisory": "GHSA-jh57-j3vq-h438",
            "discovery": "UNKNOWN"
          },
          "title": "LibreNMS\u0027s Time-Based Blind SQL injection leads to database extraction"
        }
      },
      "cveMetadata": {
        "assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
        "assignerShortName": "GitHub_M",
        "cveId": "CVE-2024-32480",
        "datePublished": "2024-04-22T22:10:50.221Z",
        "dateReserved": "2024-04-12T19:41:51.168Z",
        "dateUpdated": "2024-08-02T02:13:39.173Z",
        "state": "PUBLISHED"
      },
      "dataType": "CVE_RECORD",
      "dataVersion": "5.1"
    }
  }
}



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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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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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