GHSA-GPQQ-59RP-3C3W

Vulnerability from github – Published: 2023-03-27 15:30 – Updated: 2023-03-31 16:08
VLAI
Summary
Apache InLong vulnerable to JDBC Deserialization of Untrusted Data
Details

Apache InLong versions from 1.1.0 through 1.5.0 are vulnerable to Java Database Connectivity (JDBC) deserialization of untrusted data from the MySQL JDBC URL in MySQLDataNode. It could be triggered by authenticated users of InLong. This has been patched in version 1.6.0. Users are advised to upgrade to Apache InLong's latest version or cherry-pick the patch to solve it.

Show details on source website

{
  "affected": [
    {
      "package": {
        "ecosystem": "Maven",
        "name": "org.apache.inlong:inlong-manager"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "1.1.0"
            },
            {
              "fixed": "1.6.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2023-27296"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-502"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2023-03-27T22:10:31Z",
    "nvd_published_at": "2023-03-27T15:15:00Z",
    "severity": "HIGH"
  },
  "details": "Apache InLong versions from 1.1.0 through 1.5.0 are vulnerable to Java Database Connectivity (JDBC) deserialization of untrusted data from the MySQL JDBC URL in MySQLDataNode. It could be triggered by authenticated users of InLong. This has been patched in version 1.6.0. Users are advised to upgrade to Apache InLong\u0027s latest version or cherry-pick the [patch](https://github.com/apache/inlong/pull/7422) to solve it.",
  "id": "GHSA-gpqq-59rp-3c3w",
  "modified": "2023-03-31T16:08:49Z",
  "published": "2023-03-27T15:30:16Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2023-27296"
    },
    {
      "type": "WEB",
      "url": "https://github.com/apache/inlong/pull/7422"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/apache/inlong"
    },
    {
      "type": "WEB",
      "url": "https://lists.apache.org/thread/xbvtjw9bwzgbo9fp1by8o3p49nf59xzt"
    },
    {
      "type": "WEB",
      "url": "https://programmer.help/blogs/jdbc-deserialization-vulnerability-learning.html"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "Apache InLong vulnerable to JDBC Deserialization of Untrusted Data"
}


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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

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Nomenclature

  • Seen: The vulnerability was mentioned, discussed, or observed by the user.
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