CVE-2023-30617 (GCVE-0-2023-30617)

Vulnerability from cvelistv5 – Published: 2024-01-03 15:29 – Updated: 2025-06-16 18:10
VLAI
Title
Leverage the kruise-daemon pod to list all secrets in the entire cluster
Summary
Kruise provides automated management of large-scale applications on Kubernetes. Starting in version 0.8.0 and prior to versions 1.3.1, 1.4.1, and 1.5.2, an attacker who has gained root privilege of the node that kruise-daemon run can leverage the kruise-daemon pod to list all secrets in the entire cluster. After that, the attacker can leverage the "captured" secrets (e.g. the kruise-manager service account token) to gain extra privileges such as pod modification. Versions 1.3.1, 1.4.1, and 1.5.2 fix this issue. A workaround is available. For users that do not require imagepulljob functions, they can modify kruise-daemon-role to drop the cluster level secret get/list privilege.
SSVC
Exploitation: none Automatable: no Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-06-16 18:09 UTC
CWE
  • CWE-250 - Execution with Unnecessary Privileges
  • CWE-269 - Improper Privilege Management
References
Impacted products
Vendor Product Version CPE status
openkruise kruise Affected: >= 0.8.0, < 1.3.1
Affected: = 1.4.0
Affected: >= 1.5.0, < 1.5.2
guessed Create a notification for this product.
Show details on NVD website

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                  "lang": "en",
                  "type": "CWE"
                }
              ]
            },
            {
              "descriptions": [
                {
                  "cweId": "CWE-269",
                  "description": "CWE-269: Improper Privilege Management",
                  "lang": "en",
                  "type": "CWE"
                }
              ]
            }
          ],
          "providerMetadata": {
            "dateUpdated": "2024-01-03T15:29:17.552Z",
            "orgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
            "shortName": "GitHub_M"
          },
          "references": [
            {
              "name": "https://github.com/openkruise/kruise/security/advisories/GHSA-437m-7hj5-9mpw",
              "tags": [
                "x_refsource_CONFIRM"
              ],
              "url": "https://github.com/openkruise/kruise/security/advisories/GHSA-437m-7hj5-9mpw"
            }
          ],
          "source": {
            "advisory": "GHSA-437m-7hj5-9mpw",
            "discovery": "UNKNOWN"
          },
          "title": "Leverage the kruise-daemon pod to list all secrets in the entire cluster"
        }
      },
      "cveMetadata": {
        "assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
        "assignerShortName": "GitHub_M",
        "cveId": "CVE-2023-30617",
        "datePublished": "2024-01-03T15:29:17.552Z",
        "dateReserved": "2023-04-13T13:25:18.832Z",
        "dateUpdated": "2025-06-16T18:10:14.525Z",
        "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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