Vulnerability-Lookup

GHSA-P979-P78R-6JP8

Vulnerability from github – Published: 2024-04-03 18:30 – Updated: 2024-04-03 18:30

Details

A vulnerability in Cisco Nexus Dashboard could allow an authenticated, remote attacker to learn cluster deployment information on an affected device.

This vulnerability is due to improper access controls on a specific API endpoint. An attacker could exploit this vulnerability by sending queries to the API endpoint. A successful exploit could allow an attacker to access metrics and information about devices in the Nexus Dashboard cluster.

Severity

4.3 (Medium)


                  
                    CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:N/A:N

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{
  "affected": [],
  "aliases": [
    "CVE-2024-20283"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-284"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2024-04-03T17:15:48Z",
    "severity": "MODERATE"
  },
  "details": "A vulnerability in Cisco Nexus Dashboard could allow an authenticated, remote attacker to learn cluster deployment information on an affected device.\n\n This vulnerability is due to improper access controls on a specific API endpoint. An attacker could exploit this vulnerability by sending queries to the API endpoint. A successful exploit could allow an attacker to access metrics and information about devices in the Nexus Dashboard cluster.",
  "id": "GHSA-p979-p78r-6jp8",
  "modified": "2024-04-03T18:30:41Z",
  "published": "2024-04-03T18:30:41Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2024-20283"
    },
    {
      "type": "WEB",
      "url": "https://sec.cloudapps.cisco.com/security/center/content/CiscoSecurityAdvisory/cisco-sa-ndidv-LmXdvAf2"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:N/A:N",
      "type": "CVSS_V3"
    }
  ]
}

CVE-2024-20283 (GCVE-0-2024-20283)

Vulnerability from cvelistv5 – Published: 2024-04-03 16:25 – Updated: 2024-08-01 21:59

Summary

A vulnerability in Cisco Nexus Dashboard could allow an authenticated, remote attacker to learn cluster deployment information on an affected device. This vulnerability is due to improper access controls on a specific API endpoint. An attacker could exploit this vulnerability by sending queries to the API endpoint. A successful exploit could allow an attacker to access metrics and information about devices in the Nexus Dashboard cluster.

Severity

4.3 (Medium)


                        
                          CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:N/A:N

SSVC

Exploitation: none Automatable: no Technical Impact: partial

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2024-04-03 18:22 UTC

CWE

CWE-284 - Improper Access Control

Assigner

cisco mitre root

References

1 reference

URL	Tags
https://sec.cloudapps.cisco.com/security/center/c…

Impacted products

1 product

Vendor	Product	Version
Cisco	Cisco Nexus Dashboard	Affected: 1.1(0c) Affected: 1.1(0d) Affected: 1.1(2h) Affected: 1.1(2i) Affected: 1.1(3c) Affected: 1.1(3d) Affected: 1.1(3e) Affected: 1.1(3f) Affected: 2.0(1b) Affected: 2.0(1d) Affected: 2.0(2g) Affected: 2.0(2h) Affected: 2.1(1d) Affected: 2.1(1e) Affected: 2.1(2d) Affected: 2.1(2f) Affected: 2.2(1e) Affected: 2.2(1h) Affected: 2.2(2d) Affected: 2.3(1c) Affected: 2.3(2b) Affected: 2.3(2c) Affected: 2.3(2d) Affected: 2.3(2e) Affected: 3.0(1f) Affected: 3.0(1i)

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{
  "containers": {
    "adp": [
      {
        "metrics": [
          {
            "other": {
              "content": {
                "id": "CVE-2024-20283",
                "options": [
                  {
                    "Exploitation": "none"
                  },
                  {
                    "Automatable": "no"
                  },
                  {
                    "Technical Impact": "partial"
                  }
                ],
                "role": "CISA Coordinator",
                "timestamp": "2024-04-03T18:22:09.601659Z",
                "version": "2.0.3"
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        "providerMetadata": {
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    "cna": {
      "affected": [
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        }
      ],
      "exploits": [
        {
          "lang": "en",
          "value": "The Cisco PSIRT is not aware of any public announcements or malicious use of the vulnerability that is described in this advisory."
        }
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      "metrics": [
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            "confidentialityImpact": "LOW",
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    "datePublished": "2024-04-03T16:25:09.906Z",
    "dateReserved": "2023-11-08T15:08:07.626Z",
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    "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.