Vulnerability-Lookup

GHSA-82GM-Q2VC-G3X3

Vulnerability from github – Published: 2022-04-16 00:00 – Updated: 2022-05-14 00:01

Details

A vulnerability in the History API of Cisco SD-WAN vManage Software could allow an authenticated, remote attacker to gain access to sensitive information on an affected system. This vulnerability is due to insufficient API authorization checking on the underlying operating system. An attacker could exploit this vulnerability by sending a crafted API request to Cisco vManage as a lower-privileged user and gaining access to sensitive information that they would not normally be authorized to access.

Severity

6.5 (Medium)


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

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{
  "affected": [],
  "aliases": [
    "CVE-2022-20747"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-202"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2022-04-15T15:15:00Z",
    "severity": "MODERATE"
  },
  "details": "A vulnerability in the History API of Cisco SD-WAN vManage Software could allow an authenticated, remote attacker to gain access to sensitive information on an affected system. This vulnerability is due to insufficient API authorization checking on the underlying operating system. An attacker could exploit this vulnerability by sending a crafted API request to Cisco vManage as a lower-privileged user and gaining access to sensitive information that they would not normally be authorized to access.",
  "id": "GHSA-82gm-q2vc-g3x3",
  "modified": "2022-05-14T00:01:19Z",
  "published": "2022-04-16T00:00:47Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-20747"
    },
    {
      "type": "WEB",
      "url": "https://tools.cisco.com/security/center/content/CiscoSecurityAdvisory/cisco-sa-sdwan-vman-infodis-73sHJNEq"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N",
      "type": "CVSS_V3"
    }
  ]
}

CVE-2022-20747 (GCVE-0-2022-20747)

Vulnerability from cvelistv5 – Published: 2022-04-15 14:20 – Updated: 2024-11-06 16:24

Title

Cisco SD-WAN vManage Software Information Disclosure Vulnerability

Summary

Severity

6.5 (Medium)


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

SSVC

Exploitation: none Automatable: no Technical Impact: partial

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2024-11-06 15:58 UTC

CWE

CWE-202

Assigner

cisco mitre root

References

1 reference

URL	Tags
https://tools.cisco.com/security/center/content/C…	vendor-advisoryx_refsource_CISCO

Impacted products

1 product

Vendor	Product	Version
Cisco	Cisco SD-WAN vManage	Affected: n/a

Date Public

2022-04-13 00:00

Show details on NVD website

JSON

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  "containers": {
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      {
        "providerMetadata": {
          "dateUpdated": "2024-08-03T02:24:49.306Z",
          "orgId": "af854a3a-2127-422b-91ae-364da2661108",
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        },
        "references": [
          {
            "name": "20220413 Cisco SD-WAN vManage Software Information Disclosure Vulnerability",
            "tags": [
              "vendor-advisory",
              "x_refsource_CISCO",
              "x_transferred"
            ],
            "url": "https://tools.cisco.com/security/center/content/CiscoSecurityAdvisory/cisco-sa-sdwan-vman-infodis-73sHJNEq"
          }
        ],
        "title": "CVE Program Container"
      },
      {
        "metrics": [
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            "other": {
              "content": {
                "id": "CVE-2022-20747",
                "options": [
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                  },
                  {
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                  },
                  {
                    "Technical Impact": "partial"
                  }
                ],
                "role": "CISA Coordinator",
                "timestamp": "2024-11-06T15:58:54.497868Z",
                "version": "2.0.3"
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        "providerMetadata": {
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          "orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
          "shortName": "CISA-ADP"
        },
        "title": "CISA ADP Vulnrichment"
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    ],
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        }
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      "exploits": [
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      "metrics": [
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            "attackVector": "NETWORK",
            "availabilityImpact": "NONE",
            "baseScore": 6.5,
            "baseSeverity": "MEDIUM",
            "confidentialityImpact": "HIGH",
            "integrityImpact": "NONE",
            "privilegesRequired": "LOW",
            "scope": "UNCHANGED",
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        "discovery": "INTERNAL"
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          "STATE": "PUBLIC",
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        },
        "affects": {
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            }
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  },
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}

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.