Vulnerability-Lookup

GHSA-Q8H5-CHQQ-P9J3

Vulnerability from github – Published: 2022-05-24 17:21 – Updated: 2022-05-24 17:21

Details

On TP-Link TL-WR740N v4 and TL-WR740ND v4 devices, an attacker with access to the admin panel can inject HTML code and change the HTML context of the target pages and stations in the access-control settings via targets_lists_name or hosts_lists_name. The vulnerability can also be exploited through a CSRF, requiring no authentication as an administrator.

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{
  "affected": [],
  "aliases": [
    "CVE-2020-14965"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-74"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2020-06-23T14:15:00Z",
    "severity": "LOW"
  },
  "details": "On TP-Link TL-WR740N v4 and TL-WR740ND v4 devices, an attacker with access to the admin panel can inject HTML code and change the HTML context of the target pages and stations in the access-control settings via targets_lists_name or hosts_lists_name. The vulnerability can also be exploited through a CSRF, requiring no authentication as an administrator.",
  "id": "GHSA-q8h5-chqq-p9j3",
  "modified": "2022-05-24T17:21:29Z",
  "published": "2022-05-24T17:21:29Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2020-14965"
    },
    {
      "type": "WEB",
      "url": "https://github.com/g-rubert/CVE-2020-14965"
    }
  ],
  "schema_version": "1.4.0",
  "severity": []
}

CVE-2020-14965 (GCVE-0-2020-14965)

Vulnerability from cvelistv5 – Published: 2020-06-23 13:30 – Updated: 2024-08-04 13:00

Summary

Severity

No CVSS data available.

CWE

Assigner

mitre CNA under the mitre root

CNA scorecard E 28/100 over 2264 records in the last 180 days details

References

1 reference

URL	Tags
https://github.com/g-rubert/CVE-2020-14965	x_refsource_MISC

Date Public

2020-06-22 00:00

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            ],
            "url": "https://github.com/g-rubert/CVE-2020-14965"
          }
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      }
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          "versions": [
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      ],
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      "descriptions": [
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        }
      ],
      "problemTypes": [
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      ],
      "providerMetadata": {
        "dateUpdated": "2020-06-23T13:30:13.000Z",
        "orgId": "8254265b-2729-46b6-b9e3-3dfca2d5bfca",
        "shortName": "mitre"
      },
      "references": [
        {
          "tags": [
            "x_refsource_MISC"
          ],
          "url": "https://github.com/g-rubert/CVE-2020-14965"
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          "ASSIGNER": "cve@mitre.org",
          "ID": "CVE-2020-14965",
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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.

Vulnerability timeline

Sightings and recorded dates, grouped by day · UTC

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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.

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