Vulnerability-Lookup

GHSA-F57C-P28V-H84W

Vulnerability from github – Published: 2022-05-24 19:15 – Updated: 2022-05-24 19:15

Details

Dr.Web Firewall 12.5.2.4160 on Windows incorrectly restricts applications signed by Dr.Web. A DLL for a custom payload within a legitimate binary (e.g., frwl_svc.exe) bypasses firewall filters.

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{
  "affected": [],
  "aliases": [
    "CVE-2021-28130"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-427"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2021-09-24T16:15:00Z",
    "severity": "HIGH"
  },
  "details": "Dr.Web Firewall 12.5.2.4160 on Windows incorrectly restricts applications signed by Dr.Web. A DLL for a custom payload within a legitimate binary (e.g., frwl_svc.exe) bypasses firewall filters.",
  "id": "GHSA-f57c-p28v-h84w",
  "modified": "2022-05-24T19:15:42Z",
  "published": "2022-05-24T19:15:42Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-28130"
    },
    {
      "type": "WEB",
      "url": "https://habr.com/ru/company/pm/blog/579328"
    },
    {
      "type": "WEB",
      "url": "https://news.drweb.ru/show/?i=14180\u0026lng=ru"
    }
  ],
  "schema_version": "1.4.0",
  "severity": []
}

CVE-2021-28130 (GCVE-0-2021-28130)

Vulnerability from cvelistv5 – Published: 2021-09-24 15:27 – Updated: 2024-08-03 21:33

Summary

Dr.Web Firewall 12.5.2.4160 on Windows incorrectly restricts applications signed by Dr.Web. A DLL for a custom payload within a legitimate binary (e.g., frwl_svc.exe) bypasses firewall filters.

Severity

No CVSS data available.

CWE

Assigner

mitre CNA under the mitre root

CNA scorecard E 29/100 over 2354 records in the last 180 days details

References

2 references

URL	Tags
https://news.drweb.ru/show/?i=14180&lng=ru	x_refsource_MISC
https://habr.com/ru/company/pm/blog/579328/	x_refsource_MISC

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{
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        "providerMetadata": {
          "dateUpdated": "2024-08-03T21:33:17.447Z",
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        "references": [
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            ],
            "url": "https://news.drweb.ru/show/?i=14180\u0026lng=ru"
          },
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              "x_refsource_MISC",
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            ],
            "url": "https://habr.com/ru/company/pm/blog/579328/"
          }
        ],
        "title": "CVE Program Container"
      }
    ],
    "cna": {
      "affected": [
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          "versions": [
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      ],
      "providerMetadata": {
        "dateUpdated": "2021-09-24T15:29:20.000Z",
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            "x_refsource_MISC"
          ],
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          "ID": "CVE-2021-28130",
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  "cveMetadata": {
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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.

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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