Vulnerability-Lookup

CNVD-2021-18235

Vulnerability from cnvd - Published: 2021-03-17

Title

多款Realtek产品缓冲区溢出漏洞

Description

Realtek RTL8195AM等都是中国台湾瑞昱半导体（Realtek）公司的一款物联网微控制器。多款Realtek产品中存在缓冲区溢出漏洞。远程攻击者可借助特制EAPOL-Key数据包利用该漏洞在系统上执行任意代码。

Severity

中

Patch Name

多款Realtek产品缓冲区溢出漏洞的补丁

Patch Description

Realtek RTL8195AM等都是中国台湾瑞昱半导体（Realtek）公司的一款物联网微控制器。多款Realtek产品中存在缓冲区溢出漏洞。远程攻击者可借助特制EAPOL-Key数据包利用该漏洞在系统上执行任意代码。目前，供应商发布了安全公告及相关补丁信息，修复了此漏洞。

Formal description

目前厂商已发布升级补丁以修复漏洞，详情请关注厂商主页： http://www.realtek.com/

Reference

https://www.amebaiot.com/en/arduino-faq/

Impacted products

Name
['Realtek RTL8710AF <2.0.6', 'Realtek RTL8711AF <2.0.6', 'Realtek RTL8711AM <2.0.6', 'Realtek RTL8195AM <2.0.6']

Show details on source website

JSON

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{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2020-9395"
    }
  },
  "description": "Realtek RTL8195AM\u7b49\u90fd\u662f\u4e2d\u56fd\u53f0\u6e7e\u745e\u6631\u534a\u5bfc\u4f53\uff08Realtek\uff09\u516c\u53f8\u7684\u4e00\u6b3e\u7269\u8054\u7f51\u5fae\u63a7\u5236\u5668\u3002\n\n\u591a\u6b3eRealtek\u4ea7\u54c1\u4e2d\u5b58\u5728\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\u3002\u8fdc\u7a0b\u653b\u51fb\u8005\u53ef\u501f\u52a9\u7279\u5236EAPOL-Key\u6570\u636e\u5305\u5229\u7528\u8be5\u6f0f\u6d1e\u5728\u7cfb\u7edf\u4e0a\u6267\u884c\u4efb\u610f\u4ee3\u7801\u3002",
  "formalWay": "\u76ee\u524d\u5382\u5546\u5df2\u53d1\u5e03\u5347\u7ea7\u8865\u4e01\u4ee5\u4fee\u590d\u6f0f\u6d1e\uff0c\u8be6\u60c5\u8bf7\u5173\u6ce8\u5382\u5546\u4e3b\u9875\uff1a\r\nhttp://www.realtek.com/",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2021-18235",
  "openTime": "2021-03-17",
  "patchDescription": "Realtek RTL8195AM\u7b49\u90fd\u662f\u4e2d\u56fd\u53f0\u6e7e\u745e\u6631\u534a\u5bfc\u4f53\uff08Realtek\uff09\u516c\u53f8\u7684\u4e00\u6b3e\u7269\u8054\u7f51\u5fae\u63a7\u5236\u5668\u3002\r\n\r\n\u591a\u6b3eRealtek\u4ea7\u54c1\u4e2d\u5b58\u5728\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\u3002\u8fdc\u7a0b\u653b\u51fb\u8005\u53ef\u501f\u52a9\u7279\u5236EAPOL-Key\u6570\u636e\u5305\u5229\u7528\u8be5\u6f0f\u6d1e\u5728\u7cfb\u7edf\u4e0a\u6267\u884c\u4efb\u610f\u4ee3\u7801\u3002\u76ee\u524d\uff0c\u4f9b\u5e94\u5546\u53d1\u5e03\u4e86\u5b89\u5168\u516c\u544a\u53ca\u76f8\u5173\u8865\u4e01\u4fe1\u606f\uff0c\u4fee\u590d\u4e86\u6b64\u6f0f\u6d1e\u3002",
  "patchName": "\u591a\u6b3eRealtek\u4ea7\u54c1\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\u7684\u8865\u4e01",
  "products": {
    "product": [
      "Realtek RTL8710AF \u003c2.0.6",
      "Realtek RTL8711AF \u003c2.0.6",
      "Realtek RTL8711AM \u003c2.0.6",
      "Realtek RTL8195AM \u003c2.0.6"
    ]
  },
  "referenceLink": "https://www.amebaiot.com/en/arduino-faq/",
  "serverity": "\u4e2d",
  "submitTime": "2020-07-07",
  "title": "\u591a\u6b3eRealtek\u4ea7\u54c1\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e"
}

CVE-2020-9395 (GCVE-0-2020-9395)

Vulnerability from cvelistv5 – Published: 2020-07-06 21:09 – Updated: 2024-08-04 10:26

Summary

An issue was discovered on Realtek RTL8195AM, RTL8711AM, RTL8711AF, and RTL8710AF devices before 2.0.6. A stack-based buffer overflow exists in the client code that takes care of WPA2's 4-way-handshake via a malformed EAPOL-Key packet with a long keydata buffer.

Severity

No CVSS data available.

CWE

Assigner

mitre mitre root

References

3 references

URL	Tags
https://github.com/ambiot/amb1_arduino/commit/dce…	x_refsource_MISC
https://github.com/ambiot/amb1_sdk/commit/bc5173d…	x_refsource_MISC
https://www.amebaiot.com/en/security_bulletin/	x_refsource_MISC

Date Public

2020-07-03 00:00

Show details on NVD website

JSON

To clipboard

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          "dateUpdated": "2024-08-04T10:26:16.113Z",
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            ],
            "url": "https://github.com/ambiot/amb1_arduino/commit/dcea55cf9775a0166805b3db845b237ecd5e74ea#diff-d06e7a87f34cc464a56799a419033014"
          },
          {
            "tags": [
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            ],
            "url": "https://github.com/ambiot/amb1_sdk/commit/bc5173d5d4faf6829074b0f1e1b242c12b7777a3#diff-700c216fb376666eaeda0c892e8bdc09"
          },
          {
            "tags": [
              "x_refsource_MISC",
              "x_transferred"
            ],
            "url": "https://www.amebaiot.com/en/security_bulletin/"
          }
        ],
        "title": "CVE Program Container"
      }
    ],
    "cna": {
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        }
      ],
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      "providerMetadata": {
        "dateUpdated": "2020-07-07T20:01:57.000Z",
        "orgId": "8254265b-2729-46b6-b9e3-3dfca2d5bfca",
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        {
          "tags": [
            "x_refsource_MISC"
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          "url": "https://www.amebaiot.com/en/security_bulletin/"
        }
      ],
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        "CVE_data_meta": {
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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.