Vulnerability-Lookup

CNVD-2021-40324

Vulnerability from cnvd - Published: 2021-06-08

Title

D-Link DAP-2020命令注入漏洞

Description

D-Link DAP-2020是中国台湾友讯（D-Link）公司的一款WiFi范围扩展器。TCP（Transmission Control Protocol,传输控制协议）是一种面向连接的、可靠的、基于字节流的传输层通信协议，由IETF的RFC 793定义。 D-Link DAP-2020 v1.01rc001版本在处理CGI脚本时存在命令注入漏洞。该漏洞源于程序在将用户输入复制到固定长度的堆栈缓冲区之前未对其长度进行正确验证。攻击者可利用该漏洞在root上下文中执行任意代码。

Severity

高

Patch Name

D-Link DAP-2020命令注入漏洞的补丁

Patch Description

Formal description

目前厂商已发布升级补丁以修复漏洞，补丁获取链接： https://supportannouncement.us.dlink.com/announcement/publication.aspx?name=SAP10201

Reference

https://nvd.nist.gov/vuln/detail/CVE-2021-27248

Impacted products

Name
D-Link DAP-2020 v1.01rc001

Show details on source website

JSON

To clipboard

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2021-27248",
      "cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2021-27248"
    }
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  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2021-40324",
  "openTime": "2021-06-08",
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  "patchName": "D-Link DAP-2020\u547d\u4ee4\u6ce8\u5165\u6f0f\u6d1e\u7684\u8865\u4e01",
  "products": {
    "product": "D-Link DAP-2020 v1.01rc001"
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  "referenceLink": "https://nvd.nist.gov/vuln/detail/CVE-2021-27248",
  "serverity": "\u9ad8",
  "submitTime": "2021-04-29",
  "title": "D-Link DAP-2020\u547d\u4ee4\u6ce8\u5165\u6f0f\u6d1e"
}

CVE-2021-27248 (GCVE-0-2021-27248)

Vulnerability from cvelistv5 – Published: 2021-04-14 15:45 – Updated: 2024-08-03 20:48

Summary

This vulnerability allows network-adjacent attackers to execute arbitrary code on affected installations of D-Link DAP-2020 v1.01rc001 Wi-Fi access points. Authentication is not required to exploit this vulnerability. The specific flaw exists within the processing of CGI scripts. When parsing the getpage parameter, the process does not properly validate the length of user-supplied data prior to copying it to a fixed-length stack-based buffer. An attacker can leverage this vulnerability to execute code in the context of root. Was ZDI-CAN-10932.

Severity

8.8 (High)


                        
                          CVSS:3.0/AV:A/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H

CWE

CWE-121 - Stack-based Buffer Overflow

Assigner

zdi mitre root

References

2 references

URL	Tags
https://www.zerodayinitiative.com/advisories/ZDI-…	x_refsource_MISC
https://supportannouncement.us.dlink.com/announce…	x_refsource_MISC

Impacted products

1 product

Vendor	Product	Version
D-Link	DAP-2020	Affected: v1.01rc001

Credits

chung96vn ft phieulang & Chi Tran

Show details on NVD website

JSON

To clipboard

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    "cna": {
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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.