Vulnerability-Lookup

CNVD-2021-60557

Vulnerability from cnvd - Published: 2021-08-10

Title

Raonwiz K Upload代码问题漏洞

Description

Raonwiz K Upload是韩国Raonwiz公司的一款文件传输组件。 Raonwiz K Editor v2018.0.0.10存在安全漏洞，攻击者在服务或系统重新启动时执行DLL劫持攻击。

Severity

中

Formal description

目前厂商暂未发布修复措施解决此安全问题，建议使用此软件的用户随时关注厂商主页或参考网址以获取解决办法： https://gist.github.com/blackcon/ae155656d21a2228aa25fdcb79c85159

Reference

https://nvd.nist.gov/vuln/detail/CVE-2020-29157

Impacted products

Name
Raonwiz Raonwiz K Editor v2018.0.0.10

Show details on source website

JSON

To clipboard

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2020-29157"
    }
  },
  "description": "Raonwiz K Upload\u662f\u97e9\u56fdRaonwiz\u516c\u53f8\u7684\u4e00\u6b3e\u6587\u4ef6\u4f20\u8f93\u7ec4\u4ef6\u3002\n\nRaonwiz K Editor v2018.0.0.10\u5b58\u5728\u5b89\u5168\u6f0f\u6d1e\uff0c\u653b\u51fb\u8005\u5728\u670d\u52a1\u6216\u7cfb\u7edf\u91cd\u65b0\u542f\u52a8\u65f6\u6267\u884cDLL\u52ab\u6301\u653b\u51fb\u3002",
  "formalWay": "\u76ee\u524d\u5382\u5546\u6682\u672a\u53d1\u5e03\u4fee\u590d\u63aa\u65bd\u89e3\u51b3\u6b64\u5b89\u5168\u95ee\u9898\uff0c\u5efa\u8bae\u4f7f\u7528\u6b64\u8f6f\u4ef6\u7684\u7528\u6237\u968f\u65f6\u5173\u6ce8\u5382\u5546\u4e3b\u9875\u6216\u53c2\u8003\u7f51\u5740\u4ee5\u83b7\u53d6\u89e3\u51b3\u529e\u6cd5\uff1a\r\nhttps://gist.github.com/blackcon/ae155656d21a2228aa25fdcb79c85159",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2021-60557",
  "openTime": "2021-08-10",
  "products": {
    "product": "Raonwiz Raonwiz K Editor v2018.0.0.10"
  },
  "referenceLink": "https://nvd.nist.gov/vuln/detail/CVE-2020-29157",
  "serverity": "\u4e2d",
  "submitTime": "2021-07-15",
  "title": "Raonwiz K Upload\u4ee3\u7801\u95ee\u9898\u6f0f\u6d1e"
}

CVE-2020-29157 (GCVE-0-2020-29157)

Vulnerability from cvelistv5 – Published: 2021-07-14 19:59 – Updated: 2024-08-04 16:48

Summary

An issue in RAONWIZ K Editor v2018.0.0.10 allows attackers to perform a DLL hijacking attack when the service or system is restarted.

Severity

No CVSS data available.

CWE

Assigner

mitre mitre root

References

2 references

URL	Tags
https://gist.github.com/blackcon/ae155656d21a2228…	x_refsource_MISC
https://docs.microsoft.com/en-us/windows/win32/dl…	x_refsource_MISC

Show details on NVD website

JSON

To clipboard

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          "dateUpdated": "2024-08-04T16:48:01.632Z",
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            "url": "https://gist.github.com/blackcon/ae155656d21a2228aa25fdcb79c85159"
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        "title": "CVE Program Container"
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        },
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          "tags": [
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          ],
          "url": "https://docs.microsoft.com/en-us/windows/win32/dlls/dynamic-link-library-search-order"
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          "ID": "CVE-2020-29157",
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                "product": {
                  "product_data": [
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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.