CNVD-2021-37707

Vulnerability from cnvd - Published: 2021-05-28
VLAI
Title
Spring Security安全特征问题漏洞
Description
Spring Security的前身是Acegi Security ,是Spring项目组中用来提供安全认证服务的框架。 Spring Security中存在安全特征问题漏洞。攻击者可借助字典攻击利用该漏洞获取未加密的值。
Severity
中
Patch Name
Spring Security安全特征问题漏洞的补丁
Patch Description
Spring Security的前身是Acegi Security ,是Spring项目组中用来提供安全认证服务的框架。 Spring Security中存在安全特征问题漏洞。攻击者可借助字典攻击利用该漏洞获取未加密的值。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,补丁获取链接: https://tanzu.vmware.com/security/cve-2020-5408

Reference
https://nvd.nist.gov/vuln/detail/CVE-2020-5408
Impacted products
Name
['Pivotal Software Spring Security 5.3*,<5.3.2', 'Pivotal Software Spring Security 5.2*,<5.2.4', 'Pivotal Software Spring Security 5.1.*,<5.1.10', 'Pivotal Software Spring Security 5.0.*,<5.0.16', 'Pivotal Software Spring Security 4.2.*,<4.2.16']
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2020-5408"
    }
  },
  "description": "Spring Security\u7684\u524d\u8eab\u662fAcegi Security \uff0c\u662fSpring\u9879\u76ee\u7ec4\u4e2d\u7528\u6765\u63d0\u4f9b\u5b89\u5168\u8ba4\u8bc1\u670d\u52a1\u7684\u6846\u67b6\u3002\n\nSpring Security\u4e2d\u5b58\u5728\u5b89\u5168\u7279\u5f81\u95ee\u9898\u6f0f\u6d1e\u3002\u653b\u51fb\u8005\u53ef\u501f\u52a9\u5b57\u5178\u653b\u51fb\u5229\u7528\u8be5\u6f0f\u6d1e\u83b7\u53d6\u672a\u52a0\u5bc6\u7684\u503c\u3002",
  "formalWay": "\u76ee\u524d\u5382\u5546\u5df2\u53d1\u5e03\u5347\u7ea7\u8865\u4e01\u4ee5\u4fee\u590d\u6f0f\u6d1e\uff0c\u8865\u4e01\u83b7\u53d6\u94fe\u63a5\uff1a\r\nhttps://tanzu.vmware.com/security/cve-2020-5408",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2021-37707",
  "openTime": "2021-05-28",
  "patchDescription": "Spring Security\u7684\u524d\u8eab\u662fAcegi Security \uff0c\u662fSpring\u9879\u76ee\u7ec4\u4e2d\u7528\u6765\u63d0\u4f9b\u5b89\u5168\u8ba4\u8bc1\u670d\u52a1\u7684\u6846\u67b6\u3002\r\n\r\nSpring Security\u4e2d\u5b58\u5728\u5b89\u5168\u7279\u5f81\u95ee\u9898\u6f0f\u6d1e\u3002\u653b\u51fb\u8005\u53ef\u501f\u52a9\u5b57\u5178\u653b\u51fb\u5229\u7528\u8be5\u6f0f\u6d1e\u83b7\u53d6\u672a\u52a0\u5bc6\u7684\u503c\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": "Spring Security\u5b89\u5168\u7279\u5f81\u95ee\u9898\u6f0f\u6d1e\u7684\u8865\u4e01",
  "products": {
    "product": [
      "Pivotal Software Spring Security 5.3*\uff0c\u003c5.3.2",
      "Pivotal Software Spring Security 5.2*\uff0c\u003c5.2.4",
      "Pivotal Software Spring Security 5.1.*\uff0c\u003c5.1.10",
      "Pivotal Software Spring Security 5.0.*\uff0c\u003c5.0.16",
      "Pivotal Software Spring Security 4.2.*\uff0c\u003c4.2.16"
    ]
  },
  "referenceLink": "https://nvd.nist.gov/vuln/detail/CVE-2020-5408",
  "serverity": "\u4e2d",
  "submitTime": "2020-05-15",
  "title": "Spring Security\u5b89\u5168\u7279\u5f81\u95ee\u9898\u6f0f\u6d1e"
}



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Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.

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.

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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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