CNVD-2020-58037

Vulnerability from cnvd - Published: 2020-10-22
VLAI
Title
Crossbeam缓冲区溢出漏洞
Description
Crossbeam是个人开发者的一个应用于并发编程的工具。 Crossbeam crossbeam-channel 0.4.4之前版本存在缓冲区溢出漏洞,该漏洞源于Vec::from iter分配内存与迭代器数量不一致。攻击者可利用该漏洞导致缓冲区溢出或堆溢出等。
Severity
高
Patch Name
Crossbeam缓冲区溢出漏洞的补丁
Patch Description
Crossbeam是个人开发者的一个应用于并发编程的工具。 Crossbeam crossbeam-channel 0.4.4之前版本存在缓冲区溢出漏洞,该漏洞源于Vec::from iter分配内存与迭代器数量不一致。攻击者可利用该漏洞导致缓冲区溢出或堆溢出等。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

厂商已发布了漏洞修复程序,请及时关注更新: https://github.com/crossbeam-rs/crossbeam/security/advisories/GHSA-v5m7-53cv-f3hx

Reference
https://github.com/crossbeam-rs/crossbeam/issues/539
Impacted products
Name
Crossbeam Crossbeam <0.4.4
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2020-15254",
      "cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2020-15254"
    }
  },
  "description": "Crossbeam\u662f\u4e2a\u4eba\u5f00\u53d1\u8005\u7684\u4e00\u4e2a\u5e94\u7528\u4e8e\u5e76\u53d1\u7f16\u7a0b\u7684\u5de5\u5177\u3002\n\nCrossbeam crossbeam-channel 0.4.4\u4e4b\u524d\u7248\u672c\u5b58\u5728\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8eVec\uff1a\uff1afrom iter\u5206\u914d\u5185\u5b58\u4e0e\u8fed\u4ee3\u5668\u6570\u91cf\u4e0d\u4e00\u81f4\u3002\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u5bfc\u81f4\u7f13\u51b2\u533a\u6ea2\u51fa\u6216\u5806\u6ea2\u51fa\u7b49\u3002",
  "formalWay": "\u5382\u5546\u5df2\u53d1\u5e03\u4e86\u6f0f\u6d1e\u4fee\u590d\u7a0b\u5e8f\uff0c\u8bf7\u53ca\u65f6\u5173\u6ce8\u66f4\u65b0\uff1a\r\nhttps://github.com/crossbeam-rs/crossbeam/security/advisories/GHSA-v5m7-53cv-f3hx",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2020-58037",
  "openTime": "2020-10-22",
  "patchDescription": "Crossbeam\u662f\u4e2a\u4eba\u5f00\u53d1\u8005\u7684\u4e00\u4e2a\u5e94\u7528\u4e8e\u5e76\u53d1\u7f16\u7a0b\u7684\u5de5\u5177\u3002\r\n\r\nCrossbeam crossbeam-channel 0.4.4\u4e4b\u524d\u7248\u672c\u5b58\u5728\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8eVec\uff1a\uff1afrom iter\u5206\u914d\u5185\u5b58\u4e0e\u8fed\u4ee3\u5668\u6570\u91cf\u4e0d\u4e00\u81f4\u3002\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u5bfc\u81f4\u7f13\u51b2\u533a\u6ea2\u51fa\u6216\u5806\u6ea2\u51fa\u7b49\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": "Crossbeam\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\u7684\u8865\u4e01",
  "products": {
    "product": "Crossbeam Crossbeam \u003c0.4.4"
  },
  "referenceLink": "https://github.com/crossbeam-rs/crossbeam/issues/539",
  "serverity": "\u9ad8",
  "submitTime": "2020-10-19",
  "title": "Crossbeam\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e"
}



Log in or create an account to share your comment.




Tags
Taxonomy of the tags.


Loading…

Loading…

Loading…

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.

Loading…

Loading…

Loading…

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.


Loading…