CNVD-2022-23485

Vulnerability from cnvd - Published: 2022-03-29
VLAI
Title
Pytorch-Lightning代码注入漏洞
Description
Pytorch-Lightning是一个开源轻量级 PyTorch 包装器。用于高性能 Ai 研究。 Pytorch-Lightning存在代码注入漏洞,攻击者可利用该漏洞向GitHub存储库中注入代码。
Severity
Patch Name
Pytorch-Lightning代码注入漏洞的补丁
Patch Description
Pytorch-Lightning是一个开源轻量级 PyTorch 包装器。用于高性能 Ai 研究。 Pytorch-Lightning存在代码注入漏洞,攻击者可利用该漏洞向GitHub存储库中注入代码。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

厂商已发布了漏洞修复程序,请及时关注更新: https://github.com/pytorchlightning/pytorch-lightning/commit/8b7a12c52e52a06408e9231647839ddb4665e8ae

Reference
https://huntr.dev/bounties/a795bf93-c91e-4c79-aae8-f7d8bda92e2a
Impacted products
Name
Pytorch-Lightning Pytorch-Lightning <1.6.0
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2022-0845"
    }
  },
  "description": "Pytorch-Lightning\u662f\u4e00\u4e2a\u5f00\u6e90\u8f7b\u91cf\u7ea7 PyTorch \u5305\u88c5\u5668\u3002\u7528\u4e8e\u9ad8\u6027\u80fd Ai \u7814\u7a76\u3002\n\nPytorch-Lightning\u5b58\u5728\u4ee3\u7801\u6ce8\u5165\u6f0f\u6d1e\uff0c\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u5411GitHub\u5b58\u50a8\u5e93\u4e2d\u6ce8\u5165\u4ee3\u7801\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/pytorchlightning/pytorch-lightning/commit/8b7a12c52e52a06408e9231647839ddb4665e8ae",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2022-23485",
  "openTime": "2022-03-29",
  "patchDescription": "Pytorch-Lightning\u662f\u4e00\u4e2a\u5f00\u6e90\u8f7b\u91cf\u7ea7 PyTorch \u5305\u88c5\u5668\u3002\u7528\u4e8e\u9ad8\u6027\u80fd Ai \u7814\u7a76\u3002\r\n\r\nPytorch-Lightning\u5b58\u5728\u4ee3\u7801\u6ce8\u5165\u6f0f\u6d1e\uff0c\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u5411GitHub\u5b58\u50a8\u5e93\u4e2d\u6ce8\u5165\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": "Pytorch-Lightning\u4ee3\u7801\u6ce8\u5165\u6f0f\u6d1e\u7684\u8865\u4e01",
  "products": {
    "product": "Pytorch-Lightning Pytorch-Lightning \u003c1.6.0"
  },
  "referenceLink": "https://huntr.dev/bounties/a795bf93-c91e-4c79-aae8-f7d8bda92e2a",
  "serverity": "\u9ad8",
  "submitTime": "2022-03-08",
  "title": "Pytorch-Lightning\u4ee3\u7801\u6ce8\u5165\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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Detection rules are retrieved from Rulezet.

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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.


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