CNVD-2021-17223

Vulnerability from cnvd - Published: 2021-03-13
VLAI
Title
Apple ImageIO资源管理错误漏洞(CNVD-2021-17223)
Description
Apple ImageIO是美国Apple公司的一个用于IOS移动设备中对图像数据进行解析和写入的必要组件。 Apple ImageIO 存在资源管理错误漏洞,该漏洞源于macOS的ImageIO组件中的curl实现中处理图像文件时,由于边界条件而存在此漏洞。远程攻击者可以创建特制文件,诱骗受害者打开文件,触发越界读取错误并使系统崩溃。
Severity
Patch Name
Apple ImageIO资源管理错误漏洞(CNVD-2021-17223)的补丁
Patch Description
Apple ImageIO是美国Apple公司的一个用于IOS移动设备中对图像数据进行解析和写入的必要组件。 Apple ImageIO 存在资源管理错误漏洞,该漏洞源于macOS的ImageIO组件中的curl实现中处理图像文件时,由于边界条件而存在此漏洞。远程攻击者可以创建特制文件,诱骗受害者打开文件,触发越界读取错误并使系统崩溃。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://support.apple.com/en-us/HT212146

Reference
https://support.apple.com/en-us/HT212146
Impacted products
Name
Apple Apple ImageIO
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2021-1783",
      "cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2021-1783"
    }
  },
  "description": "Apple ImageIO\u662f\u7f8e\u56fdApple\u516c\u53f8\u7684\u4e00\u4e2a\u7528\u4e8eIOS\u79fb\u52a8\u8bbe\u5907\u4e2d\u5bf9\u56fe\u50cf\u6570\u636e\u8fdb\u884c\u89e3\u6790\u548c\u5199\u5165\u7684\u5fc5\u8981\u7ec4\u4ef6\u3002\n\nApple ImageIO \u5b58\u5728\u8d44\u6e90\u7ba1\u7406\u9519\u8bef\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8emacOS\u7684ImageIO\u7ec4\u4ef6\u4e2d\u7684curl\u5b9e\u73b0\u4e2d\u5904\u7406\u56fe\u50cf\u6587\u4ef6\u65f6\uff0c\u7531\u4e8e\u8fb9\u754c\u6761\u4ef6\u800c\u5b58\u5728\u6b64\u6f0f\u6d1e\u3002\u8fdc\u7a0b\u653b\u51fb\u8005\u53ef\u4ee5\u521b\u5efa\u7279\u5236\u6587\u4ef6\uff0c\u8bf1\u9a97\u53d7\u5bb3\u8005\u6253\u5f00\u6587\u4ef6\uff0c\u89e6\u53d1\u8d8a\u754c\u8bfb\u53d6\u9519\u8bef\u5e76\u4f7f\u7cfb\u7edf\u5d29\u6e83\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://support.apple.com/en-us/HT212146",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2021-17223",
  "openTime": "2021-03-13",
  "patchDescription": "Apple ImageIO\u662f\u7f8e\u56fdApple\u516c\u53f8\u7684\u4e00\u4e2a\u7528\u4e8eIOS\u79fb\u52a8\u8bbe\u5907\u4e2d\u5bf9\u56fe\u50cf\u6570\u636e\u8fdb\u884c\u89e3\u6790\u548c\u5199\u5165\u7684\u5fc5\u8981\u7ec4\u4ef6\u3002\r\n\r\nApple ImageIO \u5b58\u5728\u8d44\u6e90\u7ba1\u7406\u9519\u8bef\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8emacOS\u7684ImageIO\u7ec4\u4ef6\u4e2d\u7684curl\u5b9e\u73b0\u4e2d\u5904\u7406\u56fe\u50cf\u6587\u4ef6\u65f6\uff0c\u7531\u4e8e\u8fb9\u754c\u6761\u4ef6\u800c\u5b58\u5728\u6b64\u6f0f\u6d1e\u3002\u8fdc\u7a0b\u653b\u51fb\u8005\u53ef\u4ee5\u521b\u5efa\u7279\u5236\u6587\u4ef6\uff0c\u8bf1\u9a97\u53d7\u5bb3\u8005\u6253\u5f00\u6587\u4ef6\uff0c\u89e6\u53d1\u8d8a\u754c\u8bfb\u53d6\u9519\u8bef\u5e76\u4f7f\u7cfb\u7edf\u5d29\u6e83\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": "Apple ImageIO\u8d44\u6e90\u7ba1\u7406\u9519\u8bef\u6f0f\u6d1e\uff08CNVD-2021-17223\uff09\u7684\u8865\u4e01",
  "products": {
    "product": "Apple  Apple ImageIO"
  },
  "referenceLink": "https://support.apple.com/en-us/HT212146",
  "serverity": "\u4e2d",
  "submitTime": "2021-03-02",
  "title": "Apple ImageIO\u8d44\u6e90\u7ba1\u7406\u9519\u8bef\u6f0f\u6d1e\uff08CNVD-2021-17223\uff09"
}



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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

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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.
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  • Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.

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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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