Vulnerability-Lookup

CNVD-2022-06523

Vulnerability from cnvd - Published: 2022-01-25

Title

ffjpeg缓冲区溢出漏洞（CNVD-2022-06523）

Description

ffjpeg是一个简单的jpeg编码和解码实现。 ffjpeg 2020-06-22及更早版本中的jfif.c:701的jfif_encode存在全局缓冲区溢出漏洞。攻击者可通过特制jpeg文件利用该漏洞导致拒绝服务。

Severity

中

Patch Name

ffjpeg缓冲区溢出漏洞（CNVD-2022-06523）的补丁

Patch Description

ffjpeg是一个简单的jpeg编码和解码实现。 ffjpeg 2020-06-22及更早版本中的jfif.c:701的jfif_encode存在全局缓冲区溢出漏洞。攻击者可通过特制jpeg文件利用该漏洞导致拒绝服务。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/rockcarry/ffjpeg/commit/31649ad67e232aaa31ceb7aaa3c3451e5bbcb4cb

Reference

https://nvd.nist.gov/vuln/detail/CVE-2020-23705

Impacted products

Name
ffjpeg ffjpeg <=2020-06-22

Show details on source website

JSON

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{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2020-23705",
      "cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2020-23705"
    }
  },
  "description": "ffjpeg\u662f\u4e00\u4e2a\u7b80\u5355\u7684jpeg\u7f16\u7801\u548c\u89e3\u7801\u5b9e\u73b0\u3002\n\nffjpeg 2020-06-22\u53ca\u66f4\u65e9\u7248\u672c\u4e2d\u7684jfif.c:701\u7684jfif_encode\u5b58\u5728\u5168\u5c40\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\u3002\u653b\u51fb\u8005\u53ef\u901a\u8fc7\u7279\u5236jpeg\u6587\u4ef6\u5229\u7528\u8be5\u6f0f\u6d1e\u5bfc\u81f4\u62d2\u7edd\u670d\u52a1\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/rockcarry/ffjpeg/commit/31649ad67e232aaa31ceb7aaa3c3451e5bbcb4cb",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2022-06523",
  "openTime": "2022-01-25",
  "patchDescription": "ffjpeg\u662f\u4e00\u4e2a\u7b80\u5355\u7684jpeg\u7f16\u7801\u548c\u89e3\u7801\u5b9e\u73b0\u3002\r\n\r\nffjpeg 2020-06-22\u53ca\u66f4\u65e9\u7248\u672c\u4e2d\u7684jfif.c:701\u7684jfif_encode\u5b58\u5728\u5168\u5c40\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\u3002\u653b\u51fb\u8005\u53ef\u901a\u8fc7\u7279\u5236jpeg\u6587\u4ef6\u5229\u7528\u8be5\u6f0f\u6d1e\u5bfc\u81f4\u62d2\u7edd\u670d\u52a1\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": "ffjpeg\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\uff08CNVD-2022-06523\uff09\u7684\u8865\u4e01",
  "products": {
    "product": "ffjpeg ffjpeg \u003c=2020-06-22"
  },
  "referenceLink": "https://nvd.nist.gov/vuln/detail/CVE-2020-23705",
  "serverity": "\u4e2d",
  "submitTime": "2021-07-16",
  "title": "ffjpeg\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\uff08CNVD-2022-06523\uff09"
}

CVE-2020-23705 (GCVE-0-2020-23705)

Vulnerability from cvelistv5 – Published: 2021-07-15 21:55 – Updated: 2024-08-04 15:05

Summary

A global buffer overflow vulnerability in jfif_encode at jfif.c:701 of ffjpeg through 2020-06-22 allows attackers to cause a Denial of Service (DOS) via a crafted jpeg file.

Severity

No CVSS data available.

CWE

Assigner

mitre CNA under the mitre root

CNA scorecard E 27/100 over 2363 records in the last 180 days details

References

1 reference

URL	Tags
https://github.com/rockcarry/ffjpeg/issues/25	x_refsource_MISC

Show details on NVD website

JSON

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          "dateUpdated": "2024-08-04T15:05:10.363Z",
          "orgId": "af854a3a-2127-422b-91ae-364da2661108",
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        "references": [
          {
            "tags": [
              "x_refsource_MISC",
              "x_transferred"
            ],
            "url": "https://github.com/rockcarry/ffjpeg/issues/25"
          }
        ],
        "title": "CVE Program Container"
      }
    ],
    "cna": {
      "affected": [
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          "vendor": "n/a",
          "versions": [
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      ],
      "problemTypes": [
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              "description": "n/a",
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        "dateUpdated": "2021-07-15T21:55:05.000Z",
        "orgId": "8254265b-2729-46b6-b9e3-3dfca2d5bfca",
        "shortName": "mitre"
      },
      "references": [
        {
          "tags": [
            "x_refsource_MISC"
          ],
          "url": "https://github.com/rockcarry/ffjpeg/issues/25"
        }
      ],
      "x_legacyV4Record": {
        "CVE_data_meta": {
          "ASSIGNER": "cve@mitre.org",
          "ID": "CVE-2020-23705",
          "STATE": "PUBLIC"
        },
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            "vendor_data": [
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                      "version": {
                        "version_data": [
                          {
                            "version_value": "n/a"
                          }
                        ]
                      }
                    }
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                "vendor_name": "n/a"
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        "references": {
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            }
          ]
        }
      }
    }
  },
  "cveMetadata": {
    "assignerOrgId": "8254265b-2729-46b6-b9e3-3dfca2d5bfca",
    "assignerShortName": "mitre",
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    "state": "PUBLISHED"
  },
  "dataType": "CVE_RECORD",
  "dataVersion": "5.1"
}

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.

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.

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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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CNVD-2022-06523

CVE-2020-23705 (GCVE-0-2020-23705)

Tags

Sightings

Nomenclature

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