Vulnerability-Lookup

CNVD-2017-33737

Vulnerability from cnvd - Published: 2017-11-13

Title

GNU Emacs信息泄露漏洞

Description

GNU Emacs是GNU计划开发的一个使用C语言编写的Unix文本编辑器，它支持语法高亮显示、多种语言和功能扩展等。 GNU Emacs 25.3.1版本中存在安全漏洞，该漏洞源于程序在创建swap文件时，未能使用掩码。攻击者可利用该漏洞读取或访问文件。

Severity

低

Formal description

厂商尚未提供漏洞修复方案，请关注厂商主页更新： https://www.gnu.org/software/emacs/

Reference

https://nvd.nist.gov/vuln/detail/CVE-2017-1000383

Impacted products

Name
Gnu emacs 25.3.1

Show details on source website

JSON

To clipboard

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2017-1000383"
    }
  },
  "description": "GNU Emacs\u662fGNU\u8ba1\u5212\u5f00\u53d1\u7684\u4e00\u4e2a\u4f7f\u7528C\u8bed\u8a00\u7f16\u5199\u7684Unix\u6587\u672c\u7f16\u8f91\u5668\uff0c\u5b83\u652f\u6301\u8bed\u6cd5\u9ad8\u4eae\u663e\u793a\u3001\u591a\u79cd\u8bed\u8a00\u548c\u529f\u80fd\u6269\u5c55\u7b49\u3002\r\n\r\nGNU Emacs 25.3.1\u7248\u672c\u4e2d\u5b58\u5728\u5b89\u5168\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8e\u7a0b\u5e8f\u5728\u521b\u5efaswap\u6587\u4ef6\u65f6\uff0c\u672a\u80fd\u4f7f\u7528\u63a9\u7801\u3002\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u8bfb\u53d6\u6216\u8bbf\u95ee\u6587\u4ef6\u3002",
  "discovererName": "Hanno B\u00c3\u00b6ck",
  "formalWay": "\u5382\u5546\u5c1a\u672a\u63d0\u4f9b\u6f0f\u6d1e\u4fee\u590d\u65b9\u6848\uff0c\u8bf7\u5173\u6ce8\u5382\u5546\u4e3b\u9875\u66f4\u65b0\uff1a\r\nhttps://www.gnu.org/software/emacs/",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2017-33737",
  "openTime": "2017-11-13",
  "products": {
    "product": "Gnu emacs 25.3.1"
  },
  "referenceLink": "https://nvd.nist.gov/vuln/detail/CVE-2017-1000383",
  "serverity": "\u4f4e",
  "submitTime": "2017-11-01",
  "title": "GNU Emacs\u4fe1\u606f\u6cc4\u9732\u6f0f\u6d1e"
}

CVE-2017-1000383 (GCVE-0-2017-1000383)

Vulnerability from cvelistv5 – Published: 2017-10-31 20:00 – Updated: 2024-08-05 22:00

Summary

GNU Emacs version 25.3.1 (and other versions most likely) ignores umask when creating a backup save file ("[ORIGINAL_FILENAME]~") resulting in files that may be world readable or otherwise accessible in ways not intended by the user running the emacs binary.

Severity

No CVSS data available.

CWE

Assigner

mitre CNA under the mitre root

CNA scorecard E 28/100 over 2286 records in the last 180 days details

References

2 references

URL	Tags
http://www.openwall.com/lists/oss-security/2017/10/31/1	mailing-listx_refsource_MLIST
http://www.securityfocus.com/bid/101671	vdb-entryx_refsource_BID

Date Public

2017-10-31 00:00

Show details on NVD website

JSON

To clipboard

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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.

Vulnerability timeline

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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.

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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