Vulnerability-Lookup

CNVD-2019-22417

Vulnerability from cnvd - Published: 2019-07-12

Title

GNU Binutils libiberty堆缓冲区溢出漏洞（CNVD-2019-22417）

Description

GNU Binutils（GNU Binary Utilities或binutils）是GNU计划的开发的一组编程语言工具程序。该程序主要用于处理多种格式的目标文件，并提供有连接器、汇编器和其他用于目标文件和档案的工具。libiberty是其中的一个GNU程序使用的子程序的集合。 GNU Binutils 2.32版本中的libiberty的cp-demangle.c文件的‘d_count_templates_scopes’函数存在堆栈缓冲区溢出漏洞。攻击者可利用该漏洞造成拒绝服务。

Severity

中

Formal description

目前厂商暂未发布修复措施解决此安全问题，建议使用此软件的用户随时关注厂商主页或参考网址以获取解决办法： https://www.gnu.org/

Reference

https://nvd.nist.gov/vuln/detail/CVE-2019-9071

Impacted products

Name
GNU Binutils 2.32

Show details on source website

JSON

To clipboard

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    "cve": {
      "cveNumber": "CVE-2019-9071",
      "cveUrl": "http://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2019-9071"
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  "discovererName": "unknown",
  "formalWay": "\u76ee\u524d\u5382\u5546\u6682\u672a\u53d1\u5e03\u4fee\u590d\u63aa\u65bd\u89e3\u51b3\u6b64\u5b89\u5168\u95ee\u9898\uff0c\u5efa\u8bae\u4f7f\u7528\u6b64\u8f6f\u4ef6\u7684\u7528\u6237\u968f\u65f6\u5173\u6ce8\u5382\u5546\u4e3b\u9875\u6216\u53c2\u8003\u7f51\u5740\u4ee5\u83b7\u53d6\u89e3\u51b3\u529e\u6cd5\uff1a\r\nhttps://www.gnu.org/",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2019-22417",
  "openTime": "2019-07-12",
  "products": {
    "product": "GNU Binutils 2.32"
  },
  "referenceLink": "https://nvd.nist.gov/vuln/detail/CVE-2019-9071",
  "serverity": "\u4e2d",
  "submitTime": "2019-02-26",
  "title": "GNU Binutils libiberty\u5806\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\uff08CNVD-2019-22417\uff09"
}

CVE-2019-9071 (GCVE-0-2019-9071)

Vulnerability from cvelistv5 – Published: 2019-02-24 00:00 – Updated: 2024-08-04 21:38

Summary

An issue was discovered in GNU libiberty, as distributed in GNU Binutils 2.32. It is a stack consumption issue in d_count_templates_scopes in cp-demangle.c after many recursive calls.

Severity

No CVSS data available.

CWE

Assigner

mitre mitre root

References

8 references

URL	Tags
https://sourceware.org/bugzilla/show_bug.cgi?id=24227	x_refsource_MISC
https://gcc.gnu.org/bugzilla/show_bug.cgi?id=89394	x_refsource_MISC
https://security.netapp.com/advisory/ntap-2019031…	x_refsource_CONFIRM
http://www.securityfocus.com/bid/107147	vdb-entryx_refsource_BID
https://support.f5.com/csp/article/K02884135	x_refsource_CONFIRM
https://usn.ubuntu.com/4326-1/	vendor-advisoryx_refsource_UBUNTU
https://usn.ubuntu.com/4336-1/	vendor-advisoryx_refsource_UBUNTU
https://security.gentoo.org/glsa/202107-24	vendor-advisoryx_refsource_GENTOO

Date Public

2019-02-23 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.

Detection rules are retrieved from Rulezet.

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.