Vulnerability-Lookup

CNVD-2019-05784

Vulnerability from cnvd - Published: 2019-02-28

Title

GNU Binutils缓冲区溢出漏洞（CNVD-2019-05784）

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。 GNU Binutils 2.32版本中的readelf.c文件的‘process_mips_specific’函数存在缓冲区溢出漏洞。攻击者可利用该漏洞执行代码或造成拒绝服务。

Severity

中

Patch Name

GNU Binutils缓冲区溢出漏洞（CNVD-2019-05784）的补丁

Patch Description

Formal description

厂商已发布漏洞修复程序，请及时关注更新： https://sourceware.org/git/gitweb.cgi?p=binutils-gdb.git;h=7fc0c668f2aceb8582d74db1ad2528e2bba8a921

Reference

https://nvd.nist.gov/vuln/detail/CVE-2019-9077

Impacted products

Name
GNU Binutils 2.32

Show details on source website

JSON

To clipboard

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    "bid": {
      "bidNumber": "107139"
    }
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      "cveNumber": "CVE-2019-9077"
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  "discovererName": "spinpx",
  "formalWay": "\u5382\u5546\u5df2\u53d1\u5e03\u6f0f\u6d1e\u4fee\u590d\u7a0b\u5e8f\uff0c\u8bf7\u53ca\u65f6\u5173\u6ce8\u66f4\u65b0\uff1a\r\nhttps://sourceware.org/git/gitweb.cgi?p=binutils-gdb.git;h=7fc0c668f2aceb8582d74db1ad2528e2bba8a921",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2019-05784",
  "openTime": "2019-02-28",
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  "patchName": "GNU Binutils\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\uff08CNVD-2019-05784\uff09\u7684\u8865\u4e01",
  "products": {
    "product": "GNU Binutils 2.32"
  },
  "referenceLink": "https://nvd.nist.gov/vuln/detail/CVE-2019-9077",
  "serverity": "\u4e2d",
  "submitTime": "2019-02-25",
  "title": "GNU Binutils\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\uff08CNVD-2019-05784\uff09"
}

CVE-2019-9077 (GCVE-0-2019-9077)

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

Summary

An issue was discovered in GNU Binutils 2.32. It is a heap-based buffer overflow in process_mips_specific in readelf.c via a malformed MIPS option section.

Severity

No CVSS data available.

CWE

Assigner

mitre mitre root

References

8 references

URL	Tags
https://sourceware.org/bugzilla/show_bug.cgi?id=24243	x_refsource_MISC
http://www.securityfocus.com/bid/107139	vdb-entryx_refsource_BID
https://security.netapp.com/advisory/ntap-2019031…	x_refsource_CONFIRM
https://support.f5.com/csp/article/K00056379	x_refsource_CONFIRM
https://usn.ubuntu.com/4336-1/	vendor-advisoryx_refsource_UBUNTU
http://lists.opensuse.org/opensuse-security-annou…	vendor-advisoryx_refsource_SUSE
http://lists.opensuse.org/opensuse-security-annou…	vendor-advisoryx_refsource_SUSE
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.