Vulnerability-Lookup

CNVD-2022-31935

Vulnerability from cnvd - Published: 2022-04-24

Title

YottaDB存在未明漏洞（CNVD-2022-31935）

Description

YottaDB是美国YottaDB公司的一个实时数据库。 YottaDB r1.32 和 V7.0-000 之前版本存在安全漏洞，攻击者可利用该漏洞以计算对 sr_port/op_fnj3.c 中 op_fnj3中memset的调用大小，从而产生一个非常大的值，从而导致分段错误并使应用程序崩溃。

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://gitlab.com/YottaDB/DB/YDB/-/issues/828

Reference

https://nvd.nist.gov/vuln/detail/CVE-2021-44490

Impacted products

Name
YottaDB YottaDB <=1.32

Show details on source website

JSON

To clipboard

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2021-44490"
    }
  },
  "description": "YottaDB\u662f\u7f8e\u56fdYottaDB\u516c\u53f8\u7684\u4e00\u4e2a\u5b9e\u65f6\u6570\u636e\u5e93\u3002\n\nYottaDB r1.32 \u548c V7.0-000 \u4e4b\u524d\u7248\u672c\u5b58\u5728\u5b89\u5168\u6f0f\u6d1e\uff0c\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u4ee5\u8ba1\u7b97\u5bf9 sr_port/op_fnj3.c \u4e2d op_fnj3\u4e2dmemset\u7684\u8c03\u7528\u5927\u5c0f\uff0c\u4ece\u800c\u4ea7\u751f\u4e00\u4e2a\u975e\u5e38\u5927\u7684\u503c\uff0c\u4ece\u800c\u5bfc\u81f4\u5206\u6bb5\u9519\u8bef\u5e76\u4f7f\u5e94\u7528\u7a0b\u5e8f\u5d29\u6e83\u3002",
  "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\n\r\nhttps://gitlab.com/YottaDB/DB/YDB/-/issues/828",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2022-31935",
  "openTime": "2022-04-24",
  "products": {
    "product": "YottaDB YottaDB \u003c=1.32"
  },
  "referenceLink": "https://nvd.nist.gov/vuln/detail/CVE-2021-44490",
  "serverity": "\u4e2d",
  "submitTime": "2022-04-16",
  "title": "YottaDB\u5b58\u5728\u672a\u660e\u6f0f\u6d1e\uff08CNVD-2022-31935\uff09"
}

CVE-2021-44490 (GCVE-0-2021-44490)

Vulnerability from cvelistv5 – Published: 2022-04-15 17:24 – Updated: 2024-08-04 04:25

Summary

An issue was discovered in YottaDB through r1.32 and V7.0-000. Using crafted input, attackers can cause a calculation of the size of calls to memset in op_fnj3 in sr_port/op_fnj3.c to result in an extremely large value in order to cause a segmentation fault and crash the application. This is a "- (digs < 1 ? 1 : digs)" subtraction.

Severity

No CVSS data available.

CWE

Assigner

mitre mitre root

References

1 reference

URL	Tags
https://gitlab.com/YottaDB/DB/YDB/-/issues/828	x_refsource_MISC

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.