CNVD-2019-22230
Vulnerability from cnvd - Published: 2019-07-12
VLAI
Title
Trape SQL注入漏洞(CNVD-2019-22230)
Description
Trape是一套开源的互联网跟踪识别工具。该工具能够对会话进行远程识别,模拟钓鱼攻击。
Trape 2019-05-08及之前版本中存在SQL注入漏洞。该漏洞源于基于数据库的应用缺少对外部输入SQL语句的验证。攻击者可利用该漏洞执行非法SQL命令。
Severity
高
Formal description
厂商尚未提供漏洞修复方案,请关注厂商主页更新: https://github.com/jofpin/trape
Reference
https://nvd.nist.gov/vuln/detail/CVE-2019-13489
Impacted products
| Name | Trape Trape <=2019-05-08 |
|---|
{
"cves": {
"cve": {
"cveNumber": "CVE-2019-13489",
"cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2019-13489"
}
},
"description": "Trape\u662f\u4e00\u5957\u5f00\u6e90\u7684\u4e92\u8054\u7f51\u8ddf\u8e2a\u8bc6\u522b\u5de5\u5177\u3002\u8be5\u5de5\u5177\u80fd\u591f\u5bf9\u4f1a\u8bdd\u8fdb\u884c\u8fdc\u7a0b\u8bc6\u522b\uff0c\u6a21\u62df\u9493\u9c7c\u653b\u51fb\u3002\n\nTrape 2019-05-08\u53ca\u4e4b\u524d\u7248\u672c\u4e2d\u5b58\u5728SQL\u6ce8\u5165\u6f0f\u6d1e\u3002\u8be5\u6f0f\u6d1e\u6e90\u4e8e\u57fa\u4e8e\u6570\u636e\u5e93\u7684\u5e94\u7528\u7f3a\u5c11\u5bf9\u5916\u90e8\u8f93\u5165SQL\u8bed\u53e5\u7684\u9a8c\u8bc1\u3002\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u6267\u884c\u975e\u6cd5SQL\u547d\u4ee4\u3002",
"discovererName": "unKnow",
"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://github.com/jofpin/trape",
"isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
"number": "CNVD-2019-22230",
"openTime": "2019-07-12",
"products": {
"product": "Trape Trape \u003c=2019-05-08"
},
"referenceLink": "https://nvd.nist.gov/vuln/detail/CVE-2019-13489",
"serverity": "\u9ad8",
"submitTime": "2019-07-11",
"title": "Trape SQL\u6ce8\u5165\u6f0f\u6d1e\uff08CNVD-2019-22230\uff09"
}
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
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.
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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.
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.
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