蛮力攻击T-Mobile导致sim卡劫持和身份盗窃的研究

Christopher Faircloth, Gavin Hartzell, Nathan Callahan, S. Bhunia
{"title":"蛮力攻击T-Mobile导致sim卡劫持和身份盗窃的研究","authors":"Christopher Faircloth, Gavin Hartzell, Nathan Callahan, S. Bhunia","doi":"10.1109/aiiot54504.2022.9817175","DOIUrl":null,"url":null,"abstract":"The 2021 T-Mobile breach conducted by John Erin Binns resulted in the theft of 54 million customers' personal data. The attacker gained entry into T-Mobile's systems through an unprotected router and used brute force techniques to access the sensitive information stored on the internal servers. The data stolen included names, addresses, Social Security Numbers, birthdays, driver's license numbers, ID information, IMEIs, and IMSIs. We analyze the data breach and how it opens the door to identity theft and many other forms of hacking such as SIM Hijacking. SIM Hijacking is a form of hacking in which bad actors can take control of a victim's phone number allowing them means to bypass additional safety measures currently in place to prevent fraud. This paper thoroughly reviews the attack methodology, impact, and attempts to provide an understanding of important measures and possible defense solutions against future attacks. We also detail other social engineering attacks that can be incurred from releasing the leaked data.","PeriodicalId":409264,"journal":{"name":"2022 IEEE World AI IoT Congress (AIIoT)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A Study on Brute Force Attack on T-Mobile Leading to SIM-Hijacking and Identity-Theft\",\"authors\":\"Christopher Faircloth, Gavin Hartzell, Nathan Callahan, S. Bhunia\",\"doi\":\"10.1109/aiiot54504.2022.9817175\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The 2021 T-Mobile breach conducted by John Erin Binns resulted in the theft of 54 million customers' personal data. The attacker gained entry into T-Mobile's systems through an unprotected router and used brute force techniques to access the sensitive information stored on the internal servers. The data stolen included names, addresses, Social Security Numbers, birthdays, driver's license numbers, ID information, IMEIs, and IMSIs. We analyze the data breach and how it opens the door to identity theft and many other forms of hacking such as SIM Hijacking. SIM Hijacking is a form of hacking in which bad actors can take control of a victim's phone number allowing them means to bypass additional safety measures currently in place to prevent fraud. This paper thoroughly reviews the attack methodology, impact, and attempts to provide an understanding of important measures and possible defense solutions against future attacks. We also detail other social engineering attacks that can be incurred from releasing the leaked data.\",\"PeriodicalId\":409264,\"journal\":{\"name\":\"2022 IEEE World AI IoT Congress (AIIoT)\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE World AI IoT Congress (AIIoT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/aiiot54504.2022.9817175\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE World AI IoT Congress (AIIoT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/aiiot54504.2022.9817175","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

摘要

2021年,约翰·艾琳·宾斯(John Erin Binns)对T-Mobile进行了入侵,导致5400万客户的个人数据被盗。攻击者通过未受保护的路由器进入T-Mobile的系统,并使用暴力破解技术访问存储在内部服务器上的敏感信息。被盗的数据包括姓名、地址、社会安全号码、生日、驾照号码、身份证信息、imei和imsi。我们分析了数据泄露,以及它如何为身份盗窃和许多其他形式的黑客行为(如SIM卡劫持)打开大门。SIM卡劫持是一种黑客行为,坏人可以控制受害者的电话号码,从而绕过目前为防止欺诈而采取的额外安全措施。本文全面回顾了攻击方法、影响,并试图提供对未来攻击的重要措施和可能的防御解决方案的理解。我们还详细介绍了释放泄露数据可能引发的其他社会工程攻击。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Study on Brute Force Attack on T-Mobile Leading to SIM-Hijacking and Identity-Theft
The 2021 T-Mobile breach conducted by John Erin Binns resulted in the theft of 54 million customers' personal data. The attacker gained entry into T-Mobile's systems through an unprotected router and used brute force techniques to access the sensitive information stored on the internal servers. The data stolen included names, addresses, Social Security Numbers, birthdays, driver's license numbers, ID information, IMEIs, and IMSIs. We analyze the data breach and how it opens the door to identity theft and many other forms of hacking such as SIM Hijacking. SIM Hijacking is a form of hacking in which bad actors can take control of a victim's phone number allowing them means to bypass additional safety measures currently in place to prevent fraud. This paper thoroughly reviews the attack methodology, impact, and attempts to provide an understanding of important measures and possible defense solutions against future attacks. We also detail other social engineering attacks that can be incurred from releasing the leaked data.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信