我有你的包裹:使用包裹跟踪号码枚举攻击收集客户的送货订单信息

Simon S. Woo, Hanbin Jang, Woojung Ji, Hyoungshick Kim
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引用次数: 2

摘要

包裹跟踪号(PTN)被广泛用于监控和跟踪货物。然而,从安全和隐私的角度来看,快递单号可能会泄露某些个人信息,从而导致安全和隐私泄露。在这项工作中,我们研究了与全球三大最受欢迎的包裹递送服务提供商(联邦快递、DHL和UPS)使用的在线包裹跟踪系统相关的隐私问题,发现这些网站无意中泄露了用户的个人数据。此外,我们发现ptn是高度结构化和可预测的。因此,通过PTN枚举攻击可以大量收集客户的个人数据。我们分析了从Fedex、DHL和UPS获得的100多万个包裹跟踪记录,结果表明,在5次尝试中,攻击者可以有效地猜测Fedex和DHL超过90%的ptn,以及接近50%的UPS ptn。此外,我们还提出了两种实际的攻击场景:1)推断业务交易信息和2)唯一标识收件人。此外,我们发现,通过将PTN信息与在线人物搜索服务Whitepages联系起来,不到10次比较就可以唯一识别超过109个收件人。
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I’ve Got Your Packages: Harvesting Customers’ Delivery Order Information using Package Tracking Number Enumeration Attacks
A package tracking number (PTN) is widely used to monitor and track a shipment. Through the lenses of security and privacy, however, a package tracking number can possibly reveal certain personal information, leading to security and privacy breaches. In this work, we examine the privacy issues associated with online package tracking systems used in the top three most popular package delivery service providers (FedEx, DHL, and UPS) in the world and found that those websites inadvertently leak users’ personal data with a PTN. Moreover, we discovered that PTNs are highly structured and predictable. Therefore, customers’ personal data can be massively collected via PTN enumeration attacks. We analyzed more than one million package tracking records obtained from Fedex, DHL, and UPS, and showed that within 5 attempts, an attacker can efficiently guess more than 90% of PTNs for FedEx and DHL, and close to 50% of PTNs for UPS. In addition, we present two practical attack scenarios: 1) to infer business transactions information and 2) to uniquely identify recipients. Also, we found that more than 109 recipients can be uniquely identified with less than 10 comparisons by linking the PTN information with the online people search service, Whitepages.
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