
在充满网络风险的世界里,账户接管已成为最隐蔽的威胁之一。如果攻击者成功入侵合法电子邮件账户,便能在不触发任何警报的情况下,冒充受信任的个人或组织。传统电子邮件安全系统将无法察觉异常。随后,威胁行为者可伺机而动,实施从窃取资金、窃取敏感数据到传播灾难性恶意软件等各类攻击。严重的财务损失和企业声誉受损是常见后果。
In a world full of cyber risk, account takeover has emerged as one of the most insidious of all threats. If an attacker can successfully compromise a legitimate email account, they are then able to pose as a trusted individual or organization without triggering any warnings. Traditional email security will see nothing wrong. From there the threat actor can pick their moment to cause havoc with objectives that range from stealing money, expropriating sensitive data and propagating catastrophic malware. Serious financial loss and a damaged corporate reputation are commonplace outcomes.
典型的账户接管生命周期始于攻击者获取凭证,通常通过网络钓鱼手段。生成式人工智能(GenAI)让攻击者能轻松诱骗疏忽大意的人员泄露数据,例如冒充同事或其他受信任方,或诱导其在伪造页面输入机密信息。人们可能预期,一旦合法身份被成功入侵,攻击会立即全面爆发。但如今,典型的账户接管者更加隐蔽和阴险,并不急于在早期阶段采取行动,因为此时并未触发警报。大多数攻击者会花时间测试和验证窃取的数据,探寻其潜在用途。
The typical account takeover lifecycle starts with the bad guys obtaining credentials, usually through the medium of phishing. Generative AI (GenAI) has made it easy for an attacker to trick an unwary individual into giving away data, perhaps by posing as a colleague or other trusted party or by encouraging them to enter confidential information on a fake page. You might expect, once a legitimate identity has been successfully compromised, that all hell would immediately break loose. These days the typical account takeover artist is more stealthy and sinister than that, in no rush to act at this early stage since no alarm bells have been triggered. Most will take their time to test out and verify their stolen data, and see where it might take them.
软件开发商 Kaseya 网络安全高级副总裁 Dave Baggett 表示:“传统上,攻击者接管账户后会立即大量发送垃圾邮件和钓鱼邮件。现在他们开始变得狡猾。他们会获取账户访问权限后按兵不动,监视所有经过的电子邮件流量,等待合适时机插入对话。”由内而外一旦摸清组织的弱点并制定攻击计划,攻击者便会开始将被入侵的电子邮件账户武器化,以此为跳板攻击其他员工和内部系统。
“Conventionally attackers would take over an account and immediately start firing off spam and phishing,” says Dave Baggett, SVP Cybersecurity with software developer Kaseya. “Now they are starting to get clever. They’ll get access to an account and sit tight, watching all the email traffic passing and waiting for an opportune moment to inject themselves into the conversation.”From the inside out Once they’ve figured out an organisation’s weak points and come up with a plan of attack, the bad guys will start to weaponize the compromised email account to target other employees and internal systems.
假设他们的动机是经济利益,他们可能正在寻找进入薪资或发票数据库的途径。但他们的最终目标可能更远大,指向该组织的客户和供应商,而这才是真正噩梦的开始。所谓的“出站钓鱼”让犯罪分子得以控制一系列全新的敏感终端。面对看似来自可信合作伙伴和盟友的信息,出站钓鱼的受害者极其脆弱。组织用多因素认证(MFA)等强有力的控制措施保护自己的电子邮件账户是一回事,但没有人能控制其他方的认证做法:“假设我们有一个受保护的客户,”Baggett 解释道。
Assuming their motivation is financial, they might be on the hunt for a way into payroll or invoicing databases. But their ultimate aim might lie further afield in the form of the organisation’s customers and suppliers, and that’s when the real nightmare can start. So called outbound phishing offers the criminal a way to assert control over a whole new range of sensitive end points. Victims of outbound phishing are highly vulnerable in the face of what seem to be messages from a trusted partner and ally. It is one thing for an organisation to protect its own email accounts with robust controls like multifactor authentication (MFA), but no one has control over the authentication practices of other parties: “Let’s say we have a customer who we’re protecting,” explains Baggett.
“他们很安全,但想象一下,他们开始收到来自第三方的可疑邮件。我们的客户完全不知道那个第三方有什么保护措施,或者没有什么保护措施。来自该来源的邮件可能看起来像是来自真实账户,但可能是黑客在敲击键盘发送的。”鉴于你无法对第三方组织进行检查,因此需要比常规电子邮件安全更复杂的解决方案。理想情况下,这应该是一个由生成式 AI 驱动的解决方案,能够引入语言理解能力,深入检查对话历史,以发现是否存在异常。
“They’re safe, but imagine that they start getting suspicious emails from a third party. Our customer has no idea what is or isn’t protecting that third party. Emails coming from that source might appear to be from a real account, but it could be a hacker typing them.”Given that you can’t run checks on third party organisations, something more sophisticated than regular email security is required. Ideally this would be a GenAI-powered solution that can bring language understanding to bear, able to examine conversation histories in depth to see if something anomalous can be spotted.
当坏人成功冒充高层人士的身份时,防守方的工作会变得更加困难。如果他们冒充一位拥有广泛且可信声誉的高层管理人员,手中就握有了一项强大的资产。那位高层人士所有的信任和善意现在都被犯罪分子继承了。传统的电子邮件过滤系统通常会配置为让高层人员以最小的阻力通过某些防御层,以免限制重要的业务沟通。
It makes life even harder for defenders when the bad actor has successfully assumed the identity of somebody senior. If they are impersonating a top-tier manager with an extensive and trusted reputation then they have a powerful asset on their hands. All the trust and goodwill of that senior individual is now inherited by the criminal. Conventional email filtering systems will often be configured to allow senior personnel past certain defensive layers with minimal friction, so as not to restrict important business communications.
如果收到来自这类来源的邮件,且邮件内容令人怀疑(尤其是当邮件中请求的信息显得不合理或可疑时),收件人可能不愿意对此提出质疑或进行举报。只有那些敢于冒险的员工才会指出这些邮件其实是欺诈行为——尤其是当电子邮件系统已经判定这些邮件为“真实”时。如今,不仅IT部门面临压力,那些为多个组织提供安全服务的MSP(Managed Service Providers)也同样面临巨大挑战;这些组织中的许多本身并没有专业的安全防护知识。
Recipients of mail from such sources may be disinclined to challenge and report them, should suspicions be raised by the nature of what they are asking for. It takes a bold employee to call out as fraud what seems to be a message from somebody at C-level, especially when the email system has apparently green lighted it as authentic. Bringing the power of AI to bear The heat is on not just for IT departments but for MSPs who have multiple organisations under their protection, many of which will have no real in-house security knowledge of their own.
Kaseya自己的研究就表明,许多组织实际上都处于高度脆弱的状态中。因此,我们需要新的方法来及时应对账户被非法控制的威胁,从而在造成损害之前阻止其发生。如果账户确实被非法控制,就必须采取措施来限制其影响,确保重要数据和基础设施的安全。好消息是,现代技术已经具备了完成这些任务的能力。INKY就是Kaseya开发的一款基于生成式AI的电子邮件分析工具。
Kaseya’s own research shows just how exposed many are. New approaches are needed that deal with the menace of account takeover before damage can be caused. And should a takeover transpire, consideration must be given to containing its impact before vital data and infrastructure are affected. The good news is that modern tools exist that perform just these tasks. INKY is Kaseya's generative AI-driven email analysis tool.
它的功能远超传统的电子邮件安全系统:它能够通过最细微的线索,检测出电子邮件对话是否正在被入侵。通过先进的发送者画像分析、文体分析以及机器学习技术,INKY能够识别出合法员工与虚假邮件之间的语言风格差异;即使邮件头部信息看似真实,它也能通过分析上下文中的异常之处来判断邮件是否为伪造。在处理第三方账户被非法控制的事件时,INKY尤为有效——它通过收集并维护可信发送者的详细信息(包括技术特征和行为习惯),建立起这些发送者的“档案”。
It has capabilities that go well beyond any kind of traditional email security, tuned to detect, through the most subtle and marginal signs, when an email conversation is in the process of being infiltrated. Using techniques such as advanced sender profiling, stylometry and machine learning, INKY is adept at identifying inconsistencies between the known writing patterns of a legitimate employee and the slightly unfamiliar tone of a fake message. It can sniff out that something is wrong, even when message headers seem real, just by spotting the kind of contextual anomalies that expose a phoney message. INKY is especially useful when it comes to third party account takeover.
随着时间的推移,INKY能够逐渐识别出“正常”的发送行为模式,从而判断第三方发送的邮件是否与这些档案中的信息不符。
It achieves this by building and maintaining detailed profiles of trusted senders based on technical and behavioural characteristics.
- 人名和地名一律使用中文字符进行转写;品牌名称和产品名称可保留其原有的拉丁字母形式。
Over time it learns what “normal” looks like and can see when a third-party email doesn’t match a sender’s established profile.
如果收购尝试成功,仅仅封禁嫌疑账户是远远不够的……一旦发现入侵行为,受损的范围可能已经远远超出了单一电子邮件线程的范畴。因为被入侵的身份信息可能已经被用来入侵相关的 SaaS 应用程序、云存储系统及协作工具,从而扩大了攻击的影响范围。现代 IT 环境由众多基于身份认证的终端设备和网关组成,因此对于那些持有合法凭证的入侵者来说,防御工作变得极为困难。
Containing an attack If a takeover attempt has been successful, there’s more to stemming the damage than just putting a block on a suspect account. By the time of its discovery, a compromised identity may have already led to inroads being made into connected SaaS apps, cloud storage and collaboration tools, widening the possible blast zone well beyond a single email thread. Modern IT environments are a jungle of identity-driven endpoints and gateways, and therefore increasingly difficult to defend against intruders armed with legitimate credentials.
更糟糕的是,当攻击者掌握了人工智能技术后,他们可以将这些 SaaS 应用程序视为一个统一的攻击目标。仅依赖那些为解决组织内部特定问题而单独开发的防御工具,根本无法有效应对这类威胁。
To compound matters, when the bad guys have AI at their disposal they are able to treat these SaaS-driven ecosystems as a single attack surface. Defence that relies on a patchwork of individual tools, each created to solve a particular challenge in one silo of the organisation, will not be up to countering this kind of threat.
INKY 与 Kaseya SaaS Alerts 的协同作用为了解决这一问题,INKY 被设计为与 Kaseya SaaS Alerts 这一基于云的检测与响应平台配合使用。Kaseya SaaS Alerts 专门帮助托管服务提供商(MSP)等机构监控和保护企业应用程序。当 INKY 检测到某个邮箱被黑客控制时,它会立即隔离该用户并阻止其发送任何邮件。
That’s why INKY is configured to work with Kaseya SaaS Alerts, a cloud-based detection and response platform designed to help MSPs and others to monitor and protect business applications. Once INKY has picked up that a mailbox has been hijacked, it isolates the user and blocks outbound mail. It then sends an event to SaaS Alerts so that it can lock down that user's access across the rest of the stack.
随后,INKY 会向 Kaseya SaaS Alerts 发送警报,以便进一步限制该用户在所有受影响系统中的访问权限。这两个工具协同工作:INKY 负责阻止被入侵的账户继续发送邮件,而 Kaseya SaaS Alerts 则防止损害进一步扩散。这种集成机制的强大之处在于 INKY 能够将实时的电子邮件安全数据(包括传入邮件的分析结果、威胁检测信息、用户报告的钓鱼攻击行为以及邮件发送过程中的安全事件)实时传输给 Kaseya SaaS Alerts。这种集成方式有助于在整个复杂的 SaaS 生态系统中实现实时威胁检测。
The tools work as a team, INKY blocking the compromised account and SaaS Alerts preventing the damage from spreading. The power of this partnership comes from INKY’s ability to stream real-time email security telemetry into SaaS Alerts, including inbound analysis results and threat detections, user-reported phishing activity and outbound mail protection events. This type of integration helps to automate real-time threat detection across a complex SaaS ecosystem.
Baggett 如是说:“这意味着,一旦发现可疑邮件被发送出去,我们就可以立即关闭相关账户并采取其他补救措施。”“你越能理解邮件的含义,就能拦截得越多。” 智能工具来援手对抗账户接管的战斗永远不会结束,未来的创新始终是必要的。我们已经看到,AI 在攻击者手中是一种危险的武器。它也是防御者手中一件非常得力的工具——但有一些前提条件:“你不能把每一封收发邮件都扔给大语言模型处理,因为算不过经济账,”Baggett 指出道。“你必须想得更周全。”
“It means if we see suspicious mail going out, we can shut the account down, and take other remedial actions,” says Baggett. “The more you understand the meaning of the mail, the more you can catch.”Smart tools to the rescue The battle against account takeover is never won, and future innovation is always needed. We’ve seen how AI is a dangerous weapon in the hands of the attacker. It’s also a very handy tool for the defender – but there are some qualifications: “You can’t just put every inbound and outbound mail through an LLM since the economics don’t add up,” points out Baggett. “You’ve got to be more clever than that.”
生成式 AI 最重要、也最聪明的新兴用途之一,不在于单纯防范账户接管,而在于预测弱点可能出在何处,帮助在问题发生前就将其阻止。Baggett 认为,安全行业利用模型进行此类预测的能力才刚刚起步。一个必不可少的前提工作,是确保保护组织安全的诸多不同组件能够彼此共享信息。这种集成工作已在进行中,一个早期的例子是 INKY 邮件保护系统与 SaaS Alerts 之间的实时对话。下一步是建立一个统一数据层,让任何安全组件都能实时发布事件,任何其他组件也能实时获取。
One of the most important and cleverest emerging uses for GenAI lies in not simply protecting against account takeover but predicting where weakness might lie, helping to stop a problem before it happens. Baggett believes that the security industry is at the very beginning of being able to use models to predict in this way. An essential preliminary is making sure the many different components that go into securing an organisation can share information with each other. That integration work is underway, an early example being the real time dialogue between INKY Mail Protection System and SaaS Alerts. Next step is a unified data layer where any security component can publish an event in real time, and any other component can.
“我们将随着时间的推移,继续推出更多此类集成,”Baggett 承诺道。“我们还在构建一个集中式的 AI 能力平台。既然这么多不同组件都有自己的 AI,你就需要一个底层支撑平台。我们还拥有一支机器学习专家服务团队,能为不同任务定制模型。绝不能有丝毫松懈。攻击量显然将会增加。”
“We’ll continue to make more integrations of this sort over time,” promises Baggett. “We’re also building a centralised capability for AI. With so many of the different components having their own AI, you need an underpinning platform. We also have a service bureau of Machine Learning experts who can make customised models for different tasks. There’s no sleeping on the job. The volume of attacks is clearly going to increase.”