内容来源：https://www.wired.com/story/ai-is-getting-really-good-at-messing-with-cybercriminals/

内容总结：

人工智能正成为打击网络诈骗的新武器。澳大利亚公司Apate开发了一套AI机器人系统，能冒充潜在受害者与电话诈骗分子周旋，尽可能长时间地拖延通话，同时实时收集诈骗情报。该公司创始人兼首席执行官达利·卡法尔表示，平台目前拥有约35万个机器人，已实时收集超过25万条诈骗者信息，包括诈骗网址、钱骡账户和银行信息等。这些机器人具有不同性格、语言能力和背景资料，以降低被识破的风险。卡法尔称，Apate的通话通常能持续两个小时以上。

与此同时，AI驱动的“蜜罐”技术也被用于对抗黑客。苏黎世联邦理工学院博士生马克·韦罗的研究发现，由大语言模型驱动的蜜罐能让AI攻击者花费“显著更长”的时间进行攻击，且被识破为蜜罐的概率更低。

尽管全球网络犯罪形势依然严峻，执法部门和研究机构难以遏制数字诈骗的整体扩张，但AI正在为反诈骗工作开辟新路径。通过AI驱动的监控和数据分析，警方、社交媒体公司、银行等行业之间有望实现更好的情报共享。此外，利用生成式AI消耗诈骗者和网络犯罪分子的资源、使其无暇发动其他攻击的做法，正日益显现出效果。

中文翻译：

欢迎来到《内核恐慌》！这是莉莉·海·纽曼和马特·伯吉斯每周撰写的电子报，带你深入了解隐私与数字安全的新世界。想每周在收件箱中收到这份电子报，请在此订阅。

尽管人工智能加剧了数字诈骗和网络犯罪，它也被招募来保护潜在受害者。世界各国政府在应对全球网络犯罪危机方面一直举步维艰，苦于无法跨境打击犯罪分子。这催生了各种替代方案，比如利用自动化手段大规模反击诈骗者——或许通过向诈骗者发送垃圾信息来消耗他们的资源。如今，人工智能平台正将这类实验转化为打击网络犯罪的实际工具。

过去两年间，澳大利亚公司Apate——以希腊神话中的欺骗女神命名——一直在构建一套系统，将电话诈骗者引导至与AI机器人的通话中。这些机器人经过训练，会尽可能延长对话时间，当然，绝不会真正上当受骗。其目标是给诈骗者足够的希望，让他们留在线上，同时收集有关其所实施诈骗的情报。

“我们真正想做的事情是，为诈骗者打造完美的受害者，”Apate创始人兼首席执行官达利·卡法尔告诉我们。“诈骗者与机器人或代理通话的每一分钟，都可能意味着你拯救了数百甚至数千名可能被同一个诈骗者接触到的潜在受害者，”他说，并提到诈骗者能够使用自动拨号工具。

卡法尔表示，Apate的平台被银行使用，并得到电信公司的支持，目前拥有约35万个机器人。它们不仅能接听电话，还能渗透到网上的诈骗聊天群组中，并以类似的目标回复短信——既让诈骗者感到挫败，又从他们那里收集情报。他说，该公司已实时收集了超过25万条关于诈骗者的信息，从诈骗网址到钱骡账户和银行信息，不一而足。

卡法尔说，这些机器人拥有不同的性格、语言能力和人物设定，这样诈骗者就不会察觉自己正在与AI对话。和真人一样，“有时候（机器人）有WhatsApp，有时候没有。有时候它们接电话，有时候它们就直接挂断，对诈骗者说‘我回头再找你’，”他说。

但它们有说服力吗？《内核恐慌》用一个演示版本测试了这款工具，用户扮演诈骗者的角色，与Apate的AI“受害者”对话。这些人物设定被设计为表现出适度的怀疑态度，但又留出足够的空间让诈骗者继续试图赢得他们的信任——这种互动节奏我们立刻就能感受到，并且觉得极其令人沮丧。

诈骗者很可能熟悉这种充满怀疑的互动方式，卡法尔说Apate的通话通常会持续两个多小时。在我们的测试中，Apate系统反应积极、应答流畅，对话的节奏感觉很自然，即使我们俩配合扮演一个朋友“露西”和她的财务顾问“米奇”来联手对付AI。即便经过六分钟的坚持不懈，我们也没能成功让Apate的AI系统投资我们的加密货币机会。（不过回报真的非常惊人，我们发誓。）

目前，即便Apate有庞大的机器人军团在应对，你下一次收到诈骗电话或短信也只是时间问题。网络犯罪分子每年发起数十亿条信息和电话，其中最精密的活动运营着实体化、工业规模的诈骗站点。尽管专业的反诈骗人士和渗透诈骗活动的行动多年来做了关键的威慑工作，但执法部门和研究努力仍未能阻止数字诈骗的整体扩张。

但AI可能为反诈骗工作开创一个新时代，而不仅仅是服务于诈骗者本身。警方、社交媒体公司、银行和其他行业之间迫切需要更好的情报共享，而AI驱动的监控和数据分析可能为此提供助力。越来越多的创新行动也在试图利用网络犯罪分子的“心理弱点”来打击他们。在某些案例中，这些心理战包括直接嘲讽勒索软件攻击背后的操纵者。随着对干扰诈骗者和网络犯罪分子的关注不断扩大，利用生成式AI让他们忙于应付、浪费资源、无暇发动其他攻击，似乎正变得越来越有效。

以蜜罐为例。多年来，公司和安全研究人员一直在部署虚假虚拟机来吸引黑客，浪费他们的时间、收集信息并了解他们秘密的黑客技术。苏黎世联邦理工学院计算机科学系的博士研究员马克·韦罗表示，开源蜜罐提供商越来越多地将大语言模型融入其系统，使其看起来更加逼真。

在最近的研究中，韦罗和同事发现，由大语言模型驱动的蜜罐会让AI攻击代理对其系统攻击“明显更长时间”，相比行为更可预测的蜜罐。“代理型攻击者更容易被大语言模型模拟的蜜罐所说服，而且它们将这些蜜罐标记为真实蜜罐的比率也低得多，”他说。“如果这些系统构建得足够好，我认为对防御方来说是非常有利的。”

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英文来源：

Welcome to Kernel Panic!, a weekly newsletter by Lily Hay Newman and Matt Burgess from inside the new world of privacy and digital security. To receive this newsletter in your inbox each week, sign up here.
Even as AI supercharges digital scamming and cybercrime, it’s also being recruited in the fight to protect potential victims. Governments around the world have consistently struggled to address the global crisis of online crime, grappling with the limitations of attempting to crack down on criminals beyond their borders. This has inspired alternative efforts, like using automation to attempt to go after scammers en masse—perhaps by spamming the spammers to squander their resources. Now, AI platforms are turning these types of experiments into real tools in the fight against cybercrime.
For the last two years, the Australian company Apate, named after the Greek goddess of deception, has been building a system that diverts phone scammers onto calls with AI bots that are trained to keep conversations going as long as possible without, of course, ever actually falling for the scam. The goal is to give scammers enough hope that they stay on the phone, while also collecting intelligence about the scams they’re running.
“What we really like to think is that we’re building the perfect victims for scammers,” Dali Kaafar, the founder and CEO of Apate, tells us. “A minute that a scammer is talking to a bot or an agent is a minute where you’re probably saving hundreds, if not thousands of possible people being reached out to by that exact same scammer,” he says, referencing the ability for scammers to use automated dialing tools.
Kaafar says Apate’s platform, which is used by banks and supported by telecom companies, has around 350,000 bots. They not only pick up calls, but also infiltrate scam chat groups online and respond to text messages with similar goals of frustrating scammers while collecting intelligence from them. He says the company has collected more than 250,000 pieces of information about fraudsters in real-time, from scam URLs to money mule accounts and bank details.
The bots have different personalities, language skills, and profiles, Kaafar says, so scammers hopefully don’t detect that they’re conversing with an AI. Like real people, “sometimes [the bots] do have WhatsApp, sometimes they don’t. Sometimes they pick up the phone, sometimes they just actually hang up on the scammer saying, ‘I'll come back to you later,’” he says.
But are they convincing? Kernel Panic tested the tool using a demo version where users play the role of the scammer and talk to one of Apate’s AI “victims.” The personas are designed to express a healthy amount of skepticism but leave enough openings for scammers to continue to try to win them over, a dynamic that we could immediately feel and found intensely frustrating.
Scammers are likely familiar with this type of skeptical interaction, and Kaafar says that Apate calls regularly go on for more than two hours. In our testing, the Apate system was engaged and responsive, and the timing of the conversation felt natural, even with both of us tag-teaming the AI as a friend, “Lucy,” and her financial adviser “Mickey.” We did not succeed at getting the Apate AI system to invest in our cryptocurrency opportunity even after six minutes of diligent effort. (The returns are truly incredible, though, we swear.)
For now, even with Apate’s massive swarm of bots on the case, it’s only a matter of time before you get your next scam call or text. Cybercriminals initiate billions of messages and calls each year, with the most sophisticated operations running physical, industrial scale scamming sites. And while professional scambaiters and initiatives to infiltrate scam operations have done critical deterrent work for years, law enforcement and research efforts haven’t been able to stop the expansion of digital scamming overall.
But AI could create a new era for anti-scam efforts, not just scammers themselves. Better intelligence sharing between cops, social media companies, banks, and other industries is desperately needed and could potentially be aided by AI-driven monitoring and data analysis. Increasingly, too, innovative efforts have been looking to disrupt cybercriminals by exploiting their “psychological vulnerabilities.” In some cases, these psyops have included directly trolling those behind ransomware attacks. As the focus on disrupting scammers and cybercriminals expands, the use of generative AI as a way to keep them preoccupied, wasting resources, and not launching other attacks appears to be increasingly effective.
Take honeypots, for instance. For years, companies and security researchers have deployed false virtual machines to attract hackers, waste their time, gather information, and understand their secret hacking techniques. Mark Vero, a doctoral researcher at the department of computer science at ETH Zurich, says open source honeypot providers have increasingly been incorporating LLMs into their systems to make them appear more realistic.
In recent research, Vero and colleagues found an LLM-powered honey pot would keep AI agents attacking their system “significantly longer” than a honey pot with more predictable behavior. “The agentic attackers are much more convinced by the LLM simulated honeypots and they also mark them as actual honeypots at a much lower rate,” he says. “If these systems are built well enough, then I think it’s quite advantageous for defenders.”
Spotted something we should include next week? Let us know at [email protected]. And stay safe out there.
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