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    Home » Pig Butchering Scams Are Going High Tech
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    Pig Butchering Scams Are Going High Tech

    News RoomBy News RoomOctober 14, 20243 Mins Read
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    As digital scamming explodes in Southeast Asia, including so called “pig butchering” investment scams, the United Nations Office on Drugs and Crime (UNODC) issued a comprehensive report this week with a dire warning about the rapid growth of this criminal ecosystem. Many digital scams have traditionally relied on social engineering, or tricking victims into giving away their money willingly, rather than leaning on malware or other highly technical methods. But researchers have increasingly sounded the alarm that scammers are incorporating generative AI content and deepfakes to expand the scale and effectiveness of their operations. And the UN report offers the clearest evidence yet that these high tech tools are turning an already urgent situation into a crisis.

    In addition to buying written scripts to use with potential victims or relying on templates for malicious websites, attackers have increasingly been leaning on generative AI platforms to create communication content in multiple languages and deepfake generators that can create photos or even video of nonexistent people to show victims and enhance verisimilitude. Scammers have also been expanding their use of tools that can drain a victim’s cryptocurrency wallets, have been manipulating transaction records to trick targets into sending cryptocurrency to the wrong places, and are compromising smart contracts to steal cryptocurrency. And in some cases, they’ve been purchasing Elon Musk’s Starlink satellite internet systems to help power their efforts.

    “Agile criminal networks are integrating these new technologies faster than anticipated, driven by new online marketplaces and service providers which have supercharged the illicit service economy,” John Wojcik, a UNODC regional analyst, tells WIRED. “These developments have not only expanded the scope and efficiency of cyber-enabled fraud and cybercrime, but they have also lowered the barriers to entry for criminal networks that previously lacked the technical skills to exploit more sophisticated and profitable methods.”

    For years, China-linked criminals have trafficked people into gigantic compounds in Southeast Asia, where they are often forced to run scams, held against their will, and beaten if they refuse instructions. Around 200,000 people, from at least 60 countries, have been trafficked to compounds largely in Myanmar, Cambodia, and Laos over the last five years. However, as WIRED reporting has shown, these operations are spreading globally—with scamming infrastructure emerging in the Middle East, Eastern Europe, Latin America, and West Africa.

    Most prominently, these organized crime operations have run pig butchering scams, where they build intimate relationships with victims before introducing an “investment opportunity” and asking for money. Criminal organizations may have conned people out of around $75 billion through pig butchering scams. Aside from pig butchering, according to the UN report, criminals across Southeast Asia are also running job scams, law enforcement impersonation, asset recovery scams, virtual kidnappings, sextortion, loan scams, business email compromise, and other illicit schemes. Criminal networks in the region earned up to $37 billion last year, UN officials estimate. Perhaps unsurprisingly, all of this revenue is allowing scammers to expand their operations and diversify, incorporating new infrastructure and technology into their systems in the hope of making them more efficient and brutally effective.

    For example, scammers are often constrained by their language skills and ability to keep up conversations with potentially hundreds of victims at a time in numerous languages and dialects. However, generative AI developments within the last two years—including the launch of writing tools such as ChatGPT—are making it easier for criminals to break down language barriers and create the content needed for scamming.

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