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    Home»Fraud & Scams»AI-Driven Fraud Fueling $521 Billion ‘National Security Crisis,’ Warns Cybersecurity Firm
    Group of shadowy fraudsters in suits working on glowing laptops with silver and teal AI circuits, red and black shards scattering across the table, symbolizing a $521 billion national security crisis.

    AI-Driven Fraud Fueling $521 Billion ‘National Security Crisis,’ Warns Cybersecurity Firm

    By CapitalAI Daily TeamSeptember 5, 20252 Mins Read
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    A cybersecurity firm valued at $2 billion is warning that the escalation of AI attacks represents not just a financial problem but a threat to US national security.

    Citing data from the Government Accountability Office, ID.me says that fraudsters drained up to $521 billion annually from the US government.

    Meanwhile, criminal networks in Russia, China, and Nigeria siphoned billions from pandemic relief programs, as North Korean actors increasingly target American companies using stolen identities.

    “Fraud is now both a financial and national security crisis… Fraudsters are now weaponizing AI tools like deepfakes to exploit vulnerabilities faster than ever. Defeating them requires equally advanced, rapidly deployed solutions.”

    Blake Hall, ID.me’s founder and chief executive, underscores the pace of escalation.

    “Fraud is evolving at the speed of AI… Secure identity is foundational to AI ecosystems that will depend on memory, context, and authentication.”

    ID.me is not alone in sounding the alarm about AI-driven identity theft. A new study from Juniper Research projected that global fraud losses will surge 153%, climbing from $23 billion in 2025 to $58.3 billion in 2030, driven by criminals using artificial intelligence (AI) to forge convincing personas built from stolen and fabricated data.

    Recently, a South Los Angeles woman sold her condo for $350,000 and lost $81,304 after scammers used artificial intelligence to impersonate General Hospital star Steve Burton.

    AI AI fraud artificial intelligence Fraud identity theft Scam

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