加密貨幣向來是詐騙者的溫床。近年來，科技—特別是人工智慧的進步—大幅提升詐騙規模與複雜度，令詐騙策略更精密、更具規模，且更難察覺。
加密交易本身的去中心化與偽匿名特性，已為執法與受害者帶來獨特挑戰。如今，隨著AI的應用，詐騙者掌握了能栩栩如生模仿真人、大規模自動化網路釣魚，甚至從零打造完整數位人物或專案的新戰術。
這場轉型早已不是紙上談兵。報告顯示，與加密貨幣詐騙相關的投訴及損失激增，AI加持的詐騙是主要推手之一。
這些攻擊手法之精巧，甚至讓資深投資人和產業專家都難以倖免。新一波詐騙潮利用深偽、語音仿製、AI生成的釣魚訊息與自動交易詐騙，現實與假象的界線變得模糊不清。
結果是威脅環境演變速度遠超傳統安全措施的應變，讓個人投資人及整個加密生態圈都籠罩在風險之中。
充分理解現代詐騙手法的運作機制，是所有涉足加密領域者—無論是投資人、開發者還是平台營運者—的必修課。本篇文章將深入探討最普遍及新興的加密詐騙形式，特別著重於AI強化的詐騙方案。
合成信任的興起
加密詐騙最具顛覆性的發展之一是深偽技術的應用。深偽為AI生成的影音檔案，能以假亂真模仿真人，特別是公眾人物或產業領袖。在加密領域中，詐騙集團愛用深偽技術，設法利用投資人對名人信任的心理。
深偽詐騙通常先製作某知名人物（如科技執行長、加密影響者、甚至政府官員）推銷詐騙項目或投資機會的超擬真影音，再將這些內容發到社交媒體、通訊軟體，甚至假新聞文章中，以擴大散播。
這些深偽內容之真實度，足以連熟悉產業的觀察者也誤信不疑，尤其當它夾雜虛構背書與偽造螢幕截圖來模仿主流媒體的形式。
深偽詐騙的影響非常深遠。受害者被誘導向詐騙控制的錢包轉帳，以為在參與獨家投資機會或贈獎活動。有時甚至整個社群都被深偽策動的行動所欺騙，造成重大財務損失，加深加密生態圈的信任危機。
AI的可擴展性代表詐騙可同時在多平台發動，幾小時內即可鎖定數千名潛在受害者。
深偽冒充的最大危險，在於它能腐蝕支撐數位金融的根基—信任。一旦用戶無法分辨真實與合成的背書，基於聲譽的投資模式便易受攻擊。外界因此呼籲發展更強驗證工具，提高數位素養，但技術仍遠快於防禦手段的步伐。
隨著深偽技術日益普及與平價，潛在詐騙者的門檻大幅降低。開源軟體與線上教學，讓技術門檻不高者也能產出有說服力的深偽內容。
欺詐門檻的下降等同於「騙術民主化」，凡具備基本技術就能發動高影響力詐騙攻勢。此趨勢未見放緩，使深偽冒充成為加密產業最亟需解決的難題之一。
AI生成網路釣魚
網路釣魚一直是線上詐騙的主力手法，但AI已將其提升至全新層次。傳統釣魚是透過群發郵件或假網站誘騙用戶洩漏敏感資訊，有了AI，這類攻擊變得更逼真、個人化且更具規模。
AI釣魚方案會先大量蒐集並分析公開資料。機器學習算法能掃描社群檔案、交易紀錄、論壇發文，建立潛在受害者的詳細人像。這讓詐騙者能量身打造訊息，參照真實事件、聯絡人或投資資訊，大幅提升釣魚成功率。這些訊息用語經常毫無瑕疵，不見以往容易警醒的文法錯誤。
除了郵件，AI聊天機器人也已進場。它們能與受害人進行即時對話，冒充主流交易所的客服。這些聊天機器人之精巧程度足以回答疑問、提供虛假疑難排解，最終誘騙用戶交出私鑰或憑證。
有時甚至整個仿真交易網站都由AI生成，配備假造交易紀錄、見證與客服管道，營造逼真合法的外觀。
AI自動化特性使釣魚活動規模空前。同時可啟動數千封個人化郵件或機器人對話，每次失敗都讓AI能調整策略，讓流程更有效、也更加自我進化。
AI型網釣的後果極其深遠。受害者可能失去錢包存取權、個資外洩，甚至淪為進一步詐騙的工具。而攻擊數量之多，讓傳統安全機制疲於應付，平台難以招架。
隨AI不斷演進，真實與詐騙的界線將更模糊，勢必得仰賴高度警覺與進階偵測工具來防範。
自動交易詐騙
毫不費力賺取收益的承諾，一直是加密領域極具誘惑力的賣點，詐騙集團也利用這點熱炒AI交易機器人與自動投資平台。這類詐騙常宣稱擁有能穩定獲利且風險極低的演算法，並附帶偽造的報酬數據與熱烈見證。
這類詐騙操作流程簡單。受害人被邀請將資金存入交易平台或綁定錢包給AI機器人，號稱能代表他們自動下單實現獲利。實則不少平台是徹頭徹尾的詐騙，專為吞噬存款設計，最後無聲消失。另有些則是龐氏騙局，後金補前金，操作者從中剝削利潤。
AI讓這類詐騙能打造寫實的交易儀表板、即時客服，甚至模擬合法交易所的虛擬交易活動。有些平台還用AI生成白皮書與路線圖，加上專業術語及設計，營造權威感。
還有AI深偽推薦與假名人背書，進一步強化騙局可信度，連資深投資人也可能中招。
在市場波動劇烈時，自動交易的誘惑尤為強大，許多詐騙者藉「保證獲利」、「專屬演算法」或「搶先進場」等話術利誘，甚至施壓要盡快行動錯失即逝。
自動交易詐騙的災損非常嚴重。受害者不只損失本金，還可能因授權交易而面臨更多資安風險。這類詐騙日益普遍，監管壓力隨之升高，但加密世界的去中心與無國界特點，讓執法依然困難。AI自動交易詐騙持續演化，投資人需提高警覺與審慎查證從未如此重要。
AI強化Rug Pull（抽地毯）
Rug pull為惡名昭彰的加密詐騙，開發團隊推出新專案，吸引大額投資後，突然捲款潛逃。雖非新鮮事，但AI讓這類騙局更難識破、更難防範。
AI在此類騙局中的應用，常從偽造但極具說服力的白皮書、網站及社交帳號做起。AI可
generate technical documentation, project roadmaps, and even code snippets that appear legitimate to the untrained eye.
產生技術文件、專案路線圖，甚至看起來對於外行人來說相當正規的程式碼範例。
These materials are often accompanied by AI-generated social media activity, including posts, comments, and interactions that create the illusion of a vibrant and engaged community.
這些資料經常伴隨著 AI 產生的社群媒體活動，包括貼文、留言以及互動，營造出一個活躍並且充滿互動的社群假象。
Influencer marketing is another area where AI has made a significant impact. Scammers use AI-powered bots to flood forums, Twitter, and other platforms with positive reviews and endorsements. In some cases, deepfake videos of well-known figures are used to promote the project, lending an air of credibility that is difficult to achieve through traditional means. The result is a meticulously crafted ecosystem that appears legitimate, drawing in unsuspecting investors who are eager to participate in the next big thing.
網紅行銷也是 AI 造成重大影響的另一個領域。詐騙者利用 AI 驅動的機器人，在論壇、X/Twitter 以及其他平台上大量散布正面評論與背書。有時更會利用名人深偽（Deepfake）影片宣傳項目，營造出傳統途徑難以達到的可信度。其結果就是建立起一個精心打造的、看似正當合法的生態圈，吸引毫無戒心、渴望參與下一波熱潮的投資人。
Once a critical mass of investment has been reached, the operators execute the rug pull, draining the project's liquidity and disappearing. The speed and coordination enabled by AI make it possible to execute these exits with minimal warning, leaving victims with worthless tokens and no recourse for recovery.
一旦投資達到一定規模，操作者就會執行「地毯拉拽」（Rug Pull），抽走項目的資金流動性並迅速消失。AI 提供的速度與協同效應，使得這些退出行為幾乎不留任何預警，受害者最終只能手握毫無價值的代幣，而且沒有任何追回的途徑。
The scale of AI-enhanced rug pulls is alarming. The ability to automate the creation and promotion of fake projects means that scammers can launch multiple schemes simultaneously, increasing their chances of success.
AI 賦能的 rug pull（跑路）規模非常驚人。自動化建立與推廣假項目的能力，讓詐騙集團可以同時發動多起詐騙計畫，大幅提升其成功的機會。
The use of AI also makes it easier to adapt to changing market conditions, tweaking project details or pivoting to new narratives as needed. This adaptability, combined with the anonymity afforded by blockchain, makes rug pulls one of the most persistent threats in the crypto space.
AI 也讓詐騙者能夠更輕鬆地因應市場變化，隨時調整專案細節或轉移話題。這種彈性，加上區塊鏈本身的匿名性，讓 rug pull 成為加密貨幣領域中最難消除的持續性威脅之一。
Fake Reviews and Social Proof
Social proof is a powerful motivator in investment decisions, and scammers have long exploited this by generating fake reviews and testimonials. With AI, the scale and realism of these efforts have reached new heights, making it increasingly difficult for investors to distinguish genuine feedback from manufactured hype.
社會認可（Social Proof）是驅動投資決策的強大動力，而詐騙者早就利用偽造評論與推薦來操弄這一點。隨著 AI 的進步，這類操作的規模與真實感達到前所未有的水準，讓投資人越來越難區別哪些是來自真實用戶的回饋，哪些又是刻意捏造的宣傳。
AI-driven fake reviews are often deployed across multiple platforms, including social media, forums, and review sites. These reviews are crafted to mimic the language and tone of real users, complete with specific details about the investment process, returns, and customer support experiences. In some cases, deepfake technology is used to create video testimonials that appear to feature real investors sharing their success stories.
AI 主導的虛假評價會在多個平台鋪天蓋地地發布，包括社群媒體、論壇和評價網站。這些評論特別模仿真實用戶的語言風格，甚至包含投資流程、收益與客服經驗等細節，有些甚至會利用深偽技術產生「真人投資人」敘述成功經驗的影片推薦。
The impact of fake social proof is twofold. First, it creates a false sense of legitimacy around fraudulent projects, encouraging more investors to participate. Second, it drowns out genuine feedback, making it harder for potential victims to find accurate information. This is particularly problematic in the fast-moving world of crypto, where decisions are often made quickly and based on limited data.
虛假社會認可帶來雙重衝擊：第一，這會為詐騙項目營造一種虛假的正當性，誘使更多投資人參與；第二，也讓真實且有用的意見被淹沒，潛在受害者更難獲取正確資訊。這在快速變動的加密貨幣世界中尤其危險，因為人們通常依靠有限資訊快速做決定。
AI also enables the automation of social media activity, with bots generating likes, shares, and comments to amplify the reach of fraudulent content. This creates the illusion of widespread interest and engagement, further reinforcing the project's credibility.
AI 亦讓社群活動完全自動化，機器人可自動產生按讚、分享、留言等互動，大幅擴散詐騙內容的能見度。這樣不但營造出廣泛關注與熱絡的假象，更強化了項目的可靠形象。
In some cases, scammers coordinate these efforts with influencer partnerships, either by impersonating real influencers or by paying for endorsements from lesser-known personalities.
某些情況下，詐騙者甚至配合所謂的網紅合作推廣，有時冒充知名意見領袖，有時則購買知名度較低人物的推薦。
The prevalence of AI-generated fake reviews has prompted some platforms to implement stricter verification measures, but the arms race between scammers and defenders continues. As AI becomes more sophisticated, the line between real and fake social proof will only become more blurred, making it essential for investors to approach online reviews with a healthy dose of skepticism.
隨著 AI 生成的假評價愈來愈普及，有些平台只好實施更嚴格的驗證措施。但騙子與防禦者之間的攻防賽仍持續升級。隨著 AI 持續進化，真實與偽造的社會證明只會越來越難分辨，投資人必須謹慎看待線上評論，培養必要的懷疑精神。
Identity Theft and Synthetic Identities
Identity theft has always been a concern in the digital world, but AI has introduced new dimensions to this threat. Scammers now use AI to create synthetic identities - combinations of real and fabricated information that can pass as legitimate in online verification processes. These synthetic identities are used to open accounts, bypass KYC checks, and perpetrate a range of fraudulent activities.
數位時代早就有身份盜用問題，但 AI 讓這種威脅產生嶄新面貌。詐騙者如今利用 AI 生成「合成身份」，將真實資料與偽造資訊混合，足以通過線上驗證程序。這些合成身份可以用來開設帳戶、繞過 KYC（認識你的客戶）檢查，以及執行各種詐騙行為。
The process often begins with the collection of publicly available data, such as names, addresses, and social media profiles. AI algorithms then generate realistic documents, including passports, driver's licenses, and utility bills, that can be used to verify identities on exchanges or other platforms. In some cases, scammers use deepfake technology to conduct video verification calls, impersonating real individuals in real time.
這種手法通常從蒐集公開資料開始，例如姓名、地址和社群媒體檔案。AI 接著生成看似真實的證件，包括護照、駕照和水電帳單，可用於交易所或其他平台的身份驗證。有些詐騙甚至利用深偽技術，進行即時視訊身份驗證通話，假扮真人身分。
The implications of synthetic identity fraud are significant. Once an account has been established, scammers can use it to launder funds, execute pump-and-dump schemes, or perpetrate further scams. The use of AI makes it difficult for platforms to distinguish between real and fake users, undermining the effectiveness of traditional security measures.
合成身份詐騙的影響深遠。一旦帳戶建立，詐騙者可用來洗錢、操作拉抬出貨（pump-and-dump）或進行更多詐騙。AI 的應用讓平台難以區分真實與假用戶，嚴重削弱傳統安全措施的功效。
Victims of identity theft may find themselves implicated in fraudulent activities or face difficulties accessing their own accounts. The scalability of AI-driven identity fraud means that thousands of synthetic identities can be created and deployed in a short period, overwhelming the resources of even the most well-prepared platforms.
身份遭竊的受害者可能被牽連捲入詐騙活動，甚至無法順利存取自己的帳戶。AI 推動的身份詐騙具有高度擴展性，短時間內能產生數千個合成身份，即使再嚴密的平台也可能應接不暇。
As AI continues to evolve, the challenge of combating synthetic identity fraud will only intensify. New verification techniques, such as biometric analysis and behavioral profiling, are being explored, but the arms race between scammers and defenders shows no signs of abating.
隨著 AI 持續發展，對抗「合成身份」詐騙的挑戰只會不斷加劇。市面上正積極研發如生物辨識、行為輪廓分析等新型驗證技術，但詐騙與防護的軍備競賽短期內不會終止。
Multi-Stage and Hybrid Scams
One of the most concerning trends in modern crypto fraud is the emergence of multi-stage and hybrid scams. These schemes combine elements of phishing, deepfake impersonation, social engineering, and automated trading to create complex, layered attacks that are difficult to detect and defend against.
當前加密詐騙最令人士憂的趨勢之一，就是「多階段與混合型詐騙」的崛起。這些手法融合網釣、深偽假冒、社交工程與自動化交易等元素，組成層層疊疊、難以偵測與防範的複雜攻擊。
A typical multi-stage scam might begin with a phishing email that directs the victim to a fake website. Once the victim enters their credentials, the scammers use AI chatbots to engage them further, offering investment opportunities or technical support.
典型的多階段詐騙可能從一封釣魚郵件開始，把受害者引導至假冒網站。當受害者輸入帳號密碼後，詐騙者又利用 AI 聊天機器人進一步進行互動，推銷投資機會或提供技術支援。
Deepfake videos or voice calls may be used to reinforce the legitimacy of the scheme, while fake reviews and social media activity create a sense of consensus and urgency.
還會用深偽影片或語音通話來加強詐騙計畫的可信度，同時配合假評論與社群互動營造共識與緊迫感。
These hybrid attacks are particularly effective because they exploit multiple vectors of trust simultaneously. Victims are not just tricked by a single tactic but are drawn into a web of deception that reinforces itself at every stage. The use of AI allows scammers to coordinate these efforts seamlessly, adapting their approach based on the victim's responses and behavior.
混合型詐騙特別有效，因為它同時攻擊多個信任的層面。受害人不只是被一招擊倒，而是整個過程不斷受到層層欺騙，引誘至更深的圈套。AI 則讓詐騙者可以無縫整合這一切，並根據受害者的反應與行為持續調整攻擊策略。
The scalability and adaptability of multi-stage scams make them a significant threat to the crypto ecosystem. Traditional security measures, which are often designed to address specific types of fraud, may be ineffective against these complex, evolving attacks.
多階段詐騙的可擴展性與適應力，使其對整個加密生態造成重大威脅。傳統的安全措施往往針對單一型態詐騙設計，對於這類複合型且持續演化的攻擊可能毫無防禦力。
As a result, platforms and users must adopt a more holistic approach to security, integrating advanced detection tools, continuous monitoring, and user education.
因此，平台與用戶必須採用更全面的安全策略，結合先進偵測工具、持續監控及用戶教育。
The rise of multi-stage and hybrid scams underscores the need for collaboration across the industry. Exchanges, wallet providers, and regulators must work together to share information, develop best practices, and respond quickly to emerging threats. Only by staying ahead of the curve can the crypto community hope to mitigate the risks posed by these sophisticated fraud schemes.
多階段與混合型詐騙的興起凸顯了產業跨界合作的重要性。交易所、錢包業者和監管機構必須攜手合作，分享情報、建立最佳實務、即時應對新興威脅。唯有領先趨勢，整個加密社群才能減少這些高端詐騙手法帶來的損失。
Final thoughts
The integration of AI into crypto fraud has fundamentally changed the threat landscape. Scams are now more convincing, scalable, and adaptive than ever before, leveraging deepfakes, automated phishing, synthetic identities, and multi-stage attacks to exploit trust and evade detection. The rapid pace of technological advancement means that new tactics are constantly emerging, challenging the ability of platforms and users to keep up.
AI 加入加密詐騙，徹底改變了威脅格局。現今的詐騙不僅更加逼真可疑、規模巨大，且極具彈性，結合深偽、釣魚自動化、合成身份與多階段攻擊手法，有效操縱信任並躲避偵查。科技發展一日千里，新型詐騙手法層出不窮，持續挑戰平台和用戶的防備能力。
For investors and industry participants, awareness is the first line of defense. Understanding how modern scams operate, recognizing the signs of AI-enhanced fraud, and maintaining a healthy skepticism toward unsolicited offers and endorsements are essential.
對投資人與產業參與者而言，保持警覺始終是第一道防線。瞭解現代詐騙的運作模式，辨識 AI 強化詐騙的徵兆，並對於任何主動上門的推銷或背書保持懷疑，都是不可或缺的自保之道。
Platforms must invest in advanced detection tools, robust verification processes, and continuous user education to stay ahead of the curve.
平台必須投資於先進偵測工具、嚴謹的驗證程序與持續的用戶教育，才能跟上發展步伐。
The battle against crypto fraud is an ongoing arms race, with scammers and defenders constantly adapting to new technologies and tactics. While AI has introduced unprecedented risks, it also offers new opportunities for defense, from automated threat detection to behavioral analysis.
對抗加密詐騙是一場持續不斷的軍備競賽，攻防雙方都在不斷運用新科技與新戰術。雖然 AI 帶來前所未有的風險，也同時提供偵測威脅與行為分析等防守新機會。
By embracing innovation and fostering collaboration, the crypto community can navigate this new era of fraud and build a more secure and trustworthy ecosystem for the future.
唯有擁抱創新與加強合作，整個加密生態圈才能在新的詐騙時代中立於不敗之地，並共創更安全、值得信賴的未來。