2025年XCon×HG议题：数字人安全攻防白皮书

Core Insights - The report titled "Digital Human Security Offensive and Defensive White Paper" highlights the rapid integration of digital humans into various sectors, including e-commerce and emotional companionship, while also exposing significant security threats associated with this technology [1][2]. Group 1: Industry Growth and Risks - The digital human industry is experiencing explosive growth, with applications expanding from live streaming to AI companions, but the white paper warns that if digital humans are hijacked, they could be used for fraud or manipulation [2][3]. - The technology stack of digital humans, which includes AI, NLP, and computer vision, presents a wide and hidden attack surface, where a single vulnerability could lead to systemic failure [2][3]. Group 2: Technical Architecture and Threats - The white paper outlines a four-layer technical architecture for digital humans, identifying risks at each level, including code injection and business logic vulnerabilities at the front end, signaling hijacking and protocol vulnerabilities in streaming, and data leaks and supply chain attacks at the infrastructure level [3][4]. - Specific attack vectors include prompt injection that can manipulate digital human behavior, DDoS attacks that incapacitate them, and TTS semantic disguise attacks that bypass content moderation [4][5]. Group 3: Compliance and Regulatory Challenges - The report emphasizes compliance risks, particularly the potential for deepfake technology to create highly realistic fraudulent digital humans, complicating the identification of genuine content and making accountability difficult in cases of infringement or fraud [5][6]. - The lack of a standardized "AI-generated" label for digital content further blurs the line between real and virtual, posing challenges to existing legal and regulatory frameworks [5][6]. Group 4: Defense Strategies - To address these threats, the white paper proposes a systematic defense strategy focused on protecting AI models and data assets, including supply chain safeguards, encryption of training data, and strict content filtering [6]. - It advocates for real-time content review mechanisms, the implementation of AI-generated content labels, and enhanced authentication and permission controls to protect user interactions [6].