Core Viewpoint - The article emphasizes the transformative role of AI in the security industry, particularly through the introduction of intelligent agents that enhance efficiency and reduce reliance on human resources in security operations [2][4][8]. Group 1: AI and Security - AI can serve as both a weapon and a shield in addressing security challenges, with large models being crucial for vertical applications in the security sector [2][3]. - The concept of "Security as a Service" was introduced by 360 in 2023, aiming to productize security services and address the inefficiencies of traditional security methods [7][10]. - The evolution from large models to intelligent agents is seen as essential, as these agents can autonomously understand tasks, plan, and deliver results, significantly improving operational efficiency [8][9]. Group 2: Intelligent Agents - 360 Security Cloud has launched three types of intelligent agents: Security Agent, Management Agent, and Employee Agent, which enhance various aspects of security operations [13][14]. - The Security Agent can autonomously handle threat detection, response, and reporting, achieving a threefold increase in threat discovery speed compared to manual processes [15][16]. - The Management Agent focuses on internal data security and compliance, while the Employee Agent streamlines business processes across various functions [16]. Group 3: Data and Standardization - 360 Security Cloud possesses over 2 exabytes of security data, which supports the intelligent agents and enhances their accuracy in threat detection [10][20]. - The company is implementing standardization across its services to facilitate easier integration for partners, allowing them to quickly adopt and benefit from 360's capabilities [19][21]. - The shared data and expertise from 360 Security Cloud enable partners to enhance their security operations and reduce costs significantly [20][22]. Group 4: Market Impact - The adoption of AI-driven security solutions is expected to democratize access to advanced security capabilities, allowing more businesses to benefit from robust security measures [22]. - The company aims to expand its national-level security capabilities to various industries, promoting a safer digital transformation for enterprises [22].

Group 1 - The integration of artificial intelligence (AI) technology, particularly large models, is accelerating global digitalization while also increasing network threats, necessitating the fusion of AI and digital security for effective digital economy development [1] - Large models exhibit strong general capabilities but face challenges in specialized applications due to insufficient professional knowledge and limited adaptability, requiring collaboration between AI providers and industry leaders to create high-quality professional datasets [1][2] - There is a call for innovative models like "industry large model as a service" to lower application barriers, enabling small and medium enterprises to access customized AI capabilities affordably [1] Group 2 - A fundamental transformation of digital security systems is needed, shifting from passive to proactive immune models driven by AI, utilizing large models for threat hunting, anomaly detection, and automated responses [2] - The theme of the conference emphasizes the strategic value of integrating AI with cybersecurity, highlighting the necessity for collaborative efforts across sectors to address global challenges [2] - The evolution from large models to intelligent agents is essential for enhancing productivity, as intelligent agents can understand goals, plan tasks, and utilize tools effectively [3] Group 3 - The emergence of "intelligent agent hackers" poses a new challenge in cybersecurity, where a single hacker can control multiple agents to launch automated attacks, increasing the risk of cyber warfare [3] - 360 Group is developing security intelligent agents based on large security models to enhance cybersecurity capabilities, aiming to replicate the skills of human security experts [3][4] - The company emphasizes the dual focus on "security + AI" to protect the digital era while defining the future through AI advancements [4]

Core Viewpoint - The rapid development of artificial intelligence (AI) technology poses both risks and opportunities for cybersecurity, with the emergence of "super hackers" being a significant concern. The solution lies in effectively utilizing intelligent agents to enhance security measures and response capabilities [1][2][3]. Group 1: AI and Cybersecurity Challenges - Intelligent agents are AI entities capable of perceiving their environment, making autonomous decisions, and executing actions, which can significantly impact cybersecurity [2]. - The rise of AI has led to an increase in complex and covert cyberattack methods, highlighting the need for improved cybersecurity measures and response capabilities [2][3]. - The current global digital technology landscape is uneven, with some regions lacking robust digital infrastructure, making them more vulnerable to cyberattacks [2]. Group 2: Evolution of Intelligent Agents - Intelligent agents are evolving through various levels, with L1 being basic chat assistants and L5 potentially being self-evolving superintelligent agents [6][7][8]. - The transition from traditional AI models to intelligent agents is crucial for addressing the limitations of current AI applications, particularly in operational tasks [4][6]. - Intelligent agents can enhance operational efficiency by acting as digital counterparts to human experts, thereby addressing talent shortages in cybersecurity [4][5]. Group 3: Future Directions and Collaboration - There is a pressing need for international collaboration on AI ethics, data sharing, and cybersecurity standards to effectively combat new security threats [3][4]. - The future of human-AI interaction is expected to shift towards collaboration with intelligent agents, which will take on routine tasks, allowing humans to focus on higher-level management and oversight [6][7]. - The management of intelligent agents will require new strategies to handle their coordination and ensure effective task execution [10][11].

Core Viewpoint - The ISC.AI 2025 conference emphasizes the transition from large models to intelligent agents, highlighting their potential to revolutionize the AI industry and improve business operations [3][4][5]. Group 1: Conference Highlights - The theme of ISC.AI 2025 is "All in Agent," indicating a focus on intelligent agents as the next direction for the AI industry [4]. - Zhou Hongyi, founder of 360, stresses that intelligent agents can replace traditional business processes and are essential for countering automated attacks from hackers using multiple agents [4][6]. - The conference showcased the advancements in intelligent agents, which are seen as more effective than large models in practical applications [5][6]. Group 2: Intelligent Agents Development - Intelligent agents are categorized into four levels: L1 (chat assistants), L2 (low-code workflow agents), L3 (reasoning agents), and L4 (multi-agent swarms) [7]. - The current capabilities of intelligent agents allow them to perform tasks with greater efficiency compared to human efforts, such as threat detection and incident management [6][7]. - Zhou notes that while intelligent agents are powerful, they require deep industry knowledge to be effective, and a universal agent is currently unattainable [6][7]. Group 3: Industry Challenges and Future Directions - The emergence of "intelligent agent hackers" poses a new challenge, as they can automate attacks, increasing the risk of cyber warfare [7]. - The integration of AI technology with digital security is crucial, with a focus on collaborative model development and proactive immune systems [7].

Core Insights - The 13th Internet Security Conference (ISC.AI 2025) in Beijing focused on digital security and artificial intelligence, emphasizing the transition to an era driven by intelligent agents [1] - The founder of 360, Zhou Hongyi, highlighted two main pain points in the application of large models: insufficient reasoning ability and lack of independent operational capability, with the latter still unresolved [1][3] - The evolution from large models to intelligent agents is deemed necessary for AI to become a productive tool rather than a mere toy [1][3] Intelligent Agent Evolution Path - L1: Chat assistants are basic tools for suggestions and emotional support, categorized as "toy-level" intelligent agents, such as GPTs [3] - L2: Low-code workflow agents have evolved into tools that require human setup for task execution, enhancing productivity [3] - L3: Reasoning agents can autonomously plan and complete tasks, akin to specialized employees, but face limitations in cross-domain collaboration [3] - L4: Multi-agent swarms represent a revolutionary breakthrough, allowing multiple expert agents to collaborate flexibly, achieving high task success rates [3][4] Nano AI and Collaboration - Nano AI employs a unique "multi-agent swarm collaboration space" technology, enabling memory sharing among agents and efficient task execution [4] - The platform has gathered over 50,000 L3 agents, allowing users to create their own "Manus" through natural language [4] - The efficiency of complex tasks has drastically improved, reducing completion time from 2 hours to 20 minutes for tasks like generating a 10-minute movie [4] Intelligent Agent Factory and Security Implications - 360 Group launched the "Intelligent Agent Factory," enabling enterprises to customize L3 agents without programming knowledge [6] - The emergence of "intelligent agent hackers" poses new challenges in cybersecurity, as individual hackers can control multiple agents for automated attacks [6] - 360's security intelligent agents aim to replicate the capabilities of human security experts, marking a qualitative breakthrough in security [6] Strategic Vision - Zhou Hongyi emphasized that security is the foundation of digitalization, while AI represents its pinnacle, with 360 committed to a dual development strategy of "security + AI" [6]

Group 1: AI and Cybersecurity Risks - AI has introduced greater risks to enterprise cybersecurity, with 57% of privacy and data security issues and 55% of AI-driven cyberattacks being attributed to generative AI cloud security concerns, yet only 7% of IT decision-makers believe there are no related security risks [2] - The complexity of attack methods has increased, with attackers leveraging a larger internet exposure as an entry point, utilizing AI capabilities for social engineering phishing attacks and supply chain attacks, leading to full-chain attacks [3] - Gartner predicts that by 2025, the adoption of generative AI will increase the need for cybersecurity resources in enterprises, resulting in a more than 15% rise in application and data security spending [3] Group 2: API Security Concerns - In the past year, China spent the highest cost on resolving API security incidents, amounting to $778,000 (approximately 5.68 million RMB), with a total of 108 billion API attacks recorded in the Asia-Pacific region from January 2023 to June 2024, accounting for 15% of all web attacks [4] - Over 60% of web attack traffic is focused on API interfaces, with attack volume increasing by 23% year-on-year, driven by the new threat exposure brought by the large-scale implementation of generative AI technology [4] - Common API vulnerabilities include misconfigurations, network firewalls not intercepting, and authorization flaws, with API misconfiguration being the most prevalent at 22.3% [5] Group 3: Web Security Trends - Web vulnerability exploitation attacks are expected to increase by 68% in 2024, with a significant rise in attacks targeting AI application vulnerabilities [6] - The concept of using AI to combat AI is gaining traction, with security service providers launching corresponding large model services to enhance threat detection and response capabilities [7][8] - The evolution of web security defense has shifted from static rule-based defenses to dynamic game-theoretic defenses, with AI becoming the central component of security systems [9] Group 4: Systematic Defense Strategies - Enterprises are moving towards a systematic defense approach, integrating various security tools into a cohesive defense mechanism, breaking down data silos and policy fragmentation [11] - For API security, companies need to establish a comprehensive API security strategy, including continuous discovery of vulnerabilities, threat management systems, and proactive testing [12] - The demand for security operations is driving the development of security service providers, focusing on asset, vulnerability, threat, intelligence, and security policy operations [13]

Group 1 - The establishment of a quantifiable evaluation system in cybersecurity is essential, emphasizing the integration of AI to drive innovation and high-quality industry development [1][2] - The development of AI agents is categorized into three levels: conditionally autonomous, highly autonomous, and fully autonomous, with a focus on proactive defense and collaborative intelligence sharing [1][2] - The transition from static to dynamic data security is necessary, requiring a deeper understanding of data, business, and behavioral intentions, with security AI agents being the key solution [2][3] Group 2 - The brain-computer interface industry is at a critical stage of technological breakthroughs and regulatory framework development, recognized as a national strategic sector [3] - The conference highlighted significant achievements in data factor marketization, key technological innovations, and industry applications, showcasing the leadership and innovation of Hangzhou High-tech Zone in the digital economy [3][4] - The release of the "Security AI Agent Cube: Maturity Model Evaluation Research Report" introduces a multidimensional maturity assessment framework for security AI agents, aiming to enhance AI applications towards being "trustworthy and controllable" [3]