AI agents reshape global cybersecurity landscape amid fast commercial adoption

The 14th Internet Security Conference has showcased the disruptive capability of autonomous AI agents, with a fully agent-generated animation short film completed within just five days. The entire production process, covering script writing, storyboard design, voice dubbing and final rendering, was accomplished without professional production teams or lengthy development cycles, vividly demonstrating the core theme of the event that AI agents are overturning traditional cybersecurity mechanisms.

Autonomous AI agents have evolved into core operational components across industrial scenarios. Industry consensus shared at the conference confirms 2025 as the inaugural year for large-scale commercial adoption of multi-agent technology, with broader industrial penetration set to take place throughout 2026. The technology has already been deployed in manufacturing, logistics and multiple real economy sectors, transforming from passive executive tools into independent entities with autonomous perception, decision-making, interaction and execution capabilities.

The rapid upgrade of agent operational capacity is accompanied by escalating cybersecurity risks. Automated AI attack systems have elevated network offence and defence from manual operation to machine-driven iteration, drastically improving attack efficiency and scalability. The US-developed Mythos model represents a new generation of intelligent offensive tools, capable of automated vulnerability mining and attack code generation.

Intelligent agent technology has boosted vulnerability detection speed by two orders of magnitude while cutting corresponding costs to less than one thousandth of traditional levels. The Mythos model has successfully identified long-concealed security flaws, including a 27-year-old vulnerability in the open-source OpenBSD kernel and a 16-year-old loophole in the global FFmpeg audio and video infrastructure. Such automated and high-efficiency offensive capabilities constitute powerful strategic deterrence in modern cyberspace.

Traditional cybersecurity balance established over the past three decades relies on the scarcity and high discovery cost of high-value network vulnerabilities. Intelligent agent technology has dismantled this conventional balance by enabling faster, cheaper and large-scale vulnerability mining. Future network competition will centre on response speed rather than basic technical superiority, highlighting the necessity of developing domestically controllable AI vulnerability mining systems.

Consumer-level cybersecurity threats have also evolved alongside intelligent agent iteration. Data leakage privacy inference, deepfake technology and scenario-based fraudulent activities have become prevalent cyber risks. Leaked private data is circulated on dark web platforms, while AI algorithms can reverse deduce sensitive personal information from model training outputs. Deep face-swapping and voice imitation technologies further enable sophisticated financial fraud, posing tangible threats to personal property safety. Zero-trust operational frameworks have been recognised as effective defensive approaches, requiring rigorous permission management and prohibition of sensitive data input into intelligent agents.

Traditional passive cybersecurity response models fail to cope with clustered and saturated AI agent attacks. Intelligent agent-driven cyber offensives feature autonomous decision-making, cluster collaboration and continuous iterative evolution. The global cybersecurity paradigm is shifting from passive threat elimination to active immune defence, building a full-lifecycle operational system covering prediction, prevention, detection, response and recovery.

Practical industrial solutions are emerging to match the evolving security demands. Integrated cybersecurity systems combining decades of accumulated offensive and defensive experience, security databases and vulnerability knowledge bases have been developed to form collaborative intelligent agent clusters. As of June 24, the independently developed intelligent vulnerability mining agent has discovered 3,432 vulnerabilities, with 105 officially verified by regulatory authorities and multiple high-risk flaws recorded in national vulnerability databases.

Automated defensive systems have been launched to realise intelligent cybersecurity operation, transforming traditional manual intervention mechanisms into autonomous machine-driven operation modes. Continuous optimisation of AI-powered security systems will further strengthen proactive defence capabilities, adapting to the iterative evolution of intelligent network attacks and consolidating systematic cybersecurity barriers for digital industrial development.