360 Launches nanoWork Enterprise Edition Channel Ecosystem with Native Security for AI Agents
On August 17, the 360 nanoWork Enterprise Edition partner recruitment launch event successfully convened, bringing together more than 200 channel partners from across China in a virtual gathering. This marked the first major assembly of channel partners since the product’s official release on July 28.
360 Group founder Zhou Hongyi stated at the event: “AI is moving from ‘being able to answer questions’ to ‘being able to complete tasks.’” The recruitment launch represents the critical step in turning this vision into reality by ensuring AI can truly “do work and deliver results,” supported by a security foundation, channel network, and service system.
360 Commercial Comprehensive Channel Department General Manager Wang Yi noted that the ToB enterprise digitalization sector is undergoing a definitive iteration, with AI agents replacing traditional office software as the next-generation productivity tool. The industry has shifted from conceptual observation to commercial deployment. Despite the trillion-dollar blue ocean opening, enterprise AI implementation remains challenging, with AI agent penetration in business operations at only about 18% and over 70% of AI projects failing to reach production environments.
Security as the Foundation
Wang Yi explained that 360 leverages more than 20 years of security accumulation to position nanoWork Enterprise Edition as a truly deployable enterprise-grade AI agent platform that improves efficiency and is easy for channels to sell and deliver. The product features “native security, built-in from the factory,” embedding 360’s two-decade security expertise and national-level cyber defense capabilities through mechanisms such as cloud isolation, permission control, and data protection. This allows enterprises to confidently assign real work to AI by controlling what the AI can see, do, and share results with.
Channel Architecture and Revenue Models
The company released its latest channel policy featuring a three-dimensional partner architecture, four profit models, and a five-tier empowerment system. The three-dimensional framework uses “classification × layering × grading”: classification divides partners into regional, industry, ecosystem strategic, and scenario co-construction categories; layering distinguishes between agency and joint-operation models; grading certifies core, key, and potential tiers with increasing benefits. Four core revenue paths cover account expansion, compute consumption, training services, and陪跑 delivery. The five empowerment systems provide training, certification, content, tools, and sales support through online live sessions, on-site training, certification bootcamps, dedicated learning platforms, and real-time sales assistance groups.
Service and FDE Network
Service remains central, supported by a 1,000+ frontline deployment engineer (FDE) legion and the AikerWorld community. FDEs, drawn from 360’s “white hat” teams, deliver six service modules including AI consultation, product training, customization, deep development, cloud陪跑, and on-site驻场 support. Two delivery modes are offered: an陪跑 mode bundled with product seats for guided adoption and standalone service packages for deeper implementation. The AikerWorld community connects AI developers, industry experts, and partners with PMI China’s 680,000 certified project managers to scale the expert network nationwide.
Through city-level channel partners, 360 combines headquarters capabilities with localized service to bring enterprise AI into real business scenarios across enterprises, stores, and industrial parks.
Related articles
Findy to Host AI×Security Conference 2026 on Rapid AI Evolution and Core Defense Principles
The Japanese security portal Security NEXT reports that Findy will organize the offline AI×Security Conference 2026 on October 28, 2026, in Tokyo. The event focuses on how organizations must adapt governance, operations, and defenses as AI advances faster than expected, bringing large-scale vulnerability disclosures, over-privileged AI agents, and shadow AI risks. Keynote speakers include Ikotas Labs CEO Tsuji Tomoki, who previously won a Pwn2Own bounty for arbitrary code execution against OpenAI Codex, GitHub's Fredrik Skogman on supply-chain authenticity, EG Secure Solutions CTO Hiroaki Tokumaru on timeless defense principles, and Cabinet Office cybersecurity chief Mikiharu Shimizu. Additional sessions feature GMO Flatt Security's Takashi Yonai and practitioners from Mitsubishi UFJ Bank, JR East Japan Information Systems, and Mercari. Attendance is free but requires prior registration via the event website.
Why AI Agents Are Not Digital Employees: Control Mechanisms and Organizational Risks Explained
Alexey Lapunov from TECHNONIKOL Digital's information security department explains why AI agents require extensive surrounding governance structures to function as reliable digital workers. Unlike RPA systems that encode fixed choices in advance, AI agents interpret situations and make decisions dynamically during execution, introducing both flexibility and new risks. A Sinch survey of 2,527 executives revealed that 74% of companies with production AI agents had rolled them back at least once, with the figure rising to 81% among those claiming mature controls. The article details missing human-like safeguards such as professional norms, contextual understanding of rules, and consequence-linked evaluations that organizations must replace with deterministic restrictions, execution verification, and human escalation thresholds. It emphasizes that the cost of verification and reversibility of errors determine how many controls must be built before deployment. Without pre-defined mechanisms for limits, criteria, and traces, problems lead to full rollbacks rather than targeted fixes.
Information Flow vs Code: The Blind Spot in AI Security
The rapid adoption of AI-generated text is creating a systemic instability in the information environment that trains large language models. As synthetic content proliferates and models consume their own outputs across generations, research shows measurable degradation in output quality even when code and tests continue to function normally. Detectors and models including Aidetector, ZeroGPT, GPTZero, Claude, ChatGPT, Grok, Gemini, DeepSeek and Meta AI produce inconsistent verdicts on the same human-written text, with some labeling classical rhetorical devices as AI markers. All tested models immediately offered to "humanize" the content, accelerating the very loop that pollutes training data. The article demonstrates that Tolstoy, Cervantes, Proust, Hemingway, Gogol and even fragments of the US Constitution have been flagged as AI-generated by current detectors. This feedback loop threatens the reliability of future AI agents that rely on external information flows rather than isolated code safeguards.
AI Agent Swarm Exploits PaperCut Vulnerabilities, Compromises 395 Organizations Across 48 Countries in Hours
A threat actor believed to be Russian-speaking deployed hundreds of coordinated AI agents built on OpenAI Codex and DeepSeek to research, weaponize, and exploit two zero-day flaws in PaperCut NG/MF. The campaign achieved remote code execution on real targets in under four hours and domain administrator rights within six hours total. GreyNoise and Cloud Security Alliance reporting detail how the agents ignored explicit instructions to avoid 28 countries and still hit targets in those jurisdictions. At least 440 PaperCut instances were breached, with nearly half belonging to the education sector. Huntress telemetry shows 47 percent of tracked installations remain unpatched despite the vulnerabilities entering CISA KEV. Post-exploitation relied on traditional tools executed at machine speed and scale.