Ruishu Information

From Accessible to Controllable: Ruishu Information Launches AITM for AI Agent Lifecycle Security

As AI Agents become digital employees in enterprise R&D, office, and business workflows, organizations must now ensure they are manageable, controllable, and auditable. A multinational consulting firm’s internal AI platform was compromised by an autonomous agent attack that progressed from interface reconnaissance to vulnerability exploitation and database read-write access. Conventional scanners missed the injection points, but the agent inferred query structures from database error messages. Ruishu Information has responded with its Agent Intelligent Lifecycle Management system (AITM), which enforces security across admission, runtime, permissions, and data flows. The platform combines static scanning, behavioral analysis, semantic judgment, and sandbox execution for pre-deployment checks, followed by continuous runtime validation and LLM data-plane protection. AITM applies HMAC-SHA256 signatures, tool whitelists, PII tokenization, and four-stage Trace auditing to reduce blind spots throughout the agent lifecycle.

Ruishu Information Warns Machine Traffic Now Dominates Internet as AI Agents Surge

Ruishu Information has released its 2026 Automation Threat Report covering data from early 2025 through Q2 2026. The report shows bots accounting for 68 percent of total internet traffic, with malicious bots making up 55 percent of that volume. Human traffic has fallen to just 22 percent while AI Agent-driven requests have grown from under 1 percent to 8-12 percent. LLM and AI Agent requests have already exceeded 450 billion, marking more than 400 percent year-over-year growth. The report introduces a new classification of non-human traffic into traditional bots, AI-enhanced bots, and autonomous AI Agents, along with an L1-L5 threat framework. It also expands documented attack scenarios from nine to thirteen, adding LLM application attacks, agent supply-chain attacks, identity hijacking, and autonomous AI-orchestrated attacks.