68 CVEs Uncovered in MCP Servers as 91.8% Lack OAuth Authentication, Exposing AI Agent Tool Layers

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.

South Korean Hacker Uses Generative AI Framework ARTEX to Breach 90 Organizations and Steal 8.2 Million Records

Seoul Metropolitan Police arrested a 32-year-old man identified only as A for conducting a series of intrusions against approximately 90 South Korean companies and institutions between September 2025 and October 2026. The attacker, who had no formal technology education and learned hacking from publicly available online materials, previously worked in penetration testing at a security firm from 2019 to 2022. Roughly 60 of the victims were compromised using the generative AI-powered pentesting framework ARTEX, which autonomously determined attack paths after receiving only the target name. The operation resulted in the theft of 8.2 million personal records and internal documents, after which the perpetrator extorted 38 organizations for a total of 360 million won in Tether, ultimately receiving 300,000 won. Police recovered part of the stolen material and are investigating possible copies on the dark web, classifying the case as the country's first large-scale incident involving generative AI. Six additional suspects remain under investigation while the main perpetrator has been referred to prosecutors on charges of violating information and communications network laws and extortion.

AI in Vulnerability Management: Assistant, Weapon, and Emerging Target

Artificial intelligence now plays three simultaneous roles in vulnerability management: it assists defenders with prioritization and analysis, arms attackers with faster discovery tools, and introduces entirely new classes of assets and vulnerabilities that must be managed. Mature applications include ML-driven risk scoring in platforms such as Tenable VPR, Qualys TruRisk and Rapid7 Active Risk, which cut priority lists by 40-50 percent, and Google’s Big Sleep project that discovered a real-world SQLite flaw (CVE-2025-6965) before exploitation occurred. On the offensive side, systems like XBOW completed 104 test scenarios in 28 minutes versus 40 hours for human testers, shrinking the average time-to-exploit window to negative seven days according to Mandiant M-Trends 2025. New AI-specific attack surfaces are documented in the OWASP Top 10 for LLM applications and the emerging MCP Top 10, covering prompt injection, tool poisoning, and command injection against Model Context Protocol servers. Real incidents already include Air Canada’s chatbot inventing a refund policy and New York City’s MyCity bot dispensing illegal advice for nearly two years. Researchers have also demonstrated sandbox escapes in coding agents from Cursor, OpenAI Codex and Claude Code through classic file-write-and-execute patterns rather than any sentient behavior.