Full Summary
This Tuesday morning, July 21st, multiple reports confirm that while organizations are rapidly adopting AI technologies, security measures are critically lagging. Radware's 2026 Cyber Survey, highlighted by Quiver Quantitative, reveals 83% of organizations use generative AI or large language models, but only 17% have complete visibility over these processes. This oversight is creating new vulnerabilities and blind spots, as Security Info Watch details, with AI agents operating within legitimate workflows and bypassing traditional security tools. Help Net Security further emphasizes this growing risk, noting that AI agents are increasingly logging into company systems, often indistinguishable from human users. This trend, tracked across over 20,000 organizations, scatters credentials and expands security exposure. White hat hacker Park Chan-am, CEO of Steelion, warns that AI significantly speeds up cyberattacks, reducing vulnerability discovery from weeks to less than a day, making all internal software a critical target. The threats are becoming more sophisticated. Cybersecurity Insiders reports a new ransomware family, JadePuffer, specifically targeting AI models and machine learning environments, with destructive wiping capabilities. Fox Business is also monitoring national security concerns around China's Kimi K3 AI model. In response, companies are scrambling to adapt. Fasoo AI is expanding its AI Security Posture Management to secure enterprise data used by AI, ensuring accuracy and protecting sensitive information. Infobip reports that Asia Pacific businesses are rapidly increasing their use of AI to fight fraud, with AI-powered detection growing 71% year-on-year. GitLab 19.2 is introducing new agentic automation to tackle security backlogs, helping manage the increased code volume from AI-assisted coding. Even Cisco is launching Antares, a new family of smaller language models designed to find security flaws more cost-effectively and keep sensitive code local. This means your organization's data and systems are facing faster, more sophisticated AI-driven threats, while existing security tools may not be equipped to detect them.