Title: Addressing Internal AppSec Risks from No-Code AI Agents
AppSec teams have traditionally fortified external applications, APIs, and cloud infrastructures but now face new threats from internally built no-code AI agents. These agents operate autonomously across enterprise systems, pulling data and executing business logic without passing through standard software development life cycles (SDLC). Their dynamic behavior blurs the lines between internal and external risks, creating potential data breaches and security incidents. Traditional AppSec controls, which rely on static behavior reviews, prove ineffective against these agents’ runtime complexities. Security teams must adopt continuous discovery practices for constant visibility into agent interactions, preventing security incidents before they occur. By treating AI agents as production applications and ensuring behavioral monitoring, vulnerability assessments, and strict adherence to the principle of least privilege, organizations can better manage the amplified risks posed by these advanced assets. Proactive responses to agent-related failures must mirror those for external breaches to enhance overall security posture.
