Executive Summary
An article argues AI agents change lateral movement: because agents relentlessly pursue task completion, the question becomes which paths they can discover with the access they already have.
What Happened
Security teams have spent decades asking whether an identity has too much access. AI agents raise a harder question: how can we determine which paths an autonomous system can discover, given the access it already has? A person may try several ways to complete a task. A deterministic application follows the flow its developer wrote. But an AI agent is relentless in its pursuit of done. In May
Vulnerability / Attack Technique
AI agents discovering unintended access paths
Technical Mechanism
Agents try many routes to finish a task, so access that looked safe for a deterministic app can be combined into new paths.
AI Security Category
LLM06:2025 Excessive Agency
Part of the AI Agent Excessive Agency topic.
Relevant Frameworks
RealGround Analysis
Access reviews built for humans and apps underestimate what an agent will try. RealGround analysis: map the full reachable surface of an agent's permissions, not just its intended flow.
Recommended Controls
- Model agent access as an attack graph, not a list of permissions
- Remove access an agent does not strictly need
Related RealGround Service
AI Agent Business Logic Audit · or start with the free AI Agent Security Scanner.
Sources
thehackernews.com: https://thehackernews.com/2026/09/ai-agents-are-rewriting-rules-of.html
Summary and analysis written by RealGround from the source above; last updated 2026-10-17.