Uploaded August 2026 | Updated September 2026, 2 weeks ago
Traditional automation generally stops when a permission or policy blocks an action. An agentic system may instead interpret that restriction as an obstacle and search for another way forward.
That changes the security model. An agent pursuing a legitimate goal could discover an unexpected or unauthorized path to reach it. The example discussed here involves an agent attempting to create a custom application to access a restricted file.
When an AI agent is rewarded for accomplishing a goal, how do you ensure the restrictions around that goal remain actual boundaries rather than problems the agent tries to solve?
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#AgenticAI #AISecurity #RewardHacking #SecurityWeekly #Cybersecurity #InformationSecurity #AI #InfoSec
Traditional automation generally stops when a permission or policy blocks an action. An agentic system may instead interpret that restriction as an obstacle and search for another way forward.
That changes the security model. An agent pursuing a legitimate goal could discover an unexpected or unauthorized path to reach it. The example discussed here involves an agent attempting to create a custom application to access a restricted file.
When an AI agent is rewarded for accomplishing a goal, how do you ensure the restrictions around that goal remain actual boundaries rather than problems the agent tries to solve?
Subscribe to our podcasts: securityweekly.com/subscribe
#AgenticAI #AISecurity #RewardHacking #SecurityWeekly #Cybersecurity #InformationSecurity #AI #InfoSec
