AI agent risk isn't real-time blocking, it's keeping permissions updated
Developers building AI agents are pointing out a core flaw in how agent security is handled today: treating an agent's permissions as a fixed, one-time setup. keep changing after deployment. They get granted new tools, connect to new APIs, and start pulling from new servers, gaining abilities they didn't have on day one.
Standard permission systems don't keep pace with this drift. Right now, keeping an agent secure is largely a manual, human-driven process: someone has to remember to go back in, update permissions, re-review approval workflows, think through new risks, and keep everything in sync. The real bottleneck may not be blocking bad actions in real time, but keeping the whole governance setup current as the agent evolves.
One proposed fix is an SDK that continuously watches an agent to track what it can do today versus last week, exactly which tools or have changed, and what new risks have shown up as a result.
Key points
- keep gaining new abilities after deployment via new tools, APIs, and MCP connections
- Standard governance frameworks are static and don't adapt to this ongoing change
- Keeping agents secure today is mostly a manual, human-dependent process
- The real bottleneck may be , not runtime enforcement
- One idea: an SDK that continuously tracks how an agent's change over time