Microsoft extends Project Perception with Dynamic Permissions and risk scoring to control rogue enterprise AI agents
Microsoft announced new controls to monitor and restrict potentially rogue AI agents in enterprise environments, arguing that organizations should treat agents as insiders rather than trusted software. The capabilities extend Project Perception, the agentic security system launched in July, which was initially pitched as a defense against external AI-driven attacks. Hayete Gallot warned that agents are frequently overprivileged, with access to data, tools and systems, and can act in critical processes. Nadim Abdo clarified that the insider label does not mean agents are malicious, but that they can make mistakes, be manipulated or be compromised. This is product news with no direct threat or incident attached.
Technical Details
- Dynamic Permissions: agents start with no or minimal permissions. Access is granted per task and expires or shrinks as the task changes or ends, and high-impact actions require human review.
- Dynamic Agent Risk: a continuously updated per-agent risk score built from agent activity plus identity, data, endpoint, cloud, network and runtime signals. It factors in security configuration, reachable resources, potential damage and deviation from intended behavior.
- Dynamic Conditional Access: brings Entra Conditional Access to agents. It can reduce permissions, allow read-only access, limit data and network reach, require human approval, or isolate the runtime or halt execution at high risk.
- Playbooks and Guardian Agents: humans set rules and approval limits, Playbooks define the desired security response, and Guardian Agents investigate risk shifts and suggest or enforce containment.
- Agent discovery expands by 35 local agent types, for a total of 60, including Claude Code, OpenAI Codex and GitHub Copilot.
Remediation
The article frames the guidance as least-privilege, per-task access for agents, continuous risk scoring, human approval for consequential actions, and containment of agents whose risk rises.
Linha do tempo
-
Microsoft extends Project Perception with Dynamic Permissions and risk scoring to control rogue enterprise AI agents
ler a análise desta fonte ocultar
Microsoft announced new controls to monitor and restrict potentially rogue AI agents in enterprise environments, arguing that organizations should treat agents as insiders rather than trusted software. The capabilities extend Project Perception, the agentic security system launched in July, which was initially pitched as a defense against external AI-driven attacks. Hayete Gallot warned that agents are frequently overprivileged, with access to data, tools and systems, and can act in critical processes. Nadim Abdo clarified that the insider label does not mean agents are malicious, but that they can make mistakes, be manipulated or be compromised. This is product news with no direct threat or incident attached.
Technical Details
- Dynamic Permissions: agents start with no or minimal permissions. Access is granted per task and expires or shrinks as the task changes or ends, and high-impact actions require human review.
- Dynamic Agent Risk: a continuously updated per-agent risk score built from agent activity plus identity, data, endpoint, cloud, network and runtime signals. It factors in security configuration, reachable resources, potential damage and deviation from intended behavior.
- Dynamic Conditional Access: brings Entra Conditional Access to agents. It can reduce permissions, allow read-only access, limit data and network reach, require human approval, or isolate the runtime or halt execution at high risk.
- Playbooks and Guardian Agents: humans set rules and approval limits, Playbooks define the desired security response, and Guardian Agents investigate risk shifts and suggest or enforce containment.
- Agent discovery expands by 35 local agent types, for a total of 60, including Claude Code, OpenAI Codex and GitHub Copilot.
Remediation
The article frames the guidance as least-privilege, per-task access for agents, continuous risk scoring, human approval for consequential actions, and containment of agents whose risk rises.