September 2026 Summaries

No summary generated yet.

No summary generated yet.

Arcade.dev presents an AI agent governance approach centered on a runtime control plane that evaluates and can deny every tool call before it reaches downstream systems. Its model uses delegated authorization, limiting an agent’s authority to the intersection of the individual user’s permissions and the agent’s predefined scope, rather than relying on broad service accounts or unrestricted inherited access. The text cites the 2025 ForcedLeak vulnerability in Salesforce Agentforce as an example of how prompt injection can exploit agents with standing permissions, arguing that delegated access reduces the potential impact even if an injection succeeds. Policies such as data-loss prevention, PII redaction, egress controls, rate limits, and limits on high-impact actions are enforced centrally and inline at runtime, while credentials remain isolated from models. The platform is designed to integrate with existing identity, compliance, logging, and SIEM tools, provide inventories and reusable registries for approved agents and integrations, and create real-time, attributed, replayable audit records for every action.