From User Logins to Agent Identities
As enterprises rebuild workflows around autonomous AI agents, identity access control can no longer focus only on human users. Agents now draft code, adjust cloud resources, and touch production data without a person in the loop, creating a new class of non‑human identities that must be governed just as tightly as employee accounts. Traditional approaches lean on shared API keys, inherited credentials, or long‑lived service tokens, which rarely align with what a specific task actually needs and are difficult to revoke quickly. This gap becomes dangerous when a misconfigured agent can exfiltrate confidential information or delete a database in seconds. The security problem is no longer just misuse by one operator but systemic failure across interconnected agents. To manage this risk, platforms are emerging that treat each AI agent as a first‑class identity with its own policy, lifecycle, and audit trail, separate from but coordinated with human identity management.
Keycard’s Scoped Access and Delegated Sessions
Keycard positions itself as an identity and access layer purpose‑built for AI agents, with its new Keycard for Multi‑Agent Apps extending that model across complex agent systems. Instead of giving agents broad, persistent credentials, developers can assign each agent its own verifiable identity and use delegated, session‑based access to scope permissions per task. When an agent starts, it receives identity through runtime attestation, avoiding long‑lived API keys or secrets on disk. When a user or another agent initiates work, Keycard issues a session that binds every downstream action back to the originating principal, enabling precise agent attribution logging. This means agents can operate with no standing privileges: they request only what they need for the current job, and access expires when the session ends. Early adopters report deploying agents against production systems in days, without requiring every engineer to become a security or identity specialist.
Idira: Unifying Human and Agentic Access Control
Palo Alto Networks’ Idira takes a broader platform approach, framing AI agent security as part of a single identity access control plane for humans, machines, and agents. Idira aggregates capabilities from CyberArk, Koi, and Portkey so security teams can see, in one place, which employees, service accounts, and autonomous AI agents exist and what each can do. CyberArk contributes privileged‑access management, defining when users or agents may receive elevated rights and how quickly those privileges are revoked. Koi maps less traditional AI assets such as plugins, scripts, and endpoint artifacts that often sit outside classic identity tools. Portkey brings AI‑agent governance, helping to monitor, route, and secure autonomous activity across applications. With Palo Alto reporting that 91% of surveyed organizations already run autonomous agents in production, the ability to grant temporary privileges, tighten revocation, and avoid dormant powerful accounts is becoming an operational necessity, not a future concern.
Why Attribution and Audit Trails Now Matter More
As agents take on higher‑impact tasks—like account creation, system configuration, or triggering production deployments—organizations face a critical question: who did what, and on whose authority? Shared credentials make this almost impossible to answer, undermining compliance and incident response. Both Keycard and Idira approach AI agent security with attribution at the center. By giving every agent a unique identity and binding actions to delegated sessions, teams can trace each API call, configuration change, or data access back to a specific agent and initiating user or process. This fine‑grained agent attribution logging supports forensics after an incident, but it also enables proactive governance: security teams can spot anomalous behavior by particular agents and adjust policies without disrupting others. In heavily regulated environments, provable audit trails for non‑human actors are becoming just as important as traditional user logs, especially as agents begin to operate with greater autonomy across critical systems.
Designing Permission Boundaries for Autonomous AI
The rise of scoped access agents is changing how architects think about authorization models. Instead of monolithic roles, emergent best practices focus on tightly bounded permissions tied to specific tasks or workflows. For example, an agent that drafts customer emails might only receive read access to CRM records during a short‑lived session, while a deployment agent could be allowed to promote builds but not modify security groups or database schemas. Platforms like Keycard enable this by delegating access on a per‑task basis with no standing privileges, and Idira brings similar concepts into a unified policy layer shared with human identities. Integration with existing tools such as CyberArk and Portkey lets organizations apply consistent standards across both human and autonomous AI permissions. The goal is not to slow agents down, but to ensure that when autonomy reaches into production, it does so inside carefully engineered, observable, and revocable boundaries.