Secure AI agents with continuous identity and runtime control
AI agents operate continuously, at scale, without natural checkpoints. Your security needs to do the same.
Autonomy without guardrails
AI agents request access, assume roles, and generate credentials as they work, and as they scale, access paths multiply, privileges accumulate, and secrets sprawl — often without explicit approval.
Four critical gaps in agentic AI security
Traditional IAM was built for humans. AI agents create control gaps that expose sensitive data at machine speed.
- Ungoverned persistent accessAgents often rely on standing credentials with no verification at the point of use. If behavior changes, access persists — and risk compounds before it’s detected.
- Privilege escalation without reviewAgents request access, invoke tools, and assume roles dynamically — accumulating privileges that were never explicitly granted or approved by any human.
- No attribution, no accountabilityAgents inherit the identity of the user they act on behalf of, making their actions indistinguishable from a human's. When something goes wrong, there's no clear record of what happened, or why.
- Fragmented controls, compounding risk Secrets, access, and identity are managed across disconnected tools. The gaps between them leave credentials exposed and policies inconsistently enforced.
Security and governance for agentic AI
HashiCorp and IBM's Security Lifecycle Management (SLM) portfolio apply the tried and true principles of zero trust to identity governance, least privilege, dynamic credentials and auditability to humans, machines and AI agents from creation to decommission.
Securing agentic AI requires a shift from static trust to continuous, runtime enforcement
- Give every agent a unique identity
Every agent gets a verifiable identity at deployment and is tracked across on-premises, cloud, and hybrid environments.
- Grant least privilege access, automatically
Agents are prevented from unfettered movement throughout the network and only receive dynamic, just-in-time access scoped to the task at hand. Access expires automatically when the task is completed.
- Enforce policy at the point of action
Authorization is verified at every API call and tool invocation — not assumed from a prior session. Runtime policy enforcement ensures access matches actual usage.
- Connect every agent action to a human decision
Every action an agent takes is traceable to the person who initiated it or owns the automation. Autonomous does not mean unaccountable. Audit logs provide a clear chain from human intent to agent action.
- Detect exposed secrets before they reach production
Continuously scan repositories, pipelines, and collaboration tools for hardcoded credentials and leaked secrets. Identify and remediate risk before it enters your environment.
- Stay audit-ready at any point in time
Tamper-proof logs capture the full identity and access lifecycle across every agent, workload, and environment. Compliance reporting is built in — not bolted on.
Govern every agent without slowing your business down
Securing agentic AI isn't just about closing risk — it's about building the foundation your organization needs to scale AI with confidence.
- Reduce risk
Dynamic, short-lived credentials and runtime policy enforcement eliminate the persistent access and credential sprawl that make agentic environments difficult to secure.
- Move faster
Automated identity provisioning and just-in-time access mean agents get what they need, when they need it — without manual overhead slowing down your teams.
- Stay in control
Full attribution from human intent to agent action gives security and compliance teams a clear, auditable record of every decision made across your environment.
- Scale with confidence
A unified control plane for secrets, access, and identity grows with your agent footprint — across on-premises, cloud, and hybrid environments — without adding operational complexity.
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What is agentic runtime security?
Engineers are being tasked to build AI, but they're not identity experts. Field CTO Tyler Lynch explains how agentic runtime security, dynamic credentials, OAuth2, and IDP flows protect AI agents from risks like prompt injection. Learn how to secure non‑human identities and cloud workloads.
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