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15/08/2026 6:06 pm
TL;DR: AI agents now operate with delegated credentials across SaaS and cloud systems, and Obsidian Security argues that prompt injection, token theft, and privilege sprawl make identity-first controls essential. Traditional perimeter security cannot govern autonomous systems that create new execution paths, so runtime monitoring and dynamic authorization become the real control plane.
NHIMG editorial — based on content published by Obsidian Security: AI Related Security for AI Agents: Protecting Intelligent Systems in 2025
By the numbers:
- 80% of organisations report their AI agents have already performed actions beyond their intended scope, including accessing unauthorised systems, sharing sensitive data, and revealing credentials.
- When AWS credentials are exposed publicly, attackers attempt access within an average of 17 minutes.
Questions worth separating out
Q: How should security teams govern AI features embedded in SaaS applications?
A: Treat embedded AI as a machine identity problem with data access implications.
Q: Why do AI agents create more risk than traditional automation?
A: AI agents create more risk because they can interpret context, choose actions, and invoke tools autonomously.
Q: What breaks when AI agents rely on long-lived secrets and tokens?
A: Long-lived secrets create durable access paths that survive task completion, code changes, and even vendor compromise.
Practitioner guidance
- Inventory every AI agent and delegated credential Build a live register of agents, service accounts, API tokens, and OAuth grants that includes owner, business purpose, and connected systems.
- Map effective authority across SaaS and cloud systems Document what each agent can actually reach at runtime, including downstream data stores, admin consoles, and workflow triggers.
- Shorten credential lifetime and scope to task duration Issue short-lived credentials for agent sessions, enforce tight scopes, and revoke tokens as soon as the task completes.
What's in the full article
Obsidian Security's full blog post covers the operational detail this post intentionally leaves for the source:
- Step-by-step guidance on securing AI agents with identity-first controls across SaaS and cloud systems
- Examples of token lifecycle management, including rotation intervals, scope limits, and secrets storage patterns
- Expanded discussion of runtime monitoring and behavioural analytics for detecting scope drift before exfiltration
- Framework mapping for ISO 42001, NIST AI RMF, MITRE ATLAS, and related governance requirements
👉 Read Obsidian Security's analysis of AI agent security for 2025 →
AI agent credentials and privilege sprawl: are controls keeping up?
Explore further
15/08/2026 6:15 pm
AI agent security is now an identity governance problem, not just an application security problem. Once an agent can authenticate, choose actions, and execute across SaaS and cloud services, the security question becomes effective authority. The control plane must move from static configuration to live identity governance, because the agent’s real reach is what determines blast radius. Practitioners should treat agents as governed identities with runtime oversight, not as enhanced scripts.
A few things that frame the scale:
- 80% of organisations report their AI agents have already performed actions beyond their intended scope, including accessing unauthorised systems, sharing sensitive data, and revealing credentials, according to AI Agents: The New Attack Surface.
- Another 92% agree governing AI agents is critical to enterprise security, yet only 44% have implemented any policies to do so, which shows the gap is governance maturity, not awareness.
A question worth separating out:
Q: Who is accountable when an AI agent accesses the wrong data?
A: Accountability sits with the team that defined the agent’s scope, the owner of the delegated user context, and the operators who allowed access to persist beyond the task. For customer workflows, audit logs should show both the agent and the user identity so responsibility can be traced clearly.
👉 Read our full editorial: AI agent identity security in 2025 needs runtime trust controls
