Enterprises did not plan for agent sprawl. They planned for AI use cases, and the sprawl arrived as a side effect of shipping those use cases quickly. Development teams provisioned service accounts because proper identity setup felt like friction. OAuth scopes got over-provisioned because the demo needed to work before the sprint ended. Nobody wrote a revocation policy because the first priority was getting the agent to function at all.
The result is a class of identity risk that has no precedent in enterprise security. Gartner named agentic AI the top technology trend of 2025 and projects that 33% of enterprise applications will include agentic AI by 2028, up from less than 1% in 2024. Organizations are expected to have 50x to 80x more agents than human users in their environments within that same window.
Each one of those agents carries credentials, scopes, and access paths into databases, APIs, and internal services. These agentic tokens are already exposed in the wild, surfacing across Jira tickets, Teams messages, Confluence pages, and code commits. This is an active exposure, not a future risk, that most security teams lack the tooling to even quantify.
Agentic sprawl, or agent sprawl, describes the uncontrolled proliferation of AI agents, their associated credentials, and their accumulated access rights across an enterprise environment. The term borrows from “tool sprawl” and “secret sprawl,” both of which are familiar problems for platform and security teams. But agent sprawl compounds both simultaneously.
When a development team builds an AI agent to automate a procurement workflow, that agent receives API keys, OAuth tokens, and service account credentials to interact with the systems it touches. When a second team builds an agent for HR automation, the same pattern repeats, often without coordination with the identity or security team. When a third team reuses an existing service account because creating a new one takes too long, the blast radius of that account expands silently.
Privilege drift sets in at this stage. In Human IAM, privilege drift occurs slowly as roles expand through job changes and organizational restructuring. With agents, it happens at development speed. No single overprovision looks alarming, but the aggregate exposure is what creates catastrophic risk. Consider that many agents are shared across more than one application, and are not rotated within recommended time frames. Also, a significant number of former employee tokens remain active long after the access should have been terminated. Any one of these conditions is a governance failure. All three occurring simultaneously, across hundreds of agents, represents a structural breakdown.
Static IAM tooling was designed around a specific assumption: that identities are persistent, that roles change slowly, and that access policies can be reviewed and updated on a human schedule. Agents invalidate every part of that assumption.
Agents do not follow fixed workflows. They reason, adapt, and make decisions at runtime. What any given agent will need to access during a specific task is not always knowable in advance. Designing least-privilege access up front for a system that reasons and plans at execution time requires a level of prediction that is not realistic in practice. That design gap leads to overpermissioning, which becomes drift, which becomes standing privileges that apply across all contexts regardless of task, time, or risk level.
Standing privileges in agentic systems create a containment problem with no manual solution. Long-lived tokens issued to agents remain valid for hours or days, giving attackers a substantial exploitation window when those tokens are compromised or leaked. When agents bypass sanctioned access paths, as happens when a developer builds a shortcut connector to avoid governance overhead, audit trails disappear entirely. MCP bypass means losing intent, losing policy enforcement, and losing the ability to detect when an agent is operating outside its authorized scope.
Governing an agentic environment requires enforcing policy at the layer where agents actually operate: at runtime, against ephemeral credentials, with scope clearly defined to the specific task being executed. This is the core principle behind Zero Standing Privileges, and it applies to agents more forcefully than to any other identity class.
Agents should never hold standing access. Every access grant should be token-bound to a specific task, a specific tool invocation, and the authority of whoever initiated the request. When the task completes, the token expires automatically. No revocation workflow is needed because there is nothing persistent to revoke. Privilege drift becomes structurally impossible when there is nothing to drift.
Cryptographically verifiable agent identity is the prerequisite for this model. OAuth Dynamic Client Registration (DCR), PKCE flows, and SPIFFE/SVID certificates ensure that only known, registered agents can authenticate, and only through sanctioned access paths. Identity-aware proxies positioned in front of every API reject any request that does not carry the right attestation, closing the bypass routes that shadow connectors and headless browser automation exploit. Continuous Access Evaluation adds a runtime layer that can pull an agent’s token mid-session if behavior deviates from authorized scope, without waiting for a token expiry.
Identity simulation testing adds another enforcement layer by validating how agents behave across identity boundaries before they reach production, catching privilege misconfigurations that would otherwise surface as incidents.
The Maverics Identity Orchestration Platform was built on the premise that identity must be decoupled from applications and managed through a distributed orchestration layer that spans every environment where identities operate. That architecture maps directly onto the requirements of agentic governance.
Maverics treats every AI agent as a first-class identity, governed with the same rigor applied to human users, and enforces zero-trust policy without requiring changes to existing applications or microservices. The platform’s identity fabric architecture provides the abstraction layer that eliminates the custom identity integrations that typically drive agent credential sprawl. Rather than each development team provisioning its own credentials through its own paths, every agent identity flows through a consistent control plane that enforces policy and produces auditable records.
The AI Identity Gateway component of the Maverics architecture sits between agents and the tools they access, downscoping tokens before agents touch resources and preventing drift by design. Because Maverics issues no standing access, the conditions that allow credential sprawl to compound are removed at the architectural level rather than managed through periodic review cycles that always run behind the rate of agent deployment.
Agent sprawl is an identity governance problem, and identity orchestration is how it gets solved. If your organization is scaling agentic workloads without a purpose-built control plane for agent identities, the access inventory you think you have is already incomplete. Explore Strata’s resources to understand how identity orchestration closes the governance gap before your agent program outgrows your ability to manage it.
The post A Guide to Agentic Sprawl: How to Govern Your Program appeared first on Strata.io.
*** This is a Security Bloggers Network syndicated blog from Strata.io authored by Mark Callahan. Read the original post at: https://www.strata.io/blog/agentic-identity/a-guide-to-agentic-sprawl-how-to-govern-your-program/