Misconfigured lifetimes can let objects persist longer than intended, which turns request-specific state into shared state. That can expose user data, session context, or authorization-related information across requests. In practice, the risk grows when singleton services hold scoped data, background tasks reuse request objects, or environment-specific overrides change behaviour between test and production.
Why This Matters for Security Teams
Service lifetimes are a security boundary, not just a code-style choice. In .NET, the difference between transient, scoped, and singleton determines whether data is isolated to one request or shared more broadly. When the wrong lifetime is assigned, objects can outlive the trust context they were created in, which can expose authentication state, tenant context, cached claims, or sensitive payloads to other flows. That turns an ordinary dependency issue into a privilege and data exposure problem.
This matters most in applications that mix web requests, background workers, caching, and token-based integrations. A singleton that stores request-scoped state may behave correctly in light testing and then leak data under concurrency, retries, or asynchronous execution. The security impact is amplified when service objects handle secrets, authorisation decisions, or downstream API calls on behalf of a user or workload identity. Guidance from the NIST Cybersecurity Framework 2.0 remains relevant here because secure software design depends on clear control boundaries, not just perimeter controls. In practice, many security teams encounter lifetime-related exposure only after a cross-request leak, not through intentional design review.
How It Works in Practice
The core issue is object reuse. A scoped service is created per request, a transient service is created when resolved, and a singleton is created once for the application. If a singleton depends on a scoped service, or stores a reference to a scoped object, the application can end up holding onto data that was only meant to exist for one request. That can expose user context, impersonation state, cached authorisation results, or even raw secrets if the service was built around a request-specific credential provider.
Typical failure patterns include:
- A singleton cache stores a current user object or claims principal for later reuse.
- A hosted background task resolves request-scoped services through a captured reference.
- A middleware component copies request data into a long-lived service field.
- Environment-specific registration changes service lifetime between test and production.
From a defensive perspective, teams should treat lifetime design as part of secure architecture review. That means validating dependency graphs, avoiding shared mutable state, and ensuring request-bound data is passed explicitly rather than retained in service fields. When service code needs secrets or tokens, the design should align with identity governance patterns described in the OWASP Non-Human Identity Top 10, especially where application components act like workload identities with access to protected resources. The practical rule is simple: the longer an object lives, the less sensitive context it should retain. These controls tend to break down when dependency injection graphs are large and services are reused across web requests, queues, and background execution because the ownership boundary becomes ambiguous.
Common Variations and Edge Cases
Tighter lifetime rules often increase refactoring overhead, requiring organisations to balance safety against codebase complexity. Not every long-lived service is unsafe, but best practice is evolving toward stricter separation between request data and reusable infrastructure. The main exception is stateless singleton use, where a service truly holds no per-user or per-request information and only performs deterministic operations.
Edge cases appear in caching, multi-tenant systems, and asynchronous pipelines. A cache may be safe if it stores normalised, non-sensitive data, but unsafe if it stores authorisation decisions that should expire with the request context. In background processing, a service can be correctly registered yet still become dangerous if it captures objects created under a web request. In multi-tenant applications, even a small mistake can cross tenant boundaries if a lifetime mismatch causes tenant context to persist beyond the request that created it. Where AI-assisted code generation or autonomous agents are used to scaffold application services, teams should also consider whether those components introduce non-human identities or long-lived credentials that behave like stateful dependencies. That is a growing concern in the current guidance, but there is no universal standard for this yet. The practical test is whether a component can be safely reused without retaining any user-specific or security-sensitive state across executions.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
OWASP Non-Human Identity Top 10 address the attack and risk surface, while NIST CSF 2.0 and NIST AI RMF set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| NIST CSF 2.0 | PR.AA-1 | Identities and contexts must be bound to the right access scope. |
| OWASP Non-Human Identity Top 10 | NHI-3 | Long-lived services can behave like mishandled workload identities. |
| NIST AI RMF | GOVERN | Secure software design needs accountable control ownership and review. |
Ensure request identity and authorisation context are isolated and revalidated at each trust boundary.
