Shadow SaaS and AI need identity-aware controls beyond CASB

At a glance

What this is: This webinar compares CASB and SSPM for Shadow SaaS and AI, concluding that modern SaaS risk now depends on identity, OAuth, and embedded AI context as much as application discovery.

Why it matters: IAM, PAM, and NHI teams need this distinction because SaaS and AI exposure increasingly flows through permissions, tokens, and machine identities that conventional app-level visibility can miss.

By the numbers:

• Only 5.7% of organisations have full visibility into their service accounts.
• The average Grip customer also uses 1,017 AI-enabled applications.
• 54% of enterprise applications contain detectable AI functionality.

👉 Read Grip Security's analysis of SSPM vs CASB for Shadow SaaS and AI

Context

CASB and SSPM are often treated as competing categories, but the real governance gap is broader: organisations need visibility into what is accessed, how it is configured, and which identities and integrations can act through SaaS environments. In a Shadow SaaS and Shadow AI setting, application discovery without identity context leaves a large part of the risk unresolved.

That matters because modern SaaS risk is no longer limited to users logging into approved apps. OAuth grants, persistent tokens, embedded AI features, service accounts, and AI agents can all extend access beyond the point of first approval, which makes this topic directly relevant to IAM, PAM, and NHI governance.

Key questions

Q: How should security teams govern Shadow AI in SaaS applications?

A: Security teams should govern Shadow AI by classifying AI-capable SaaS tools, deciding what data each tool may process, and enforcing those decisions centrally. Discovery is necessary but not sufficient. The control layer must cover model training, retention, sharing, and exceptions so users cannot create hidden data-use risk through ordinary application activity.

Q: Why do CASB and SSPM both matter for modern SaaS security?

A: CASB and SSPM matter because they solve different parts of the same problem. CASB is stronger for access visibility and policy enforcement, while SSPM is stronger for configuration and posture control inside the SaaS application. Modern environments need both, because discovery without posture leaves hidden misconfigurations and posture without discovery misses unsanctioned usage.

Q: What breaks when AI features are embedded inside approved SaaS and CI/CD systems?

A: Traditional gateway controls lose their edge because the traffic looks like normal application use. The risk shifts into configuration files, feature toggles, extension settings, and build steps, where hidden AI functions can move data to external services without a distinct application boundary.

Q: Who is accountable when OAuth consent grants outlive authentication?

A: The accountable owners are the IAM, app governance, and security teams together, because OAuth consent is an authorization control, not a login control. If users can grant broad app access without review, the risk persists after password resets and MFA changes. Governance must cover who can consent, which scopes are allowed, and how tokens are revoked.

Technical breakdown

CASB visibility versus SSPM posture control

CASB and SSPM inspect different layers of SaaS risk. CASB sits closer to access, usage, and policy enforcement, so it is better suited to identifying sanctioned and unsanctioned application activity. SSPM sits closer to the application itself, continuously checking configuration drift, permission settings, and internal security posture. The gap appears when organisations assume that knowing an app exists means knowing whether it is securely governed. In practice, discovery and posture are related but not interchangeable, especially once multiple tenants, integrations, and identity grants are involved.

Practical implication: map which control owns discovery and which owns posture, then test whether either one can explain the full access path.

OAuth grants turn SaaS risk into identity governance

OAuth changes SaaS governance because a user approval can create durable machine-to-machine access that persists beyond the original session. The access decision becomes less about who logged in and more about what scopes were granted, what tokens remain valid, and which connected apps can keep operating. That is why SaaS visibility increasingly overlaps with IAM and NHI governance. A connected app may appear benign at the UI layer while holding broad delegated access in the background. For security teams, the key question is not just whether the application is sanctioned, but whether the delegated identity has an enforceable lifecycle.

Practical implication: inventory OAuth grants as identity artefacts, not just application settings, and tie them to lifecycle review and revocation.

Shadow AI inside sanctioned SaaS changes the threat model

Shadow AI is not only about unsanctioned tools. AI capabilities now appear inside approved SaaS products, where they can inherit existing permissions, read enterprise content, and trigger actions through integrations or agents. That makes application-level approval an incomplete control, because the AI function may be the real actor that expands data reach or automates downstream activity. For governance, this is a boundary problem: the sanctioned application can become an unsanctioned capability container once AI features, tokens, and delegated access are added. Continuous review has to cover the embedded function, not just the parent platform.

Practical implication: classify embedded AI features separately from the host SaaS app and review their access paths as distinct control objects.

NHI Mgmt Group analysis

Identity context is now the missing control plane for SaaS security. CASB can tell teams what is being used, and SSPM can tell them how well an app is configured, but neither is sufficient if the decisive risk lives in the identities and grants behind the application. Modern SaaS estates are populated by humans, service accounts, OAuth-connected apps, and AI agents, which means governance must follow the actor, not only the application. For identity teams, the practical conclusion is that SaaS security has become an identity lifecycle problem as much as a discovery problem.

Shadow AI creates governance debt because embedded capability outruns application inventory. Once AI appears inside sanctioned SaaS, the old sanctioned versus unsanctioned distinction becomes too coarse to support enforcement. That creates a named governance gap we can call embedded AI visibility drift: the organisation knows the app exists, but not which AI functions, scopes, or delegated actions are active inside it. That drift is especially relevant to NHI and agentic AI governance, because the machine identity doing the work may never appear in traditional access reviews. The control answer is continuous identity-aware assessment, not periodic app lists.

OAuth is the bridge where SaaS, IAM, and NHI risks converge. OAuth grants can outlive the user interaction that created them, so delegated access becomes a standing control issue unless it is continuously monitored and revoked. This is where IAM and NHI programmes have to align: user consent, third-party connectivity, and machine-to-machine permissions all share the same lifecycle risk. Organisations that still treat OAuth as a one-time approval event are leaving the most durable part of the exposure unmanaged. The field should treat OAuth governance as core identity governance, not a side feature.

Security architecture is shifting from app-centric inventory to relationship-centric control. The article reflects a wider market move toward continuous control of relationships among applications, identities, permissions, integrations, and data. That aligns with NIST Cybersecurity Framework 2.0 thinking about ongoing govern-protect-detect cycles, but the real operational challenge is stitching together SaaS posture, identity governance, and machine identity oversight. Practitioners should expect the market to converge around relationship visibility rather than point-in-time discovery. The winning control question is no longer what apps exist, but what can act through them.

Rule of 17: the machine-to-human ratio is becoming a governance signal. When AI agents and other NHIs multiply inside SaaS environments, the scale of non-human activity can quickly outstrip manual review processes. That is why identity governance for SaaS and AI must increasingly be built for large populations of ephemeral or semi-persistent actors. The practical conclusion is simple: if the organisation cannot inventory and govern machine identities at the same pace it inventories applications, SaaS risk will remain structurally undercontrolled.

What this signals

Identity-aware SaaS control is becoming the default evaluation lens. Programmes that still separate cloud app discovery from identity governance will miss the point of modern SaaS risk. The practical shift is toward a single control view that can explain which identities, permissions, and integrations can act through a service, and that is where machine identity governance becomes a core requirement rather than an add-on.

Shadow AI will keep pushing security teams toward relationship-centric governance. The next wave of control maturity is not another inventory dashboard. It is the ability to correlate SaaS applications, OAuth grants, embedded AI features, and non-human identities into one risk picture, supported by a framework such as the NIST Cybersecurity Framework 2.0. If a programme cannot trace that relationship chain, it cannot claim continuous control.

OAuth visibility is the practical bridge between identity and SaaS security. If your team cannot explain who granted access, what scope was approved, and how quickly it can be removed, the environment is already outside a safe governance boundary. The next budget and architecture decisions should prioritise lifecycle controls, revocation workflows, and review evidence over simple app counts.

For practitioners

• Separate discovery from posture ownership Define which team owns CASB-style discovery and which owns SSPM-style posture review, then test whether the handoff actually closes the loop on remediation. A control that finds an app but cannot explain its OAuth grants or internal settings is incomplete.
• Treat OAuth grants as governed identities Inventory connected apps, scopes, tokens, and renewal paths as identity objects with lifecycle states. Build revocation into access review, offboarding, and third-party governance so delegated access does not persist after the original business need ends.
• Review embedded AI as a separate risk layer Classify AI functionality inside sanctioned SaaS separately from the host application and assess what data it can reach, what actions it can trigger, and which identities it inherits. This is where Shadow AI often hides behind a trusted brand boundary.
• Add machine identity visibility to SaaS governance Extend SaaS governance to service accounts, integrations, API credentials, and AI agents that interact with cloud applications. Use the same control discipline you would apply to other non-human identities: scope, review, rotation, and removal when no longer needed.

Key takeaways

• CASB and SSPM solve different parts of SaaS security, but neither is enough once Shadow AI, OAuth grants, and machine identities enter the picture.
• The governance gap is visibility into identity and delegated access, not just visibility into applications.
• Practitioners should shift from app-centric inventories to relationship-centric control across identities, permissions, integrations, and embedded AI.

Key terms

• Shadow SaaS: Shadow SaaS is the set of unauthorised or unreviewed software-as-a-service tools used outside central security governance. These applications often bypass normal identity controls, making them difficult to inventory, monitor, and harden against credential-based abuse.
• SaaS posture management: SaaS posture management is the continuous discovery, classification, and policy enforcement of cloud application risk. For AI-enabled SaaS, it extends beyond configuration checks to include data retention, model training permissions, delegated access, and automated remediation when behaviour drifts from policy.
• OAuth Grant: An OAuth grant is the delegated permission an application receives to act on a user's behalf without storing the user's password. In NHI governance, it should be treated as a standing identity relationship with scope, ownership, and revocation requirements, not as a one-time setup detail.
• Non-Human Identity (NHI): A digital identity assigned to a non-human entity such as a software application, service account, API key, bot, machine, or AI agent that enables it to authenticate and interact with systems without direct human involvement. NHIs now outnumber human identities in most enterprises by 25 to 50 times.

What's in the full article

Grip Security's full blog covers the operational detail this post intentionally leaves for the source:

• Side-by-side capability comparison guidance for CASB and SSPM across discovery, posture, OAuth visibility, and remediation
• Grip Security's 2026 Shadow AI exposure figures and how they change SaaS governance assumptions
• Evaluation criteria for deciding whether your current stack can track embedded AI, machine identities, and delegated permissions
• Practical questions for assessing continuous SaaS security control across sanctioned and unsanctioned applications

👉 Grip Security's full post covers the comparison criteria, Shadow AI implications, and the identity context behind SaaS risk.

Deepen your knowledge

The NHI Foundation Level course, the industry's only accredited NHI security programme, covers NHI governance, machine identity security, secrets management, and identity lifecycle controls. It helps practitioners connect SaaS and AI governance back to the identity controls their programmes already depend on.