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How to Investigate Suspicious User Activity Across Multiple SaaS Applications

by Brittany Bodane, Product Marketing Manager, AppOmni on June 26, 2025

With data and identities distributed across platforms like Microsoft 365, Salesforce, Okta, and ServiceNow, security teams face an increasingly difficult task: identifying and investigating suspicious user behavior that spans multiple systems. In times like these, the challenge isn’t detection—it’s context.

Whether you’re responding to an incident or performing proactive threat prevention, it’s essential to understand how to structure a SaaS investigation effectively before the noise becomes unmanageable or context is lost.

In this post, we’ll outline practical strategies security teams can use to investigate cross-SaaS threats, prioritize real risks, and keep incident response efforts efficient and consistent.

Step 1: Start with a centralized view of alerts

The first step in any investigation is visibility. Without a consolidated view of alert activity across your SaaS applications, patterns and connections between incidents can easily go undetected.

What to do:

Use your SaaS security tool (if available) to centralize alert ingestion.
Normalize events across platforms to ensure common attributes like user IDs, timestamps, and IPs are easily correlated.
Group alerts by monitored service to identify which platforms are generating the most risk signals.

Lateral movement in SaaS apps doesn’t follow the same patterns as in traditional infrastructure. It’s typically identity-driven and occurs across applications through permissions, tokens, or shared integrations, rather than through internal networks. Correlating activity across services helps reveal broader threats like compromised accounts or privilege abuse.

Step 2: Correlate alerts by identity

Once you’ve surfaced high-alert services, the next step is to zero in on the users involved. Investigating by user identity rather than just service can quickly expose behavior patterns that span environments.

What to look for:

Repeated high-risk actions from a single identity across different apps
Sudden changes in behavior, like login from new geographies or time-of-day shifts
Unusual permission changes, MFA disablement, or OAuth token grants

Many SaaS compromises begin with an identity (human or non-human) that gains excessive or unauthorized access. Viewing alert history by identity reveals the scope of risk faster than app-by-app review.

Step 3: Add behavioral and location context

A key challenge in SaaS investigations is differentiating misconfigurations from other types of threats. Adding behavioral context helps security teams make faster, more accurate decisions.

Tips:

Use geolocation analysis to validate logins. Watch for impossible travel or unexpected regions.
Check trends over time: Are these alerts clustered, or part of a longer pattern?
Consider seasonality or operational context (e.g., end-of-quarter access patterns).

Threat actors often mimic legitimate user behavior. Behavioral baselining makes it easier to spot anomalies that aren’t obvious from the alert alone.

Step 4: Build a structured investigation workflow

Once you identify a pattern or set of related alerts, formalize the investigation. This is especially helpful when multiple teams are involved.

Best practices:

Document the investigation scope, timeline, and involved users.
Track findings and hypothesis testing in a central location.
Assign ownership and document conclusions, even if alerts are ruled out.

You don’t need specialized tools to get started; an internal ticket, shared document, or playbook can help. However, using platforms that offer SaaS-specific investigations with identity context can greatly reduce time to resolution.

Step 5: Prioritize alerts based on risk, not volume

Not every alert deserves equal attention. One of the most common challenges in SaaS threat detection is alert fatigue, especially when tools lack context.

How to triage effectively:

Focus on high-severity alerts with identity and data implications.
Group alerts from the same user or IP address across apps to spot cross-app activity patterns.
De-prioritize redundant or low-fidelity alerts unless part of a broader pattern.

Time spent chasing false positives or isolated alerts delays real investigation. Prioritization based on context and potential impact allows security teams to focus on what matters most. Request a SaaS Risk Assessment and discover how easy operationalizing compliance can be.

Not every alert deserves equal attention. One of the most common challenges in SaaS threat detection is alert fatigue, especially when tools lack context.

Step 6: Integrate investigation data into your broader security operations

Whether or not a specific case leads to a confirmed incident, investigations offer valuable insights for tuning detections, updating policies, and improving incident response workflows.

Post-investigation tips:

Feed findings into your detection logic or UEBA models.
Adjust SaaS security baselines and access policies based on learnings.
Share conclusions across app teams to drive better cross-functional alignment.

Building an iterative feedback loop ensures SaaS investigations lead to stronger posture, not just one-off resolutions.

Moving forward

Organizations looking to mature their SaaS security programs should consider tools that provide:

Identity and activity correlation across apps
SaaS-specific alert logic and behavioral analytics
Investigation workspaces to preserve context and support collaboration

Improving your ability to investigate SaaS activity—quickly, accurately, and in context—can significantly reduce time to response and prevent the escalation of security incidents.