Better Together: MIND + Okta to Stop Insider Threats

Data loss prevention has a reputation for being painful. False positive alerts overwhelm teams and lead to alert fatigue, especially with regex-only pattern matching that misses nuanced data types like source code or subscriber IDs. Poorly tuned rules sprawl, policies are brittle and managing them is time-consuming. Even then, coverage gaps abound across SaaS, endpoints, GenAI and collaboration tools. Worse, motivated insiders can often bypass traditional DLP with minimal effort.

The industry needed a new approach to data security.

To address this, we are announcing our integration with Okta, the industry leader in identity security. By bringing Okta’s user identity details into the MIND platform, it becomes much harder for malicious insiders to get sensitive data out.

With this integration, MIND will ingest identity insights directly from Okta’s APIs to supercharge our data security engine, reducing false positives, simplifying brittle rule management, extending coverage beyond email and hardening defenses against risky or malicious insiders.

Together, MIND and Okta are delivering something new: a smarter, identity-aware approach to data loss prevention.

MIND has long used identity signals to inform and enforce data security. With Okta as the trusted source of truth for user identity, we now provide a new level of detail and precision. Okta bridges security across all your users, apps and APIs, while MIND secures data at rest and in motion, autonomously. Together, we create a powerful foundation for modern security teams: data protection that knows who’s behind every action, and why it matters.

Here’s what happens when identity and data security work together:

1. Data security policies dynamically adapt with identity risk signals
   Not all users are created equal, and not all data events deserve the same level of scrutiny. A developer downloading source code may be normal. That same activity by a contractor logging in from an unmanaged device may be a red flag.
   
   With this integration, MIND ingests Okta’s identity context and risk indicators, such as group membership, role, device trust and authentication method. Data security policies in MIND can then automatically adjust based on identity risk posture.
   
   That means security teams no longer need to rely on static rules which develop an enormous amount of false positive alerts. Instead, they can let the system adapt in real time, ensuring sensitive data stays protected.
2. Identity & context-aware data security policies can be enforced
   Most DLP solutions look only at the data, what file is being moved, what keyword is inside it, what channel it’s going to. But data alone doesn’t tell the full story.
   
   By combining Okta’s identity insights with MIND’s multi-layer classification engine, policies now consider who is accessing the data, where it’s happening and whether it makes sense. This makes enforcement more precise and less disruptive.
   
   For example, if an authenticated employee in the finance group downloads payroll data to a managed laptop, that may be permitted. If the same file is downloaded to a personal device or shared externally, MIND can automatically block, coach the user or escalate for review.
   
   And all of this sensitive data should be prevented from being sent into an unsanctioned GenAI tool.
   
   This level of nuance isn’t just smarter security, it’s a better experience for employees who can work without unnecessary friction.
3. Risky insiders can be autonomously prevented from leaking sensitive data
   Insider risk remains one of the most difficult challenges for security teams. Whether malicious or accidental, users with valid credentials can cause enormous damage if sensitive information leaves the organization.
   
   With MIND + Okta, insider threats are easier to spot and stop. Okta provides the identity signal — a user logging in from an unusual location, elevating privileges, or failing MFA. MIND provides the data signal — an attempt to move large volumes of sensitive files, upload customer records to a GenAI tool, or share source code with an external party.
   
   Together, these signals allow MIND to autonomously prevent high-risk actions. Security teams can enforce progressive controls, from coaching users in real time to fully blocking data exfiltration. The integration ensures that sensitive data stays where it belongs.

For today’s security leaders, the mandate is clear: secure the business without slowing it down. But with sprawling data environments and complex identity ecosystems, the task can feel overwhelming.

MIND has always positioned itself as Stress-Free DLP. With Okta as the trusted source of truth for user identity, that promise goes even further. This integration removes the guesswork and brings a much finer identity lens, delivering the advanced precision of identity-aware data security policies, the efficiency of automated enforcement and the assurance that insider risks are under control.

The result is a DLP program that isn’t just reactive, it’s proactive, adaptive, intelligent and far easier to manage.

Identity and data security no longer need to be separate. They are two sides of the same coin and combined they can deliver true protection.

MIND + Okta provides exactly that: a unified approach that helps organizations mind what really matters; their sensitive data, people and reputation.

Security teams gain:

• Dynamic protection that adapts policies based on identity risk
• Context-aware enforcement that reduces false positives and friction
• Autonomous insider risk mitigation that keeps data safe in real time

The outcome is peace of mind for CISOs, productivity for employees and resilience for the business.

Ready to see MIND + Okta in action?

1. Why do DLP tools create alert fatigue?
   Legacy DLP relies on regex-only detection, creating floods of false positives. MIND + Okta reduce noise by aligning data alerts with real identity context.
2. Why is traditional DLP hard to manage?
   Rules are brittle and tuning is painful. With Okta as the source of identity truth, MIND simplifies policies and automates enforcement, easing ongoing management.
3. How does this integration address coverage gaps?
   MIND extends protection beyond email into SaaS, endpoints, GenAI and collaboration tools. Okta's identity insights ensure consistent coverage across all environments.
4. Can insiders still bypass controls?
   Traditional DLP is easy to evade. MIND + Okta combine identity and data signals to autonomously block risky actions in real time, preventing exfiltration before it happens.
5. How does this improve user experience?
   Instead of blanket blocking, context-aware controls allow safe activity while only interrupting risky behavior. Employees stay productive without constant security roadblocks.
6. What about context in policy decisions?
   Legacy tools lack awareness of who and why. Okta provides role and authentication data so MIND can enforce smarter, context-rich policies with confidence.
7. How does automation help?
   MIND automates tagging, investigation and remediation. Combined with Okta identity and risk context, security teams save hours on manual tasks and focus on high-value risk reduction.

• DLP (Data Loss Prevention)
  A security strategy and set of tools designed to prevent sensitive data from being leaked, misused or accessed by unauthorized users.
• False Positives
  Alerts triggered by DLP systems that flag benign activity as risky, leading to wasted time, alert fatigue and missed true incidents.
• Identity Context
  User-specific signals such as role, group membership, authentication method and device trust, which help determine the risk behind a data event.
• Insider Threat
  Risk posed by employees, contractors or partners who may intentionally or accidentally leak sensitive data using valid credentials.
• Context-Aware Policies
  Data security rules that factor in who is accessing information, why and under what circumstances, rather than relying solely on static keywords or patterns.
• Coverage Gaps
  Blind spots in traditional DLP solutions that fail to monitor SaaS apps, endpoints, GenAI tools or collaboration platforms, leaving sensitive data unprotected.
• Stress-Free DLP
  MIND’s approach to making data loss prevention simpler to manage, reducing noise, false positives and policy sprawl through automation and identity integration.
• Source of Truth
  A reliable system, like Okta for identity, that provides accurate and authoritative data to guide policy enforcement and reduce complexity.