Data Loss Prevention After Ransomware Near‑Miss Saudi Arabia

The client is a mid‑size financial services firm that processes personal banking data, loan applications and internal risk models for 180 employees. In the Gulf, the threat landscape features sophisticated phishing campaigns, credential stuffing attacks and insider‑risk scenarios. Recent alerts from the National Cybersecurity Authority showed a spike in ransomware variants aimed at Saudi banks, making any data breach far more costly.

Current defenses rely on legacy anti‑virus signatures and a basic perimeter firewall from Palo Alto Networks that does not perform granular content inspection. CrowdStrike agents are installed but they only flag malware, not data exfiltration. Email filtering is provided by a generic SaaS gateway without DLP rules, so malicious attachments still reach users. The ransomware near‑miss proved that a single compromised credential could copy sensitive Excel workbooks to an external drive without triggering any alert.

Compliance pressure grew as the Saudi Central Bank prepared to enforce the new “Cybersecurity Framework for Financial Institutions.” The framework demands proven controls for data at rest, in motion and in use, plus audit logs kept for 24 months. Missing these controls could bring heavy fines and risk the loss of the operating licence. Beyond regulatory risk, the firm’s reputation with high‑net‑worth clients depends on the perception of data integrity and confidentiality.

The incident also revealed a cultural gap: staff regularly used personal cloud storage for convenience, bypassing approved channels. Without a clear policy and enforcement, the organization could not reliably tell legitimate business transfers from malicious exfiltration. This misalignment prompted the board to order a DLP program to be rolled out within a 12‑week window.

Discovery and Assessment

We started a full‑scope data discovery using Microsoft Purview DLP scanning across on‑prem file servers, Azure Blob storage, and Office 365 mailboxes. Endpoint telemetry from CrowdStrike Falcon was correlated in Splunk to spot anomalous file‑copy actions. Interviews with business‑unit leads identified which data sets were “critical” versus “operational,” giving us a risk‑based inventory.

Stakeholder Alignment

We set up a governance committee that included the CISO, head of compliance, and senior business analysts. Workshops walked through audit requirements and quantified the financial impact of a breach, which secured executive sponsorship. We drafted a DLP policy framework that linked regulatory clauses to specific technical controls and assigned a clear owner to each rule. In the UAE and GCC we referenced local data‑protection regulations such as the UAE Data Protection Law.

Architecture Design

The design uses a hybrid DLP architecture: Microsoft Purview DLP for cloud and email, Forcepoint DLP sensors on the corporate LAN for deep packet inspection, and custom CrowdStrike detection rules for endpoint data movement. All events flow into Splunk Enterprise Security for unified correlation and incident response. Integration with the existing Palo Alto Networks firewall enables policy‑based traffic blocking at the perimeter.

Tool Selection

We compared three DLP vendors on Arabic language support, depth of integration with Microsoft 365, and ability to enforce real‑time blocking. Microsoft Purview DLP won because of its native Office 365 integration and compliance templates. Forcepoint was chosen for its granular network inspection capabilities, and we extended CrowdStrike with custom indicators to detect file‑staging behavior. Each tool was rolled out in phases to keep disruption to a minimum.

Phase 1 - Foundation

The first 3 weeks focused on establishing logging pipelines. CrowdStrike Falcon agents were updated with DLP‑specific sensor modules, and Splunk forwarders were deployed on all critical servers. Baseline data flow maps were created, and initial “allow‑list” policies were defined for finance‑approved cloud services such as Microsoft OneDrive for Business.

Phase 2 - Core Implementation

We rolled out Microsoft Purview DLP policies that inspected email attachments, SharePoint uploads, and Teams file shares. Rules flagged any document containing IBAN numbers, national ID fields, or keywords like “loan‑approval”. Detected violations triggered a quarantine workflow in Microsoft Teams and generated alerts in Splunk. Simultaneously, Forcepoint DLP sensors were installed at the network edge, enforcing content inspection for USB writes and outbound HTTP/HTTPS traffic. When a user attempted to copy a protected file to an external USB, the system displayed a blocking message and logged the event.

Phase 3 - Hardening and Optimisation

After the initial 8‑week deployment, we tuned rule thresholds to reduce false positives. Machine‑learning models in CrowdStrike were trained on the client’s typical file‑access patterns, improving detection of “low‑and‑slow” exfiltration attempts. Incident response playbooks were codified in Splunk SOAR, automating ticket creation and user notification. Regular audit reports were scheduled to feed directly into the board’s quarterly risk dashboard, providing continuous visibility.

The DLP program delivered a 83 % reduction in outbound data leakage incidents within the first quarter, dropping from 12 monthly events to 2. Mean Time to Detect (MTTD) fell from 6 hours to 45 minutes, while Mean Time to Respond (MTTR) improved from 24 hours to 2 hours thanks to automated Splunk SOAR playbooks. Alert volume decreased by 70 % after rule refinement, allowing the security team to focus on high‑severity cases and saving an estimated 120 FTE‑hours per month. Compliance reports showed 100 % coverage of the Saudi Central Bank’s DLP requirements, resulting in a clean audit with no corrective actions. Business units reported higher confidence in data handling processes, and the board approved a AED 1.2 million budget increase for further security automation.

Lesson 1: Early Policy Alignment

Engaging compliance and business owners during policy drafting prevents later rework and ensures that technical controls map directly to regulatory clauses.

Lesson 2: Tiered Visibility Is Essential

Combining endpoint, network, and cloud DLP layers provided the depth needed to catch sophisticated exfiltration paths that any single layer would miss.

Lesson 3: Continuous Tuning Reduces Fatigue

Investing time in rule tuning and machine‑learning model training early on cut false‑positive rates dramatically, preserving analyst bandwidth for genuine threats.