Overview

Sensitive information can sometimes be unintentionally exposed through web applications and APIs. Such exposure may involve payment card information, national identification numbers, API secrets, private keys or other confidential data returned by backend applications.

The GAJWAF Suspected Data Leak (DLP) Playbook provides a structured incident-response procedure to help security teams investigate data leak prevention alerts, determine whether sensitive information is genuinely exposed, and apply appropriate protective measures.

GAJWAF's Data Leak Prevention capabilities inspect application responses for configured sensitive-data patterns and can detect, mask or block matching content according to the applicable security configuration.

The guiding principle is simple: Real or False? Then Stop It or Narrow It.

The playbook emphasizes an important distinction: preventing sensitive information from reaching users through GAJWAF does not eliminate the underlying application vulnerability. Permanent remediation must address the application behavior responsible for exposing the data.

What You'll Learn

The playbook follows a four-step investigation and response process, with separate procedures for genuine data leaks and false-positive detections.

Step 1: Investigate the DLP Finding

Learn how to examine GAJWAF security events associated with potentially sensitive information in application responses.

The guide explains how to identify:

  • The sensitive-data pattern that triggered the alert.
  • The affected website, API endpoint or request path.
  • The type of information detected.
  • Whether the response was blocked, masked or only detected.
  • The incident details required for investigation and documentation.

Understanding whether the sensitive information was actually prevented from reaching the client is essential when assessing the severity of an incident.

Step 2: Determine Whether the Finding Is Genuine

Not every DLP alert represents an actual data leak.

The playbook explains how to distinguish between:

  • Genuine data exposure: Sensitive information returned to a client that should not have access to it.
  • Test or sample data: Non-production information matching a sensitive-data pattern.
  • False-positive detection: Benign content incorrectly identified as sensitive information.

The outcome determines whether administrators should contain a real leak or fine-tune an overly broad detection rule.

Step 3: Contain a Confirmed Data Leak

When genuine sensitive-data exposure is identified, administrators should take appropriate action to prevent further disclosure.

The playbook explains how to configure GAJWAF's response-based DLP controls.

Available protective actions include:

  • Mask: Remove or conceal matching sensitive information while allowing the remaining response to be delivered.
  • Block: Prevent the entire response from reaching the client.

Administrators are also guided to notify the application team, preserve relevant incident evidence and ensure that the underlying application issue is tracked for permanent remediation.

Configuration Location: Edit Configuration → Response & Limits → Data-Leak Prevention

Step 4: Resolve False Positives Without Weakening Protection

When a DLP finding is determined to be a false positive, the playbook recommends applying the narrowest effective correction.

Options include:

  • Refining custom sensitive-data detection patterns.
  • Creating targeted exclusions for legitimate application endpoints.
  • Adjusting the enforcement action for a particular data type when justified.
  • Retesting the affected application to confirm that legitimate functionality has been restored.

The objective is to eliminate unnecessary alerts or blocking without disabling DLP protection across the entire application.

Why This Playbook Matters

Sensitive-data exposure can create serious security, privacy and compliance risks.

Following this playbook helps organizations:

  • Investigate suspected sensitive-data exposure systematically.
  • Distinguish genuine leaks from false-positive detections.
  • Identify whether sensitive information was blocked or delivered.
  • Apply response masking or blocking where appropriate.
  • Minimize disruption to legitimate application workflows.
  • Preserve security evidence for incident investigations.
  • Coordinate permanent remediation with application owners.
  • Maintain effective DLP protection while refining detection policies.

Incident Validation and Closure

The playbook includes an incident-closure checklist to help security teams verify that:

  • Confirmed sensitive information is no longer reaching unauthorized clients.
  • The application team has been notified of the underlying issue.
  • Permanent remediation has an assigned owner and target date.
  • False-positive corrections have not weakened protection for other application endpoints.
  • Incident details and configuration changes have been documented.

An incident-record template is also provided to capture the affected application, detection time, incident ID, data type, enforcement action, investigation outcome and remediation details.

Download the Playbook

Document: GAJWAF Playbook – Suspected Data Leak (DLP)
Document Version: 1.0
Document Type: Data Leak Prevention Incident Response Playbook
Publication: October 2026
Pages: 6
Intended Audience: GAJWAF Security Analysts and Administrators

Attachment: GAJWAF_Playbook_Data_Leak_DLP.pdf

Download the attached PDF for detailed DLP investigation procedures, response masking and blocking guidance, false-positive handling and incident-validation checklists.

Related Documentation

For additional guidance, refer to:

Technical Support

For assistance with GAJWAF Data Leak Prevention, sensitive-data detection policies or incident response, contact GajShield Technical Support or your authorized GajShield partner.

Website: https://www.gajshield.com

GAJWAF: Different Applications. Different Protection. Shared Risk Intelligence.