Information-protection posture summary
Grounded in the evidence, testing and risk context collected during this engagement.
Information protection
Data Classification and DLP Security Audit
Determine whether sensitive information is consistently identified, labeled and protected as employees use endpoints, email, cloud storage and collaboration tools.
The business problem
Why this assessment matters.
Data loss prevention technology cannot protect information the organization has not identified or classified. Programs also fail when broad policies generate noise, business exceptions become permanent and alerts lack accountable investigation.
Our audit follows representative sensitive-data types from classification rules through technical enforcement and response. It measures both coverage and whether controls support legitimate work.
Audit coverage
What we assess.
Final scope reflects your environment, critical systems, risk profile and assurance objective.
Sensitive-data inventory and ownership
Classification taxonomy and labeling rules
Automated discovery and confidence tuning
Endpoint, email and cloud DLP coverage
SaaS and collaboration sharing controls
Alert triage and incident escalation
Policy exceptions and business justification
Metrics, testing and continuous improvement
Assessment process
How the audit works.
Testing is evidence-led, risk-based and designed to protect business operations.
- Define priority data types and expected handling
- Sample repositories, labels and policy configurations
- Test representative movement scenarios with synthetic data
- Review alert quality, investigations and exceptions
- Create a phased coverage and tuning roadmap
Engagement outputs
What your team receives.
Classification coverage analysis
Grounded in the evidence, testing and risk context collected during this engagement.
DLP policy and channel findings
Grounded in the evidence, testing and risk context collected during this engagement.
Alert and exception workflow assessment
Grounded in the evidence, testing and risk context collected during this engagement.
High-risk data-flow map
Grounded in the evidence, testing and risk context collected during this engagement.
Prioritized tuning and rollout plan
Grounded in the evidence, testing and risk context collected during this engagement.
Standards and guidance
A recognizable basis for conclusions.
Applicable standards organize testing and reporting while the actual environment determines risk.
NIST CSF 2.0
CIS Control 3
ISO 27001 information classification controls
NIST SP 800-53
Microsoft and vendor DLP guidance
Frequently asked questions
Planning your data classification and dlp assessment.
Will DLP testing use real sensitive data?
No. Controlled tests normally use synthetic markers and approved sample records to avoid exposing real customer or employee information.
Can you audit Microsoft Purview?
Yes. Purview labeling, DLP, endpoint and related Microsoft 365 configurations can be included, along with other DLP platforms.
How do you handle false positives?
We review rule logic, confidence levels, alert samples and business context to recommend tuning that protects data without overwhelming teams.
Does the audit cover SaaS sharing?
Yes. Cloud storage, collaboration platforms and external-sharing controls can be traced as part of key data journeys.
Can you help design a classification scheme?
Yes. We can simplify or establish categories, ownership, labeling criteria and handling expectations as part of remediation planning.
Related assessments
Follow connected attack paths.
Request a Data Classification and DLP audit
Discuss scope, timing, access requirements and the evidence your stakeholders need.