Sensitive-information discovery
Identify likely data locations, sample supported repositories and endpoints, and use appropriate patterns, classifiers or labels to estimate where important information exists and how it moves.
Make sensitive-data policy enforceable
Data Leakage Prevention
Discover and classify sensitive information, design Data Loss Prevention policies, stage controls and connect alerts to workable incident processes.
Connected IT
Cloud
Security
Infrastructure
Workplace
Where the work begins
Build the decision around the business requirement.
Data leakage prevention is the business objective; Data Loss Prevention (DLP) is the commonly used set of technologies and operating practices that helps identify and control sensitive information as it is stored, used or shared. Atmic helps organisations define data types and owners, assess cloud and endpoint channels, design proportionate policies, pilot enforcement and create incident workflows. DLP reduces selected risks but cannot guarantee that information will never leave the organisation.
Problems we help address
Clarity before configuration.
The organisation wants to protect confidential data but has not agreed which information types matter, who owns them or which business uses are legitimate.
Sensitive information is spread across endpoints, email, file shares and cloud services with uneven visibility and inconsistent labels.
Broad blocking policies generate false positives because context, user role, destination and approved exceptions were not considered.
DLP alerts arrive without enough triage information, a severity model or a clear route to legal, privacy, HR or security stakeholders.
Endpoint and cloud controls are expected to behave identically even though platforms, applications, file formats and licences support different inspection and enforcement options.
Scope and capabilities
What a well-scoped engagement can include.
Final scope depends on the environment, priorities, product entitlements and agreed responsibilities.
Classification and ownership
Define an understandable classification scheme, handling expectations and named data owners. Technical detection is mapped to the organisation's terminology rather than becoming the policy by itself.
Policy and rule design
Combine information type, confidence, volume, user, device, application, destination and business context where the selected platform permits. Choose audit, warn, justify, restrict or block actions proportionate to risk.
Endpoint and cloud controls
Apply supported policy to channels such as email, collaboration services, browsers, removable media, printing or clipboard activity according to platform, operating system, application and licence capabilities.
Alert and incident workflow
Define severity, evidence access, triage questions, user contact, escalation, containment, preservation and closure. Separate accidental mistakes, policy exceptions and potentially malicious behaviour.
Tuning and governance
Review false positives, false negatives, overrides and exceptions with data owners. Maintain policy versions, test cases, privacy safeguards and a regular review process as information and work patterns change.
Potential business benefits
Designed for usefulness after handover.
A shared definition of sensitive information and accountable business owners.
Controls focused on meaningful data movements instead of indiscriminate blocking.
Measured rollout using visibility, user guidance and staged enforcement.
Alerts connected to a documented triage and escalation process.
Evidence for refining policy as applications, data and risks change.
Practical use cases
Protect sensitive email content
Detect selected identifiers or labelled documents in outbound mail, warn or restrict according to destination and context, and route higher-risk events for review without treating every external message as a violation.
Control endpoint data movement
Monitor or limit supported transfers to removable media, personal cloud services, unmanaged browsers, printing or clipboard channels while maintaining documented exceptions for legitimate workflows.
Govern cloud collaboration
Find sensitive content in supported repositories, apply classification and sharing policy, and give content owners a route to correct permissions or justify approved external collaboration.
Assessment and implementation
A controlled route from current state to usable outcome.
Each stage establishes evidence for the next decision. The sequence is adjusted to suit risk, dependencies and change windows.
Define data and risk
Work with business owners to identify information types, locations, legitimate flows, applicable obligations and the impact of exposure or excessive restriction.
Assess platforms and licences
Map endpoints, operating systems, applications, cloud repositories and existing labels to the inspection and enforcement capabilities actually available.
Build testable policies
Create narrow scenarios and test data, define expected results, configure audit or simulation modes and verify that evidence is accessible only to approved roles.
Pilot, tune and enforce
Run representative groups, review matches with data owners, improve precision, communicate user actions and progress enforcement according to agreed risk.
Operationalise
Hand over alert queues, triage and escalation playbooks, exception records, privacy controls, metrics and scheduled policy reviews.
Typical deliverables
Artifacts your team can use.
- Sensitive-data definition, location and ownership register.
- DLP platform, licence and channel capability assessment.
- Policy matrix with actions, users, destinations and exceptions.
- Test cases, pilot results and tuning decisions.
- Alert-triage, investigation and escalation playbook.
- Configuration record, exception log and governance schedule.
Planning considerations
Dependencies to surface early.
- DLP does not remove every exfiltration path; unsupported applications, screenshots, photography, encryption and novel formats can limit inspection.
- Detection quality depends on data patterns, context and representative testing, not only on the number of built-in templates enabled.
- Employee monitoring, evidence access and cross-border data handling can raise privacy and legal questions that require authorised review.
- Endpoint, email and cloud controls vary by product, operating system, application and licence.
- Exceptions need named approvers, justification, scope and expiry so they do not become permanent invisible gaps.
- DLP alerts require trained owners; continuous monitoring is not included unless separately contracted.
Frequently asked questions
Useful questions before you begin.
Is data leakage prevention different from Data Loss Prevention?
In this service, data leakage prevention describes the objective of reducing inappropriate disclosure, while Data Loss Prevention (DLP) is the established name for the policies, technologies and workflows used to discover and control sensitive information.
Can DLP guarantee that data never leaves?
No. DLP can identify and control supported channels using known signals, but it cannot cover every application, format or human action. Access control, endpoint security, encryption, awareness, contractual measures and incident response remain part of the wider protection model.
Should we start by blocking sensitive content?
Usually, discovery and audit-first testing are safer. They reveal normal business flows, detection accuracy and affected users. Higher-risk scenarios can then move to warning, justification or blocking with owner-approved exceptions and user communication.
Who should own a DLP policy?
Technology teams can operate the control, but a business or information owner should define the protected data and acceptable uses. Security, privacy, legal, HR and operations may need roles in evidence access, investigation and escalation.
Will one DLP policy work across endpoints and cloud services?
The policy intent can be shared, but detection context and enforcement options differ by channel, platform and licence. Each route should be tested separately, with gaps and compensating controls documented.
Data Leakage Prevention
Turn the requirement into a practical plan.
Share the current environment, desired outcome and timeline. We’ll help define the right next conversation.