Data Loss Prevention (DLP)
A leak does not always start with a breach. Data leaves through email, cloud storage, messengers and removable media — in the course of everyday work. DLP controls how sensitive information is used and transferred inside the organization and beyond it.
The data map comes first
We look at how information actually moves through the organization, and only then write policies.
Monitoring first
Blocking is switched on after we have seen the real flows and filtered out the noise.
Response matched to risk
Not blocking everything, but choosing an action proportionate to the event.
Data Loss Prevention solutions
Hafaza Tech designs and implements DLP based on SearchInform and Falcongaze SecureTower, adapting protection policies to the way information is actually exchanged in the organization.
A platform for leak protection and insider risk control: control of data transfer channels, content analysis, policy enforcement and incident investigation.
Where needed, DLP is complemented by other components of the ecosystem. The exact set is defined by the customer’s objectives and architecture.
A platform for leak protection and insider risk control: it monitors how information is transferred and helps investigate incidents.
Used to control data transfer and communication channels, inspect content, analyze user activity and review incidents.
We deliberately avoid reducing the choice between SearchInform and Falcongaze to a line-by-line feature comparison. Both platforms keep developing, and the presence of a specific capability has to be verified against the current product version. What matters more is how well the solution fits the real data flows, applications and workstations, and the way processes are organized in the company.
What DLP is
It is more than channel control
The core job of DLP is to protect sensitive information throughout its use inside the organization. Controlling a particular port, application or device is not enough for that: a policy has to take several factors into account at once.
Questions the system answers
Which data has to be protected
Who works with it
Where it is located
Which channels it moves through
Where it is sent
Which actions are acceptable
Which events call for blocking or investigation
Sending an internal document to a colleague and sending the same document to a personal mailbox are technically the same action, but events of very different risk.
What data DLP protects
Before blocking a transfer, you have to define which data is genuinely sensitive. The list is compiled together with the process owners, not by the security team alone.
Personal and financial data
Personal data, financial information, customer databases.
Commercial information
Trade secrets, contracts and internal documents, intellectual property.
Technical assets
Source code, technical documentation, credentials and information about how the infrastructure is protected, documents with an assigned confidentiality category.
Detection methods differ for different types of information
Keywords
→
Dictionaries
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Regular expressions
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Digital fingerprints
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Exact and partial match
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Text recognition
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Classification labels
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Contextual rules
DLP should not rely on a single mechanism. The higher the cost of an automatic block, the more important it is to use several indicators at once — that is what reduces false positives.
Data at rest, in use and in motion
Sensitive data calls for different control mechanisms depending on whether it is stored, used or transferred.
For stored data, DLP can be complemented by dedicated discovery and classification tools.
Channels and context
Design around real data flows, not around a feature list
Beyond the classic email and USB, employees use browsers, cloud applications, collaboration services, SaaS, personal devices and remote access. During the assessment it is important to understand which data → who uses it → through which systems → where it goes. Only then can the control channels that really matter be defined.
What a policy can take into account
Classification of the document and the user
Department and workstation
Direction and transfer channel
Recipient and volume of data
Time of the event
The user’s previous actions
A financial report may legitimately move between the finance team and management, but sending it to a personal address is already a different event. Context reduces false positives and makes it possible to block where it is genuinely needed. Support for a specific channel depends on the platform, the operating system, the application and the agent version on the workstation.
DLP should not block everything
The largest number of blocks does not mean the highest level of security.
The main task is to choose a response that matches the actual risk. Which actions are available depends on the platform and on the channel being controlled.
Why DLP is first deployed in monitoring mode
One of the most common mistakes is to turn on strict blocking right after the system is installed. First the system shows how data actually moves, and only then are policies switched to enforcement.
Monitoring
→
Analysis
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Tuning
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Blocking
Before DLP is in place, an organization often does not know every real way information is exchanged. Strict policies can unexpectedly stop the work of finance, HR, developers or the legal department.
In the first stage the system shows the real data flows. Then we analyze the events together with the customer, filter out the noise, and only after that switch policies to blocking.
If a rule produces thousands of irrelevant incidents, analysts stop working with the system. That is why tuning is a permanent part of the DLP lifecycle, not a one-off task.
Causes of false positives: keywords that are too broad, imprecise regular expressions, lack of knowledge of the business process, incorrect classification, thresholds set too low, missing exceptions. The quality of the system is measured not by the number of hits, but by how precisely it isolates the events that really matter.
Data owners and insider risk
The information security team cannot always decide on its own which use of data is acceptable. The finance team understands the normal exchange of financial documents better, HR the handling of employee data, and the legal team contracts.
Division of roles
Security is responsible for the technical controls, the policies and the incident review process. The business takes part in defining which data is critical and which use of it counts as normal.
Without the data owners involved, policies end up either too broad or blocking the work itself.
A leak can be accidental or deliberate
A document went to the wrong recipient
An employee used personal cloud storage
A contractor copied data
A compromised account sends information outside
An employee collects data before leaving
A DLP hit is not the same as a confirmed incident: it is a signal for review, not proof of malicious intent. DLP and employee activity monitoring overlap technically when it comes to insider risk and investigations, but they solve different problems: DLP is built around data and the risk of it spreading, not around watching a person.
Data discovery, cloud and GenAI
New tools mean new ways for data to spread
Protecting data is hard if the organization does not know where it is. Where a separate discovery and classification process is needed, the architecture is built around the cycle “find — classify — protect”, rather than around a single set of rules.
What an employee can send to an external GenAI service
Source code
An internal report
Customer information
Personal data
System configurations
Information about how the infrastructure is protected
Discovery
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Classification
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Policy
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Monitoring
→
Protection
From a DLP point of view, sending data to GenAI is not a separate “AI Security” category but one more scenario of transferring sensitive information to an external service. That is why modern policies treat public GenAI services, SaaS, personal cloud storage, web applications and browser services on the same footing as email and removable media.
Incident investigation
DLP has to give enough context to review an event, not just the fact that a rule fired. An analyst needs the user, the device, the data type and the recipient — in one place.
Critical events are passed to SIEM and to the monitoring center together with information about the user, the device, the data type and the recipient — this is how DLP becomes part of the overall response process.
On-premise and isolated infrastructure
When data cannot leave the customer’s infrastructure
For banks, government organizations and other regulated environments the deployment model matters a great deal. If security telemetry or the protected data cannot leave the perimeter, DLP is designed for local storage and limited connectivity.
What is taken into account in the design
Placement of the management components
Agents on workstations
Local storage of incidents and the volume of telemetry
Network connectivity
Active Directory and directory integrations
Mail systems, proxies, file servers
SIEM and remote sites
How Hafaza Tech implements DLP
A project does not start with installing an agent or switching on the maximum number of rules. The order of the stages below is designed so that blocking arrives when it no longer breaks the work.
Assessment
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Map of data and channels
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Architecture
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Pilot
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Monitoring
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Policy development
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Tuning
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Controlled blocking
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Review process
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Integration
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Continuous tuning
We define the business objectives, the data types to be protected, the number of users and workstations, the operating systems and applications, as well as the data owners and departments that need to take part in developing the policies.
We build a map: Data → User → System → Channel → Recipient. It shows which data really moves inside the organization and outside it, and it is what defines the architecture.
We design the management components and agents, their placement in the network, storage, incident retention periods, integrations, fault tolerance and administration. For large deployments we assess the volume of telemetry separately.
A pilot tests not the presence of features, but the visibility of the required channels, the quality of content recognition, agent stability, the impact on performance and real user scenarios.
Based on real data we create rules, dictionaries, digital fingerprints of documents, classifications, user groups, recipient lists and thresholds. Policies are agreed with the process owners.
After tuning, the most reliable policies are gradually moved from monitoring to blocking. We define who receives the notification, who performs the first-line review and when the monitoring center is involved.
DLP is not a “set it and forget it” system. Employees, applications, cloud services, business processes, contractors, GenAI services and the types of protected data all change — so policies and exceptions are reviewed regularly.
SearchInform or Falcongaze SecureTower?
There is no universally best DLP platform. Instead of comparing dozens of lines in a datasheet, we define a few critical scenarios and test the solution on the infrastructure of the particular customer — which is why a pilot on real tasks is especially useful for DLP.
Coverage
Supported operating systems, the transfer channels you need, business applications, remote workplaces.
Detection
Content recognition, classification, accuracy on the customer’s real documents.
Response to an event
The actions the system offers and how they behave in specific channels.
Investigation
The depth of incident context and how convenient the analyst’s work is.
Architecture
Deployment model, scalability, integrations, storage requirements.
Metrics, not the number of hits
Share of false positives, share of confirmed incidents, time to first-line review and to investigation, coverage of channels and workstations, the number of block overrides and their reasons.
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Related solutions
Complementary solutions for comprehensive infrastructure protection and a higher overall level of information security.
SIEM
Passing critical DLP events into a single monitoring and investigation process.
Database Security
Control of access to data in databases — where the information is stored rather than transferred.
PAM
Control of privileged access to the systems that hold sensitive data.