What is DLP (data loss prevention)?

What is DLP (data loss prevention)?

Data loss prevention (DLP) is a strategy for detecting and preventing data exfiltration or data destruction. Many DLP security solutions analyze network traffic and internal "endpoint" devices to identify the leakage or loss of confidential information. Organizations use DLP to protect their confidential business information and personally identifiable information (PII), which helps them stay compliant with industry and data privacy regulations.

What is data exfiltration?

Data exfiltration is when data moves without company authorization. This is also known as data extrusion. The primary goal of DLP is to prevent data exfiltration.

Data exfiltration can occur in a number of different ways:

• Confidential data can leave the network via email or instant messaging
• A user can copy data onto an external hard drive without authorization to do so
• An employee could upload data to a public cloud that is outside of the company's control
• An external attacker can gain unauthorized access and steal data
• An employee can upload sensitive data into an AI tool, such as a large language model (LLM)

To prevent data exfiltration, DLP tracks data moving within the network, on employee devices, and when stored on corporate infrastructure. It can then send an alert, change permissions for the data, or in some cases block the data when it is in danger of leaving the corporate network. Some DLP security solutions can even block copying and pasting within web applications to stop confidential data from being copied into an unsecured app, or otherwise moved without permission.

What kinds of threats does data loss prevention help stop?

Insider threats: Anyone with access to corporate systems is considered an insider. This can include employees, ex-employees, contractors, and vendors. Insiders with access to sensitive data can leak, destroy, or steal that data. DLP can help stop the unauthorized forwarding, copying, or destruction of sensitive data by tracking sensitive information within the network.

External attacks: Data exfiltration is often the ultimate goal of a phishing or malware-based attack. External attacks can also result in permanent data loss or destruction, as in a ransomware attack when internal data becomes encrypted and inaccessible. DLP can help prevent malicious attackers from successfully obtaining or encrypting internal data.

Accidental data exposure: Insiders often inadvertently expose data — for instance, an employee may forward an email containing sensitive information to an outsider without realizing it. Similar to how DLP security can stop insider attacks, it can detect and prevent this accidental data exposure by tracking sensitive information within the network.

AI data exposure: Publicly available AI apps use the inputs they receive to add to their data sets and further train their models. This can result in the apps leaking or revealing the data later on to external persons. AI tools also may not comply with the data regulations an organization needs to follow, putting an organization out of compliance if they upload their data.

Regulatory violations: If an organization is subject to data regulatory frameworks like the General Data Protection Regulation (GDPR), data exposure is a violation that can result in fines and other punishments. DLP helps reduce the risk of such violations.

How does DLP work to detect sensitive data?

DLP solutions may use a number of techniques to detect sensitive data. Some of these techniques include:

• Data fingerprinting: This process creates a unique digital "fingerprint" that can identify a specific file, just as individual fingerprints identify individual people. Any copy of the file will have the same fingerprint. DLP software will scan outgoing data for fingerprints to see if any fingerprints match those of confidential files.
• Keyword matching: DLP software looks for certain words or phrases in user messages and blocks messages that contain those words and phrases. If a company wants to keep their quarterly financial report confidential prior to their earnings call, a DLP system can be configured to block outgoing emails containing the phrase "quarterly financial report" or specific phrases that are known to appear in the report.
• Pattern matching: This technique classifies text by the likelihood that it fits into a category of protected data. Suppose an HTTP response going out from a company database contains a 16-digit number. The DLP system classifies this string of text as being extremely likely to be a credit card number, which is protected personal information.
• File matching: A hash of a file moving within or leaving the network is compared to the hashes of protected files. (A hash is a unique string of characters that can identify a file; hashes are created via hashing algorithms, which have the same output every time when given the same input.)
• Exact data matching: This checks data against exact data sets that contain specific information that should remain within organizational control.

What are some important data loss prevention best practices?

Data loss prevention is more than a technology solution: an organization's entire security strategy should revolve around averting data loss. In addition to activating a DLP solution, some of the best practices for loss prevention include:

• Educating internal users on security measures
• Maintaining visibility of all stored data
• Using access control to restrict who can view or alter data
• Encrypting files in transit and at rest
• Using a Zero Trust approach to ensure no device or user is trusted by default

How does Cloudflare One prevent data loss?

The Cloudflare One platform has unified security capabilities, including DLP, to protect data in transit, in use, and at rest across web, SaaS, and private applications. Cloudflare One inspects files and HTTPS traffic for the presence of sensitive data, and allows customers to configure allow or block policies. Cloudflare One also integrates remote browser isolation (RBI) in order to implement further DLP features like restricting downloads and uploads, keyboard input, and printing. Learn more about Cloudflare One.

FAQs

What is data loss prevention (DLP)?

DLP refers to security tools and processes that prevent sensitive data from being lost, stolen, or inappropriately accessed by unauthorized users. It monitors and protects data across three states: data in use, data in motion, and data at rest.

How do DLP solutions identify sensitive data?

DLP solutions use various content inspection methods like pattern matching, keyword matching, or data fingerprinting to recognize sensitive information types like credit card numbers, Social Security numbers, and healthcare data. Advanced DLP systems also employ contextual analysis and machine learning to improve detection accuracy while reducing false positives.

What business challenges does DLP address?

DLP addresses insider threats and data exfiltration risks that could lead to intellectual property theft or compliance violations. It helps organizations meet regulatory requirements like GDPR, HIPAA, and PCI DSS while protecting against both accidental and malicious data leaks.

How does cloud DLP differ from traditional DLP?

Cloud DLP extends protection to data stored in SaaS applications and cloud storage, going beyond on-premises networks. It provides continuous monitoring of all services and helps maintain visibility across hybrid environments where traditional network perimeters no longer exist.

What should organizations consider when implementing DLP?

Organizations considering DLP should start by identifying what data they are trying to protect, what the goals of the implementation are, and which regulatory frameworks (such as the GDPR) apply to their sensitive data. Organizations should also consider integration with existing security infrastructure like CASB for a more holistic approach to securing their data. They should take into account how regulatory compliance and security risks might intersect with the services provided by a DLP vendor. Depending on the implementation, a DLP service may be viewing and processing sensitive data, which can, ironically, put that data at risk or put an organization out of compliance if the vendor does not take sufficient precautions to maintain compliance and security on their end. Finally, they should roll out DLP gradually and make sure it does not hinder ordinary business processes.