Data Leakage Protection: Don’t Let Your Data Slip Away

The amount of data businesses hold is growing all the time. By the end of 2025, there will be an estimated 181 zettabytes of information in use worldwide – with 90 percent of this having been created within the last two years. With so much data in use, the consequences of losing control of it can be severe. For large enterprises, mishandling information could end up compromising the details of millions of people and making unwanted headlines.

It’s not just the sheer volume of data that presents a cyber resiliency challenge in today’s environment – it’s the complexity. Data is increasingly widely spread, with a huge number of cloud storage solutions in use, while the number of devices connecting with information has also exploded, especially when it comes to remote and mobile access.

Keeping this both secure and accessible when needed poses a big challenge to businesses. However, with the consequences of data leakage so high, firms can’t afford to overlook this area.

Data leakage refers to any situation where sensitive information is exposed to unauthorized individuals. Unlike data loss, where information is destroyed or rendered inaccessible, leakage means the data remains intact but has been accessed or shared inappropriately. This can happen both accidentally and deliberately, and understanding the difference is vital for building strong defenses.

Common causes of accidental data leakage include:

• Human error: Sending emails to the wrong recipient, falling victim to phishing, or unintentionally sharing sensitive files.
• Misconfigured applications: Leaving databases exposed or failing to change default settings that make information publicly accessible.
• Poor password management: Using weak, reused or default credentials, which attackers can exploit through breaches of other accounts.
• Unsecured devices: Lost or stolen laptops, phones or USB drives without encryption can expose large volumes of sensitive data.
• Third-party access: Vendors or partners with weak security practices inadvertently exposing shared business information.

Malicious leakage can be more dangerous as there is often an intent to expose information in ways that could damage a business, whether this is sharing trade secrets with competitors or selling customer financial information to fraudsters. Malicious data leaks generally fall into these two categories:

• External attacks: Hackers exfiltrating data for extortion, often through double extortion ransomware, to sell or to publicly expose and embarrass a business.
• Insider threats: Employees with legitimate access copying or stealing data for personal gain, espionage or retaliation.

Businesses that miss the warning signs may be unable to stop a data leak until it’s too late. This can be especially true for malicious breaches, where hackers will take precautions to cover their tracks and avoid detection, but accidental data leaks can also go unnoticed for long periods of time. However, the longer data is exposed, the more costly incidents will be.

For example, IBM calculates that in the case of malicious data breaches, it takes an average of 241 days for firms to identify and contain a breach. However, for those where data is stored across multiple environments, this rises to 276 days, compared with 217 where data is held on-premises only. This illustrates the challenges firms face when using more complex networking solutions.

There are several warning signs that can indicate data leakage, which can often be identified with the right technology. These involve comprehensive monitoring of a business’ systems, particularly endpoints, for any unusual behavior patterns. Some common red flags that these tools look for include:

• Repeated failed attempts to log in to an account
• Accessing files or systems that would not normally be needed by the account owner
• Activities such as renaming or copying files
• File access outside of normal working hours or from unusual locations
• Attempts to send data to destinations with unrecognized or overseas IP addresses
• Abnormally large file transfers

One of the most common ways in which data is exposed is through social engineering attacks. These can include:

• Email phishing
• Voice phishing
• Spear phishing
• SMS phishing
• Business email compromise
• Honeytraps

These often look to trick people into handing over login credentials, which cybercriminals can then use to gain access to databases or other applications. However, they may also seek to get people to share data directly.

There have been incidents reported in which criminals have posed as a company’s CEO or other senior executives asking lower-level employees for information or even direct financial transfers. The use of AI phishing and deepfakes has made this even trickier to spot.

For example, in 2024, an employee at UK engineering firm Arup sent $25 million to fraudsters after a video call that used an AI-generated impersonation of senior executives.

A key defense against data leakage is a specialized data loss prevention (DLP) solution. These tools monitor systems for activities that can indicate data loss, such as suspicious traffic, and help alert security teams to threats as quickly as possible.

DLP tools need to cover all aspects of a network in order to provide comprehensive protection. This includes email security, network monitoring, endpoint protection and cloud security.

In order to offer the strongest possible protection against data leakage, there are several important technologies and features that must be considered. When evaluating potential DLP solutions that cover identification, prevention and response, firms should look at:

Detection:

• Intrusion detection systems: Monitor network traffic to identify suspicious or malicious activity in real-time.
• User behavior analytics: Spot unusual access patterns or data transfers that could signal insider threats or compromised accounts.
• SIEM integration: Correlate logs and events across systems for real-time alerts on suspicious activity.

Prevention:

• Encryption: Protect data both in transit and at rest so it cannot be read if intercepted.
• Access controls: Enforce least privilege policies and strong authentication to limit unauthorized access.
• Endpoint and cloud monitoring: Track data movement across devices and cloud services to block exfiltration attempts.
• Anti data exfiltration (ADX): Stop unauthorized transfers of sensitive data in real-time before it leaves the network.

Response:

• Automated policy enforcement: Block or quarantine risky activities immediately to reduce impact.
• Incident response playbooks: Adopt redefined workflows to contain and remediate leakage incidents quickly.
• Forensic auditing and reporting: Create detailed logs and reports to investigate root causes and meet compliance obligations.

While prevention is always better than cure, unfortunately, even the best-prepared businesses may eventually fall victim to a data leakage incident. If this does happen, having a clear plan in place for both immediate steps and longer-term recovery is essential in minimizing any damage, both in terms of disruption to operations and financial costs.

Immediate steps include the following:

• Isolate affected systems or trigger remote data wiping.
• Keep devices running to preserve forensic evidence.

For longer-term recovery and protection, these steps are essential:

• Harden systems with updated tools, ADX deployment and penetration testing.
• Provide ongoing employee training to reduce future risks.
• Engage third-party experts to investigate root causes.
• Prepare for potential legal, regulatory and customer remediation costs.

In the coming years, firms will have to deal with a range of challenges. Regulations are only set to get tighter as citizens around the world become more aware of the value of their data and acceptance of poor handling of sensitive information continues to fall.

Modern data protection laws increasingly focus on consumer data rights, including the right for individuals to access and delete their own data. This means firms will have to make protecting personal data a bigger priority.

When it comes to detecting potential data leakage, the emergence of AI and machine learning tools will play a major role in boosting data security management. These technologies will be particularly useful when it comes to monitoring systems and endpoints for unusual behavior, but firms also need to be aware of risks such as data poisoning when developing their own AI tools.

Already, advanced ADX solutions use AI to improve and automate the process of blocking suspicious data transfers. As these methods become more widely implemented, they are likely to replace traditional approaches such as signature detection to identify data breaches. This will be highly important in defending against threats such as zero-day vulnerabilities and fileless attacks that aim to bypass tools like antimalware.