Data leaks represent a unique and more subtle form of cyberthreats—the ones from the inside. Unplanned and often unnoticed, data leaks can skim underneath the noses of cybersecurity leaders noses and lay the groundwork for malicious threats.
In essence, a data leak is the unintentional exposure of sensitive data to unauthorised environments. This can occur in many ways: system errors that leave vulnerabilities in a platform, weak cybersecurity infrastructure, or classic human error, such as sending emails to the wrong person.
Involving simple accidents—rather than a newsworthy, planned attack—data leaks can be overlooked by enterprises. However, the frequency and cost of data leaks is on the rise. According to a recent Mimecast study, 43% of companies saw an increase in data leaks caused by human error in 2024, causing an average loss of $13.9m to the organisation. Especially as companies struggle to match the pace of cybersecurity training with the rise of new technologies like AI and digital co-working platforms, 66% of leaders also expect to see a rise in the coming year.
Data leaks and breaches both involve the unwanted release of data from an organisation. The ways in which these threats come about, however, give the two different meanings.
Data breaches, on one hand, start with malicious attacks. Whether this attack comes from a single hacker or a cybercriminal group, it entails an unauthorised party accessing data from within an organisation. Cyberattackers also get to this data through a multitude of strategies—malware, phishing, exploiting vulnerabilities in the system. No matter the strategy, however, data breaches are intentional.
On the other hand, a data leak is more subtle and internal, due to negligence of a simple mistake. It’s what happens when someone unknowingly leaves a door open—like a file shared with the wrong team. While they might not make the news as often, leaks are both more frequent and easier to prevent.
Even though these threats start in different places, data leaks remain the leading cause of data breaches. In fact, “human error” contributed to 95% of data breaches in 2024.
Most data breaches don’t arise from high-level hacking—they’re often triggered by routine errors. Here’s where things tend to go wrong:
Misconfiguring cloud storage: Sometimes cloud storage, like AWS or Azure buckets, is left exposed to the public, wide open for anyone to access.
Leaving code unprotected: Developers might mistakenly push private repositories to a public GitHub without realizing it.
Sending emails to the wrong person: A classic case of human error that sends sensitive information to unintended recipients.
Uploading files into unsecured folders: Files saved or shared without proper access restrictions can be easily discovered or misused.
Using weak or reused passwords: Poor password hygiene—like reusing old passwords or skipping multi-factor authentication—remains a frequent and costly mistake.
Relying on unsanctioned apps or shadow IT tools: Employees may bypass security policies by using unofficial software, increasing risk exposure.
These causes are preventable with the right combination of tooling, cybersecurity training, and governance.
Under frameworks like the UK GDPR, organisations must report data leaks promptly and may be liable for:
Regulatory fines (up to £17.5M or 4% of annual turnover)
Data leak compensation claims
Long-term reputational harm
Proper documentation, rapid response, and data leakage prevention strategies help mitigate liability.
Data leaks don’t always look the same. They fall into distinct categories based on the kind of data exposed and how it's mishandled. Below are some of the most common types:
Accidental disclosures: These occur when internal data—like a file, document, or link—is unintentionally shared outside the organisation. Whether it’s sent to the wrong recipient or made publicly accessible, the result is unintended exposure of sensitive content.
Cloud misconfigurations: This is when data stored in a cloud environment is exposed as a result of incorrect access settings, causing files in storage buckets to be publicly accessible
Credential exposures: Involving the leak of login information, such as usernames or passwords, credential exposures is one of the more classic examples of data leaks. Once these items are leaked, they often end up on the dark web or in breach repositories, giving attackers direct entry into systems.
Hardcoded secrets in codebases: This leak type involves API keys, SSH credentials, or environment variables being embedded in public repositories or CI/CD workflows. Even brief exposure in a commit history can be enough for threat actors to exploit.
Lost or stolen devices: When mobile phones, laptops, or removable drives containing unencrypted data go missing, the leak happens the moment that data becomes accessible to anyone else—regardless of intent.
Machine learning data leakage: A more subtle but growing concern: sensitive information can unintentionally appear in machine learning training datasets. If these datasets are reused, shared, or exposed, so is the embedded private data—sometimes without anyone realising.
An effective data leakage protection strategy must blend technical controls with cultural awareness.
Key prevention steps include:
Deploy data loss prevention (DLP) solutions across endpoints, servers, and cloud platforms
Encrypt sensitive data at rest and in transit
Enforce identity and access management (IAM) policies with least-privilege principles
Train staff regularly on secure data handling
Audit third-party tools and integrations for compliance.
These actions significantly reduce the risk of accidental exposure.
Individuals and organisations can proactively scan for exposed data using:
Data leak checkers that monitor for compromised email addresses or credentials
Dark web monitoring tools
Cloud security posture management (CSPM) tools to detect misconfigurations
Monitoring helps detect exposure before attackers do.
These cases showcase how data leaks begin—often quietly—and how they can evolve into more severe security incidents when exploited by malicious actors.
While cybercriminal groups are typically the ones to exploit data leaks—they’re, ironically, not immune to data leaks themselves. For example, Trend Micro researchers identified that the cloud security threat TeamTNT had inadvertently leaked their own DockerHub credentials in 2022. Basically, Team TNT mistakenly ran their operations while still logged into their DockerHub—all while attempting to attack a fake cloud environment or “honeypot” set up by Trend Micro.
While the discovery pertained to a criminal group, the core issue was a classic data leak: the unintentional exposure of secrets in a publicly accessible environment. These leaked credentials offered insight into TeamTNT’s tooling and opened opportunities for defenders to study and intercept operations.
One example of a data leak that led to an attack happened through Alibaba OSS (open storage service), a cloud-based storage platform used by businesses and developers. After some of the OSS buckets were set to public access by users, attackers were enter these buckets and access sensitive metadata. In this case, cybercriminals planted seemingly-harmless malware images into buckets that let them mine cryptocurrency from these vulnerabilities—a technique called steganography.
The leak, though non-malicious in origin, quickly became a tool for cybercriminals. Attackers used the open buckets to distribute malware and launch further campaigns. This demonstrates how simple misconfigurations can spiral into exploitation.
In another incident, developers unintentionally leaked API tokens and authentication credentials in GitHub Actions workflows. These secrets were stored in environment variables or hardcoded files, which were then committed to public repositories.
Attackers scanned GitHub for exposed credentials and used them to inject malicious jobs into the automation workflows—resulting in unauthorised cryptocurrency mining. The leak didn’t require malware to occur; it simply relied on visibility and inattention.
Data loss prevention (DLP) is one of the most practical defences against unintentional data exposure. Rather than serving as a catch-all cybersecurity framework, DLP is a purpose-built strategy to detect and stop data from leaking beyond controlled environments—whether that’s through email, cloud storage, or endpoints. In the context of data leaks,
Set by security teams, DLP policies act as guardrails: flagging risky behaviour, monitoring sensitive data in motion, and preventing unauthorised transfers. When a DLP tool catches a potential data leak forming, it will notify security teams and help assess the severity of the case.
Enterprise-grade DLP solutions, such as data loss prevention software, provide visibility and enforce protective controls without disrupting legitimate workflows, helping organisations reduce accidental and negligent leaks before they escalate.
It’s not just about protecting data—it’s about managing who can see it. Zero Trust Secure Access (ZTSA) operates on the rule of “never trust, always verify.” That means access is granted based on real-time context—not just someone’s IP address. ZTSA complements DLP. While DLP guards the data, ZTSA ensures only the right people ever get close to it. Together, they build a layered defence that stops both mistakes and misuse. Trend Micro’s ZTSA brings adaptive access control to the table—backing up your DLP policies with smart, identity-based protection. For hybrid workforces, it’s an essential piece of the puzzle.
Trend Micro’s suite combines DLP, endpoint security, and ZTSA to lock down sensitive data—no matter where it lives or moves. It’s a unified approach to a sprawling challenge, helping organisations seal leaks before they start.
Explore our data leak prevention tools to keep your data protected at every step of its journey.