In an era where data serves as the currency of the digital realm, ensuring its security is critical. From financial institutions safeguarding transaction records to healthcare organizations securing patient information, the stakes have never been higher. The consequences of data leakage can be catastrophic, with the fallout affecting organizations financially, reputationally, and legally.
In this article, we will explore the different types of data leakage, the common causes behind them, and effective prevention measures that can be implemented to safeguard sensitive information. Data leakage should not be confused with data leaks, as in “actively leaking data” when cybercriminals publish stolen data.
What is Data Leakage?
Data leakage refers to the unauthorized, unintended, or malicious exposure of sensitive information such as PII (Personally Identifiable Information) from a system or code. Data leaks do not need to involve a complete breach of the system’s defenses but rather occur due to vulnerabilities or bugs within the system, code, or third-party APIs we use.
Data Leakage vs. Data Breach
The distinction between a data leak and a data breach lies in the intent and occurrence of these incidents. While both involve unauthorized exposure of sensitive information, their nature and implications differ significantly.
Data Breaches: Intentional Exposure Due to Cyberattacks
Data breaches involve the deliberate exposure of confidential and sensitive information due to a cyberattack. For instance, at the beginning of 2023, PayPal experienced a data breach where unauthorized access to accounts occurred through a technique known as credential stuffing.
This attack targeted users who reused passwords across multiple online accounts. Despite PayPal's prompt action and investigation, the breach impacted over 34,000 users, leading to the exposure of personal information like names, dates of birth, addresses, social security numbers, and transaction histories.
These breaches are typically orchestrated by external threat actors and involve purposeful infiltration of systems with the aim of obtaining confidential data for nefarious motives. In this instance, the breach did not result from a flaw in PayPal's systems but rather from external attackers deliberately compromising user credentials.
Data Leakage: Accidental Exposure Due to Misconfigurations
Typically, data leakage occurs accidentally, where sensitive information is inadvertently exposed due to misconfigurations or vulnerabilities. The majority of data leak incidents occur without the need for any active hacking like breaching a system.
One recent example involves TuneFab Converter, a platform enabling the conversion of copyrighted music from streaming services. Due to a leak attributed to a misconfigured MongoDB database, over 151 million records containing users' IP addresses, emails, and device information were left unprotected and publicly accessible. Though the exposure lasted less than 24 hours and was swiftly addressed upon discovery, such incidents pose risks for threat actors to gather data for potential exploitation.
Categorization of Data Leaks
The ability to identify the different categories and types of data leaks is crucial to effectively address its potential security, financial, and regulatory consequences. Data leaks can be categorized into three main types: active, passive, and human.
Active Data Leaks
Active data leaks occur when attackers employ malicious techniques to extract data from a system. This generally involves someone external to the system actively engaging in attempts to extract information from the system and is often deliberate. These attacks normally target specific organizations. Also known as information disclosure.
Passive Data Leaks
Passive data leaks refer to the unintentional exposure of sensitive data due to misconfigurations, software vulnerabilities, or system bugs exploited by attackers. These leaks occur when a system itself automatically exposes confidential and sensitive information without any malicious intent. Also known as information disclosure.
Human-Related Data Leaks
A human-related data leak occurs when individuals, such as employees, contractors, or third parties, inadvertently or intentionally disclose sensitive information to unauthorized parties. This can happen through actions like sending users’ personal information to the wrong recipient, leaving physical documents or storage devices unattended, misconfiguring systems in a way that leaves data open or vulnerable, or intentionally leaking information for personal gain or revenge.
Types of Data Leaks
Data leaks can manifest in various forms, each presenting unique risks and consequences. Here are some common types of data leaks:
1. Log Leaks
Log leaks occur when log records containing PIII and other confidential information, such as user credentials or payment details, are exposed to unauthorized individuals. This can happen if developers use debug logs in their code, causing sensitive data such as PII to slip into the system logs in production systems.
This issue is compounded due to the fact that logging systems grant access to a broad range of employees for diagnostic purposes. As a result, any sensitive data that reaches the log records is exposed to more people. For example, a developer may inadvertently include a user’s password in a log, which can then be accessed by any employee with access to the log system.
2. Inbound Data Leaks
Inbound data leaks occur when public APIs or web applications unintentionally expose sensitive information. An attacker first has to access the misbehaving API endpoint in order to trigger or exploit it to extract data. For example, vulnerabilities in an application's code may allow the attacker to enter email addresses, and if there’s an account associated with this address, it will return more information about it.
Thus, leaking whether there’s an account linked to a specific email address and revealing some information about that account. An example of this situation would be an API endpoint that returns sensitive customer data when queried with certain parameters.
3. Outbound Data Leaks
Outbound data leaks occur when third-party software or services used by developers that interact with an organization's data inadvertently expose sensitive information. Vulnerabilities in vendor software or misconfigurations can lead to the unauthorized access of customer data. This can involve situations such as sharing customer data with a third-party API or SaaS, thus leaking or exposing their information.
4. Application Exposing Other Customer's Data
Sometimes, data leakage can occur internally when applications expose other customers' data due to programming errors or misconfigurations. For instance, an automated email containing sensitive information could be sent to the wrong recipient, resulting in data leakage.
5. AI Models Exposing Customer Data
Artificial intelligence models trained on confidential and sensitive information or used for decision-making based on confidential data may inadvertently expose customer information. Care must be taken to prevent data leakage when developing and implementing AI systems. For example, an AI model trained on medical records may reveal confidential patient information if not properly secured or anonymized.
6. Misconfigured Data Stores
Misconfigured data storage systems, such as databases, data warehouses, or back-office file systems, can become a significant source of data leakage. Inadequate security configurations or weak access controls can allow unauthorized individuals to access sensitive information. A common example of this situation is a database server left open to the internet or an internal network without proper authentication, allowing a broad range of users to access the sensitive information it stores.
7. Privileged or Business Users
Privileged or business users with access to sensitive data may accidentally or intentionally cause data leakage. This can occur when users fail to adequately protect data or unknowingly transmit it to unauthorized recipients. For instance, a business user may accidentally forward an email containing sensitive customer data to an external email address.
Data Leakage Types Overview
What Causes Data Leakage?
Several factors can contribute to data leakage, ranging from technical vulnerabilities to human errors. Here are some common causes:
1. Misconfigured Systems
Misconfigurations within systems and lax data storage security stand as prominent triggers for data leakage. Sensitive information can become susceptible to unauthorized access when access controls are improperly set, security configurations remain feeble, or software updates are neglected.
2. Security Compromise or Cyberattacks
Security compromises and successful cyberattacks stand as grave threats, instigating data leakage incidents. Attackers adeptly exploit system vulnerabilities, circumvent authentication protocols, or deploy sophisticated tools like malware to infiltrate systems and extract valuable data without authorization.
3. Human Error
Human error remains a significant factor in data leakage incidents. This can involve employees sending sensitive data to the wrong recipients, mishandling physical documents or storage devices, or falling victim to social engineering attacks that facilitate data disclosure.
4. Vulnerable Software and Third-Party Vulnerabilities
Both in-house software vulnerabilities and weaknesses within third-party dependencies pose considerable risks. Attackers exploit these vulnerabilities by identifying weak points and taking advantage of attack vectors to extract data. Timely patching and regular updates to software and third-party systems serve as crucial preventive measures against potential data leakage.
5. Insider Threats and Social Engineering
Internal threats, whether deliberate or accidental, pose a formidable risk to data security. Disgruntled employees wielding authorized access may intentionally disclose sensitive information. Simultaneously, social engineering tactics, such as phishing attacks or impersonation, cunningly deceive employees into unintentionally revealing sensitive data to unauthorized entities, perpetuating data leakage.
How to Prevent Data Leakage?
Effectively preventing data leakage requires implementing a comprehensive approach encompassing technical, procedural, and educational measures. Here are some recommended prevention strategies:
1. Access Control and Least Privilege Principle
Implement access control mechanisms to restrict user access to sensitive data based on the principle of least privilege. Grant users only the minimal privileges necessary to perform their job responsibilities. Regularly review access privileges to ensure they align with the needs of individuals and changing organizational requirements.
2. Employee Training and Education
Employees are the backbone of any business and can play a crucial role in its security strategy. Ensure employees are up to date on security protocol and best practices by providing comprehensive training and education.
This includes raising awareness about the risks of data leakage, teaching secure handling of sensitive information, recognizing social engineering attempts, and reinforcing the importance of adhering to security policies and procedures. Employee education is just as important for developers to ensure that they have the tools they need to implement robust security measures within the company's systems and applications.
3. Robust Password Security and Multi-Factor Authentication
A robust first line of defense can be created by strengthening password policies with strategies such as enforcing complexity standards, periodic password updates, and advocating the use of password managers. Coupling these measures with the implementation of multi-factor authentication adds an additional safeguard against unauthorized access, providing an extra layer of security, especially in scenarios where passwords might get compromised.
4. Encryption of Sensitive Data
Employing robust encryption mechanisms acts as a shield, safeguarding sensitive data both during storage and transit. Encryption renders data indecipherable to unauthorized individuals even if illicitly accessed, ensuring its confidentiality and integrity remain intact. It's important to note that if the system itself has access to the unencrypted data, encryption is no longer an effective measure against data leaks.
5. Regular Security Audits and Monitoring
Conduct regular security audits to identify vulnerabilities and shortcomings within systems or processes that could contribute to data leakage. Implement continuous monitoring tools and technologies to detect and respond to any suspicious activities or signs of potential data leakage.
6. Data Loss Prevention (DLP) Solutions
Implementing Data Loss Prevention solutions emerges as a pivotal strategy to forestall the leakage or transfer of personal information beyond the organization's confines. DLP solutions actively monitor network traffic and end-point machines, identify patterns indicative of sensitive information, and enforce stringent policies to prevent inadvertent data leaks, ensuring data stays protected within prescribed boundaries.
7. Incident Response and Business Continuity Plan
Develop and maintain an incident response plan that outlines step-by-step procedures to follow in case of a data leakage incident. This includes timely detection and investigation of incidents, containment, and mitigation measures. Additionally, ensure there is a comprehensive business continuity plan in place to rapidly recover from incidents and minimize disruption to operations.
8. Minimizing Your Digital Footprint
Beyond these measures, consciously minimizing your digital footprint amplifies your overall security posture. Reducing the amount of personal data stored or shared, adopting privacy-enhancing technologies, and prudently selecting service providers versed in data protection fortifies defenses against potential leaks.
Data Leakage Prevention with Piiano
Securing your data with innovative platforms like Piiano Flows offers a seamless solution. Piiano Flows provides users with a privacy code scanner that statistically analyzes source code, empowering users with the ability to proactively track, review, and understand sensitive data usage within their applications.
This is done by inferring from the code how data is handled and flagging the problematic code lines that lead to a data leak. Whether connected to an online source code repository or utilized as a local CLI tool, Piiano Flows empowers organizations with the insights needed to prevent data leakage and mitigate potential risks.
See Piiano Flows in action in this video, where Guy, Piiano’s Director of AI, explains how Piiano Flows prevents data leaks and breaches in development by tracking sensitive data flows and providing risk assessments.
To learn more about how Piiano Flows can help you prevent leaks and maintain data privacy, check out our Co-Founder and CEO Gil’s LinkedIn post, where Gil describes how Piiano Flows can audit your code for vulnerabilities.
Linkedin post:
Conclusion
Whether it's due to human error, technical vulnerabilities, or malicious intent, the consequences of data loss can be severe, ranging from financial loss to reputational damage or legal repercussions. Mitigating these risks requires a multi-faceted approach to prevention that combines the benefits of technical solutions with employee training and close monitoring.
Solutions such as Piiano Flows offer innovative tools that allow organizations to proactively monitor their environment and prevent leakage, empowering them with the tools to secure their sensitive information effectively. By implementing comprehensive prevention strategies in conjunction with technological solutions, organizations can bolster their defenses against data leakage and keep their sensitive information secure.
Gil is a software ninja who loves both building software (companies too) and breaking code. Renowned for his prowess in security research, including notable exploits of the Microsoft Windows kernel that have earned him unusual high bounty awards. He has written a couple of very successful open source libraries. And he likes to talk publicly in conferences.
It all begins with the cloud, where applications are accessible to everyone. Therefore, a user or an attacker makes no difference per se. Technically, encrypting all data at rest and in transit might seem like a comprehensive approach, but these methods are not enough anymore. For cloud hosted applications, data-at-rest encryption does not provide the coverage one might expect.
Senior Product Owner
