Data is probably the most critical asset in modern organizations which is why cybercriminals are always on the hunt, attempting to infiltrate and steal information. Unfortunately, securing data is extremely challenging due to the massive amount of data spillage happening across organizations, sometimes unbeknownst to management.
Data spillage (a.k.a. data leakage) is a term used to describe a situation where data is accidentally or deliberately exposed or accessed by unauthorized parties while storing or transferring classified information. So far in 2024, an estimated 1 billion records have already been spilled, scraped, and stolen.
Data spillage can occur due to numerous reasons and factors. The top ones include:
Employee Mistakes: An employee copying data onto Dropbox or Google Drive and then forgetting about it;accidentally emailing data to an unintended recipient; losing a laptop, USB drive or a device at an airport, taxi or subway; forgetting to lock down a system, or sharing restricted data with generative AI, are some of the many causes of data leakage.
Social Engineering And Phishing: Social engineering scams, another human factor, is a major reason for data spillage. Cybercriminals entice victims with phishing emails, attachments, and URLs. Victims are then manipulated into sharing sensitive and classified information.
Insider Threats: A disgruntled employee intentionally leaking sensitive data on public forums, social media, etc., or stealing and sharing it with a third party (such as a competitor) can contribute to data spillage.
Data Mismanagement: Lack of expertise in handling and securing data, lack of expertise in handling tools or applications, configuration errors, improper data classification and cataloguing, absence of a data retention schedule, unclear data handling procedures, and unnecessary or excessive privileges – can cause data leakage.
System and Software Vulnerabilities: Bugs and defects in software and systems, cached data (some software cache data to improve performance), poor encryption during data migration, vulnerable third-party components, and poor coding practices can also lead to data loss.
Shadow Data: Shadow data is data that is not actively managed or monitored by IT. For example, data stored in legacy applications, personal cloud storage accounts, messaging apps, collaboration tools, software applications, development platforms, mobile devices, etc. According to IBM, 35% of breaches occur due to shadow data.
Third-party Breaches: Most organizations share some level of sensitive data with third-party suppliers, software and service providers. If security lapses or incidents occur at these third-party organizations then this may lead to shared data falling into the wrong hands.
There are a number of best practices organizations can adopt to reduce the risk of data spillage, including:
Policies And Procedures: Organizations must implement strict policies and procedures around data handling, data retention, and other data security measures. This helps bring transparency and clarity in terms of what the organization expects from its employees. The policies and procedures must also include guidance on data sharing with third parties, social media, and generative AI. Prescribe data security requirements and obligations that third-party service providers and processors must adhere to.
Employee Awareness And Training: Organizations are prone to data spillage due to the careless and negligent behaviour of employees. Users are also highly susceptible to phishing attacks, which can lead to unwanted exposure of data. By providing cybersecurity training, engaging in social engineering and phishing simulation exercises, and implementing awareness initiatives (such as best practices, do’s and don’ts), organizations can decrease the frequency of data spillage. This approach fosters a security-conscious culture where employees take responsibility for and become more vigilant about protecting data.
Granular Access Control: When employees are given blanket access to data and systems, then the possibility of data leakage incidents increases. Instead, if employees can only access data that is relevant to their work, then unwanted access, exposure, and compromise can be reduced to a great extent. If access to systems is limited, this can help curtail lateral movement when attackers infiltrate the environment.
Technical Safeguards: Secure all endpoints, deploy data loss prevention (DLP) software to identify and protect data at rest, in use, or in motion; encrypt all data and monitor access. Adopt phishing-resistant multi-factor authentication (MFA) as an extra layer of security over and above password protection. Regularly patch all systems and software to minimize vulnerabilities and lower the chances of leaks.
Regular Audits: Audits are an important element of a security strategy. Be sure to not only audit security controls and vulnerabilities, but data. Data grows and changes rapidly, so it’s important to identify all the different types of data your organization manages. Classify it based on its importance to the organization. This helps organizations evolve their defences in line with evolving risks.
Finally, despite all measures taken to prevent data spillage, they can still occur due to factors beyond one’s control. A well-practised incident response plan is crucial to identifying and mitigating the impact.
To summarize, data spillage is rampant across organizations and can occur due to many causes. By educating, training, and empowering the workforce, implementing granular access controls, enforcing strict protocols and procedures, deploying technical safeguards, and conducting routine security and data audits, organizations can mitigate the risk of data spillage to a great extent.