A data leak occurs when sensitive data exposures are overlooked, either due to a security vulnerability or stolen data being unknowingly published on the dark web. Because digital transformation is rapidly expanding attack surfaces, these events are getting harder to detect, preventing organizations from ever reaching a state of complete data breach resilience.
In this post, we describe the framework of a successful data leakage detection strategy.
The Difference Between Data Leaks and Data Breaches
A data leak is the accidental exposure of sensitive information. These events are not initiated by an external impetus. They're caused by vulnerabilities in the security controls protecting confidential data.
When sensitive data is stolen from either a data breach or a ransomware attack and published on the dark web, these events are also classified as data leaks.
A data breach, on the other hand, is the outcome of a planned cyberattack. These events are initiated by an external impetus. Cybercriminals need to overcome data security before exfiltration can occur.
Data loss is another term commonly associated with data leaks. Data loss is the irreversible loss of sensitive data, either by accidental deletion or theft.
These events can be mitigated with Data Loss Prevention (DLP) strategies that prevent data transfer beyond specified boundaries. However, a DLP strategy alone will not prevent data leaks; its focus is too narrow.
Data leak prevention efforts need to consider all of the processes that have a direct and indirect impact on sensitive data protection. This effort even stretches as far back as the coding practices that develop a solution.
Learn more about the differences between data leaks, data breaches, and data loss.
Why is Data Leakage Prevention Important?
Leaked data is a treasured find for a cybercriminal. These events significantly reduce the effort of cybercrime by removing all of the laborious stages preceding data compromised in the cyber kill chain.
Because they make life so much easier for cybercriminals, data leak finds are becoming a primary focus in the world of cybercrime. Meeting this performance metric isn't difficult given the growing prevalence of data leaks.
A 2021 UpGuard study revealed that half of analyzed Fortune 500 companies were leaking data useful for cybercriminal reconnaissance in their public documents.
Also in 2021, UpGuard researchers discovered that at least 47 organizations were unknowingly leaking data through a misconfiguration in Microsoft's PowerApp solutions - a lapse resulting in the exposure of tens of millions of private records.
Many organizations are unknowingly leaking sensitive data sets, potentially exposing trade secrets, Personal Identifiable Information (PII), and even credit card data.
The normalization of data breach prevention efforts will likely have a positive impact across all other sectors of cybersecurity. The degree of sensitive data exposure is proportional to the success of data breaches and phishing attacks. Both events could, therefore, be reduced if data leaks are remediated before they're discovered by cybercriminals.
How to Detect and Prevent Data Leaks
A comprehensive data leak detection strategy requires a two-thronged approach.
- Scan the resources commonly hosting data leak dumps.
- Remediate the vulnerabilities facilitating data leaks.
This strategy cannot be executed with manual efforts alone. Data leak instances are often too numerous and surfaced leaks need to be quickly shut down before they're discovered by cybercriminals.
To extend and accelerate the efforts of internal security teams, the capabilities of machine learning models and AI-powered solutions should be integrated with this data leak prevention strategy.
Common Host of Data Leak Dumps
There has been enough data breach intelligence analyzed to paint a picture of common cybercriminal behavior. Thanks to this data, we can now deploy security controls along each stage of the cyberattack lifecycle.
Data breach post-mortem analysis has also unveiled common cybercriminal behavior beyond a successful breach.
After exploiting leaked data, the next stop for cybercriminals is usually dark web forums where they either put it up for sale or publish it freely.
Such forums need to be continuously monitored in a data leak detection strategy.
Even data leaks being sold can still offer useful information. Such listings often include a sample of compromised data to prove the authenticity of the event.
By cross-referencing the sample information against your third-party vendor list and a database of known breaches, such as Have I Been Pwnd, the source of the leak could potentially be identified.
The following popular dark web forums should be monitored for data leaks:
- Nulled
- Dread
- Crackingking
- Cryptbb
- Raidforums
- Freehacks
- Hacktown
- Xss.is
- exploit.in
- evilzone.org
- 4chan
Learn how to reduce data leak false positives.
Addressing the Source of Data Leaks
The most effective and sustainable cybersecurity initiatives are those that assume a proactive approach to protection.
Data leak monitoring efforts are reduced if the vulnerabilities facilitating data leaks are addressed.
This is most efficiently achieved with an attack surface monitoring solution. Such a solution will discover all of the security vulnerabilities inside your ecosystem and also those throughout your third-party vendor network.
Monitoring the third-party attack surface is crucial since over half of data breach events result from compromised third-party vendors.
Since the majority of breaches stem from compromised third parties, it's safe to assume that your vendors aren't addressing data leaks in their cybersecurity practices.
Because of this, the scope of a data leak detection strategy should also extend to the third-party landscape.
Since data leaks commonly preceded data breaches, this effort will reduce third-party breaches and supply chain attacks, and therefore, the majority of all data breach events.
Watch the video below for an overview of UpGuard's data leak detection features.
