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Ransomware is malware that infects a computer, encrypts files and blocks access to them until the user makes a digital payment. Ransomware detection is the process of notifying users when ransomware is present on their system, or their files are already being encrypted, blocking ransomware if possible, and guiding users through recovery steps.
Early detection of ransomware is critical for effectively defending against this severe threat and minimizing damage to the organization. There are three primary ways to detect ransomware: signature-based detection, which leverages the binary signature of a ransomware program; traffic-based detection, which detects abnormal patterns in data traffic, and behavioral detection, which detects malware by evaluating the behavior of suspicious operating system processes.
This is part of our series of articles about ransomware protection.
Early detection in cyberattacks is very important. The earlier incidents are stopped in the attack chain, the less likely an attacker is to steal sensitive data or compromise organizational systems.
Early detection of ransomware attacks is more important than any other malware, because the damage is irreversible. If ransomware encrypts data that is not securely backed up, recovery may not be possible, even if the victim pays the ransom. To minimize damage, it is important to prevent ransomware infection before they start encrypting data.
As ransomware advances, early detection becomes more important. Newer ransomware variants steal sensitive company data before being encrypted. If ransomware is detected before data theft occurs, companies will avoid potentially costly and reputationally harmful data breaches.
Related content: Read our guide to ransomware prevention
While different ransomware variants implement the attack in different ways, most have several things in common:
The specific files encrypted will depend on the specific ransomware variant, parameters passed to the ransomware binary to customize its operation for certain victims or campaigns, and pre-configured features of the ransomware program. These could be hardcoded into the ransomware binary itself or added as scripts or utilities packaged with the ransomware.
Most types of ransomware contain configurations that specify whether to include or exclude:
Tips From the Expert
In my experience, here are tips that can help you better enhance ransomware detection strategies:
The following are the most common techniques for detecting ransomware on an infected device.
Signature-based ransomware detection compares ransomware binary hashes to known malware signatures. This enables fast, static analysis of files in the environment. Security platforms and antivirus software capture data from executables to determine whether they are ransomware or approved executables. Most modern antivirus solutions have this capability – when they scan the local environment for malware, they can detect known ransomware variants.
Signature-based ransomware detection technology is a first line of defense. It helps detect known threats, but it is largely unable to identify new ransomware strains. In addition, attackers update and permutate malware files to avoid detection. Even adding just one byte to a file creates a new hash and reduces the likelihood of malware detection.
Still, signature-based detection helps identify outdated ransomware samples and known good files (for example, common business applications), ruling out the possibility that they are malware. It can protect against ordinary ransomware campaigns, but not sophisticated, targeted ransomware campaigns.
Data traffic analysis is another detection method that looks at data processed by and transferred to or from a device, inspecting elements like timestamps and data volumes for anomalies.
If the algorithm detects unusual data patterns that indicate a possible ransomware attack, the file system is locked down. The advantage of this approach over signature-based solutions is that it is highly effective at stopping ransomware attacks, and can detect modified ransomware attacks without knowing their malware signature.
The main disadvantage of this approach is the high rate of false positives. In many cases, protective software can block legitimate files or data operations, resulting in costly downtime and hurting productivity.
Data behavior monitoring is a technique that monitors file execution to identify anomalies. Behavior-based solutions monitor the behavior of files and processes in the operating system for malicious activity such as encryption or overwriting of DLL files.
Unlike the signature-based and data traffic-based methods, this method does not require a signature and has a lower rate of false positives. Also, it does not need to lock down the entire file system – instead, it can block individual processes that exhibit suspicious behavior.
The downside of this approach is that it can take the system time to analyze process behavior before it can detect ransomware activity. This means that in many cases, some data will be encrypted before the algorithm responds.
A dedicated security tool can provide holistic protection against ransomware, both at the network, file system, and application layer. One such solution is Cynet 360, an advanced threat detection and response platform that provides protection against threats, including ransomware, zero-day attacks, advanced persistent threats (APT), and trojans that can evade signature-based security measures.
Cynet provides a multi-layered approach to stop ransomware from executing and encrypting your data:
Learn more about how Cynet 360 can protect your organization against ransomware and other advanced threats.
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