A tool for the search and detection of malware is the YARA rule.
Victor Manuel Alvarez improved the YARA framework, which first appeared in 2007, to recognize malware and arrange it into families with similar traits.
Since then, other cybersecurity-focused businesses have employed the technique. For instance, our cybersecurity experts at Sekoia.io use it to update our intelligence center while also enhancing our ongoing understanding of malware groups.
Describe the YARA ruler. How does it function? What functions does it provide in the field of cybersecurity (especially for researchers and analysts)? In this essay, we’ll try to address the following queries.
How does a Yara ruler function? What is it?
YARA provides a vocabulary for defining a file using elements like its size, the character strings that make up it, or pieces of produced code, as was indicated in the beginning to this page.
A sample of malware or a sample of a group of malware is used to generate rules. Because the malware’s character string and that of an established malware family are similar, this identification is made possible.
Information about the malware’s file size, file type, strings, creation date, and other characteristics of its many components also play a role in detecting and categorizing it.
Security researchers and analysts can stop malware before it is executed in a network by building YARA rules using a variety of samples acquired from websites like virustotal. Especially considering that this tool may detect a file without waiting for it to be executed.
A YARA rule can be used with inert files in addition to being simple to use. This uniqueness is another factor that has helped it become more well-liked within cybersecurity research circles.
Be prepared for malware detection, but also push for the development of ongoing cyber threat intelligence
In the field of cybersecurity, the YARA rule is mostly used for two purposes. It enables cyber professionals to find any dangerous files in a system, as was said at the beginning of this article. Installing it in an EDR is one example of the approach in this situation (endpoint detection response).
The rule runs to examine the file as soon as a terminal or machine (computer, phone) produces or downloads it. In other words, it checks the characters in the string to see if they belong to a family of harmful software and reports it if they do.
On the other hand, it enables CTI professionals to enhance their cyber goodwill threat intelligence actions. In other words, listing new malware versions based on data particular to a class or family of malware serves them, for instance.
In actuality, the idea is straightforward. It starts with a recovery of files that businesses have provided, particularly on the Virustotal platform, in order to check for the presence of malware. Only files that have been identified by YARA rules are the subject of this extraction.
Applying a YARA rule to this first database is the next step. The YARA rule here will make it possible to detect the malware versions and, consequently, follow the progress of the harmful software and its new technical functioning modes, much like a fishing net hunting for fish that meet a certain requirement (if the case arises ).
If it can be extracted from recently discovered malware, it can also list all of its infrastructure. As a result, it is now able to continuously display all malware variants as well as the web servers it interacts with.
Cyber Threat Intelligence professionals at SEKOIA frequently use similar techniques. One of them recently made it possible to compile a report on the “Command & Control” networks used by state-sponsored cyberattack campaigns and cybercriminals.
These findings, for instance, demonstrate that ransomware gangs used more than 38,000 IP addresses as C2 servers in 2021. When compared to the outcomes for 2020, this represents an increase of more than 75%. These outcomes, which have been transcribed and annotated by SEKOIA’s CTI specialists, are free to download by using the form or the URL provided below.
The researcher is able to develop new YARA rules as a result of this type of information (directly integrated into the intelligence center). This time, its operation will alert the discovery of fresh malware that has not yet been widely detected.
The reversinglabs company has access to all of this data pertaining to the malware’s development. As a result, it improves its capacity to eliminate any potential instances of the aforementioned malware before it causes damage.
For instance, if we discover that a client company is interacting with a web server as a result of the examination of malware discovered by a YARA rule, we are able to warn this client company before the aforementioned threat has an effect on its computer network.