In the image below I have identified some exports used by a DLL that was dropped by a piece of Formbook malware. We can also see that this library imports a number of interesting APIs that could be included within a rule. For a files timestamp to be used in a YARA rule it must be converted to an epoch unix timestamp , in the image below I have identified when the malware was compiled. The version section of PEStudio shows that this sample of Lokibot has some unique version identifiers, using the pe.
Using this information I can specify specific section names and the associated section number. In the example rule, I have included the author, file type of the malware, date the rule was written, rule version, a reference to where I got the sample from, and also a hash of the malware. This gives some contextual information to anybody else who may use the rule or may even be of use to the author when they revisit the rule at a later point in time.
Next, I have specified some strings that I have found in the malware sample, these are declared as variables within the rule and can be used to search for files with similar content. The conditions section is where the rule declares what conditions must be met in order for the YARA rule to trigger a match, the first rule I have stipulated is that the file header must be a Windows Executable.
This is done by specifying the hex values found in the header of a Windows Executable, in the image below you can see how this is identified using a hex editor.
I have also specified that three imports must be present which PEStudio has flagged up as suspicious. With time and experience, you will be able to spot suspicious sections within samples. The remaining condition is that the file size must be less than bytes. You now have the knowledge to start building out your own YARA rules to start hunting out new samples for analysis or alternatively start implementing some proactive detections within your organization.
Neil is a cyber security professional specializing in incident response and malware analysis. Initial commit. Apr 11, Feb 26, Mobile rules based on Androguard are now deprecated. Folders were ren….
View code. Project This project covers the need of a group of IT Security Researchers to have a single repository where different Yara signatures are compiled, classified and kept as up to date as possible, and began as an open source community for collecting Yara rules.
You can check your installed version with yara -v Packages available in Ubuntu Capabilities In this section you will find Yara rules to detect capabilities that do not fit into any of the other categories.
Exploit Kits In this section you will find Yara rules aimed toward the detection and existence of Exploit Kits. Malicious Documents In this section you will find Yara Rules to be used with documents to find if they have been crafted to leverage malicious code. Malware In this section you will find Yara rules specialised toward the identification of well-known malware. Packers In this section you will find Yara Rules aimed to detect well-known software packers, that can be used by malware to hide itself.
WebShells In this section you will find Yara rules specialised toward the identification of well-known webshells. Email In this section you will find Yara rules specialised toward the identification of malicious e-mails. Malware Mobile In this section you will find Yara rules specialised toward the identification of well-known mobile malware.
Deprecated In this section you will find Yara rules deprecated. About Repository of yara rules Resources Readme.
Releases No releases published. Installation, activation, and removal can be done dynamically and does not require a reboot. NET included. Whitepaper libyara. This tool searches for malware in memory images and dumps configuration data. In addition, this tool has a function to list strings to which malicious code refers. MISP Threat Sharing Threat intelligence platform including indicators, threat intelligence, malware samples and binaries. Includes support for sharing, generating, and validating YARA signatures.
MITRE MultiScanner File analysis framework that assists the user in evaluating a set of files by automatically running a suite of tools for the user and aggregating the output. Open source and free. Closed source, free, but registration required. PasteHunter Scan pastebin. Also includes a web interface and online analysis. Enumerate signatures, scan files, and more. It can be integrated into any GitHub repository containing YARA rules and it will run automated tests every time you make some change.
YaraGenerator Quick, simple, and effective yara rule creation to isolate malware families and other malicious objects of interest. Written in Go. Yara Scanner A wrapper around the yara-python project the providing multiple capabilities. Yeti Platform meant to organize observables, indicators of compromise, TTPs, and knowledge on threats in a single, unified repository. Yara Share Free repository and online community for users to upload and share Yara rules. Yara Scan Service A simple service to test your Yara rules against a large set of malicious and identified files.
Topics ioc awesome awesome-list threat-hunting malware-analysis malware-research yara yara-rules malware-detection yara-manager yara-signatures malware-rules yara-scanner awesome-yara.
Releases No releases published. Packages 0 No packages published. Malware is a complex and malicious piece of software. Its behavior range from basic actions like simple modifications of computer systems to advanced behaviors patterns. By definition, a malware is a malicious piece of software with the aim of damaging computer systems like data andidentity stealing ,espionage,legitimate users infection and gaining full or limited control to its developer.
To have a clear understanding of malware analysis, a malware categorization based on its behavior is a must. Even sometimes we cannot classify a malware because it uses many different functionalities but in general, malware can be divided into many categories some of them are described below:. Malware analysis is the art of determining the functionality, origin and potential impact of a given malware sample, such as a virus, worm, trojan horse, rootkit, or backdoor.
As a malware analyst, our main role is to collect all the information about malicious software and have a good understanding of what happened to the infected machines.
Like any process, to perform a malware analysis we typically need to follow a certain methodology and a number of steps. To perform Malware Analysis we can go thru three phases:.
Static malware analysis refers to the examination of the malware sample without executing it. It consists of providing all the information about the malicious binary. The first steps in static analysis are knowing the malware size and file type to have a clear vision about the targeted machines, in addition to determining the hashing values, because cryptographic hashes like MD5 or SHA1 can serve as a unique identifier for the sample file.
To dive deeper, finding strings, dissecting the binary and reverse engineering the code of malware using a disassembler like IDA could be a great step to explore how the malware works by studying the program instructions.
Malware authors often are trying to make the work of malware analysts harder so they are always using packers and cryptors to evade detection. That is why, during static analysis, it is necessary to detect them using tools like PEiD. When performing static malware analysis there are many techniques to classify malware and identify it such as hashes.
Another technique is using YARA rules.
0コメント