Use this script to download and merge all the yara malware rules from github: [https://gist.github.com/andreafortuna/29c6ea48adf3d45a979a78763cdc7ce9](https://gist.github.com/andreafortuna/29c6ea48adf3d45a979a78763cdc7ce9)\
Create the _**rules**_ directory and execute it. This will create a file called _**malware\_rules.yar**_ which contains all the yara rules for malware.
You can use the tool [**YaraGen**](https://github.com/Neo23x0/yarGen) to generate yara rules from a binary. Checkout these tutorials: [**Part 1**](https://www.nextron-systems.com/2015/02/16/write-simple-sound-yara-rules/), [**Part 2**](https://www.nextron-systems.com/2015/10/17/how-to-write-simple-but-sound-yara-rules-part-2/), [**Part 3**](https://www.nextron-systems.com/2016/04/15/how-to-write-simple-but-sound-yara-rules-part-3/)
IOC means Indicator Of Compromise. An IOC is a set of **conditions that identifies** some potentially unwanted software or a confirmed **malware**. Blue Teams use this kind of definitions to **search for this kind of malicious files** in their **systems** and **networks**.\
To share these definitions is very useful as when a malware is identified in a computer and an IOC for that malware is created, other Blue Teams can use it to identify the malware faster.
A tool to create or modify IOCs is **** [**IOC Editor**](https://www.fireeye.com/services/freeware/ioc-editor.html)**.**\
****You can use tools such as **** [**Redline**](https://www.fireeye.com/services/freeware/redline.html) **** to **search for defined IOCs in a device**.
****[**Linux Malware Detect (LMD)**](https://www.rfxn.com/projects/linux-malware-detect/) is a malware scanner for Linux released under the GNU GPLv2 license, that is designed around the threats faced in shared hosted environments. It uses threat data from network edge intrusion detection systems to extract malware that is actively being used in attacks and generates signatures for detection. In addition, threat data is also derived from user submissions with the LMD checkout feature and from malware community resources.
****[**NeoPI** ](https://github.com/CiscoCXSecurity/NeoPI)is a Python script that uses a variety of **statistical methods** to detect **obfuscated** and **encrypted** content within text/script files. The intended purpose of NeoPI is to aid in the **detection of hidden web shell code**.
****[**PHP-malware-finder**](https://github.com/nbs-system/php-malware-finder) does its very best to detect **obfuscated**/**dodgy code** as well as files using **PHP** functions often used in **malwares**/webshells.
When checking some **malware sample** you should always **check the signature** of the binary as the **developer** that signed it may be already **related** with **malware.**
If you know that some folder containing the **files** of a web server was **last updated in some date**. **Check** the **date** all the **files** in the **web server were created and modified** and if any date is **suspicious**, check that file.
If the files of a folder s**houldn't have been modified**, you can calculate the **hash** of the **original files** of the folder and **compare** them with the **current** ones. Anything modified will be **suspicious**.
When the information is saved in logs you can **check statistics like how many times each file of a web server was accessed as a webshell might be one of the most**.
