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Wednesday, September 30, 2020

Taidoor RAT – a truly persistent threat | IOCs Details

 

Government-supported actors usually conduct long-lasting activities in cyberspace, and to simplify such continuous processes, they often develop malicious tools with the intention of using them for a long period of time. Like any other malicious tool, they need to be stealthy, and when they get detected, some modifications are necessary to become undetectable again. Sometimes it can be as simple as changing the compromised infrastructure, while at other times creating a new version of the tool is required. When organizations put a lot of effort into creating a tool like that, they probably don’t plan to use it in massive campaigns. It is expected to be used in smaller, targeted attacks; therefore, researchers won’t have too many samples for analysis at their disposal.

An example of such a tool is Taidoor RAT (remote access trojan), dating all the way back to 2008, whose new version was recently discovered and presented in a technical report released by the US government institutions. Taidoor is described as a Remote Access Trojan developed and used by cyber actors supported by the Chinese government. The new version of the RAT consists of two parts – a loader in a DLL form, and a main RAT module that comes as RC4-encrypted binary data. The loader first decrypts the encrypted main RAT module, and then executes its exported Start function. The report provides two samples for both the loader and the main encrypted RAT module. These samples come with only two C2 domains and one C2 IP.

Taidoor

As already mentioned, the Taidoor RAT consists of two parts, a loader and the main RAT module. A few pivoting attempts on the loader samples didn’t produce any results, so we focused on the samples of the main RAT module. This makes sense, as they contain the malware configuration including C2 domains and IPs.

Two samples of the main RAT available from the threat report are encrypted with the RC4 algorithm, and aren’t suitable for pivoting in that form. The first step is to decrypt them and get them to their normal DLL format suitable for metadata extraction. Publicly available tools like CyberChef can be used to decrypt various encryption algorithms, including RC4. Once decrypted, the DLL is processed with Titanium Platform, and its metadata is extracted. The first thing to do is look at the files grouped into the same buckets based on the RHA1, our functional file similarity algorithm, for each of the samples.

 

 

 Similar files grouped by RHA1 algorithm

The RHA1 algorithm reveals ten more samples dating back to 2018 and 2019. However, there are additional options for pivoting. Looking at the samples’ exports shows a specific combination of functions and original file name.