FFRI Yarai Ransomware test
You can find more details on FFRI web site. I would like to abbreviate it at this point:
• Yarai has five core protection engines (ZDP engine against 0-day vulnerabilities in applications, static analysis, sandbox, HIPS and machine learning) and hybrid security approach provides in-depth endpoint defense
• Yarai doesn´t use signatures like legacy AV applications do
• Yarai works completely offline and doesn´t need an internet connection
Read more about Yarai here: https://www.ffri.jp/en/products/yarai.htm
Blog post in German about Yarai: https://www.securedsector.com/ffri-yarai-next-generation-endpoint-protection-mit-fnf-engines-und-verhaltenserkennung/
Goal of this test:
– To prove yarai’s performance capability
– To prove the efficiency of yarai in offline operation
Notes:
– Yarai works behavior-oriented. For the test that means that malware is not always detected by static analysis engine but by one of the other engines (sandbox, HIPS or machine learning) at runtime
– While most legacy AV applications rely on their cloud intelligence and fail in many cases regarding detection of 0-day malware or new ransomware samples when they work in offline mode, Yarai is designed to work offline and doesn´t therefore need internet access
– Windows Defender is turned off, although it can be activated to run along with Yarai to achieve a maximum protection level
Test methodology:
1. All samples have been downloaded from testmyav.com (50 samples) and from any.run (single ransomware samples)
2. Virtual network adapter was disabled to make sure that Yarai has no internet connection and works fully in offline mode
3. Samples have been extracted from archives to check whether they are being detected by static analysis engine during on-access scan. As mentioned before, static analysis can detect many malware variations but not all. To test whether the other engines were able to detect and block all threats the samples have been executed either manually or via command line