Welcome to Unprotect Project: The database about malware self-defending and protection
Malware are one of the most agressive threat in Cyber Security. Companies and Security Industry are working to be more effective against this threat and detecting new variants.
Coding a malware can sometimes be an hard task and time consuming. To avoid detection by security solution but also by malware analysts, it is crucial for malware developers to implement technics to evade the security solution. With this kind of technics, malware are able to pass under the radar and stay undetected on a system.
The purpose of this wiki is to try to centralise all these technics, to understand and detect new generation of malware.
Why malware use self-defending techniques and protection?
One of a big challenge is to detect the malware the fastest possible but also to understand its capabilities. Using self defending technics increase the time of detection and analysis and allow the malware to perform malicious actions.
If the malware evade the AV, Sandbox firewall and other, it has the time to steal data during the time where it stays undetected.
As well, once the malware is caught, it will be analysed by a security analyst that will statically and dynamically analyse it, then create a detection signature.
This time is critical for malware but also for companies:
- For malware, more the time of detection is big, more they can steal and perform malicious action.
- For companies, less the time of detection is big, less they lost data or get damage.
The purpose of this database is to bring solutions and answers to:
- Understand why AV engine doesn’t detect new generation of malware?
- Understand why sandbox tools are not enough effective in front of this threat?
- Understand why malware analyst fall in the malware trap?
- Understand the malware protection technics and how to defeat it.
We do not claim that it is a comprehensive list of techniques, only an approximation of what is publicly known; therefore, it is also an invitation for the community to contribute additional details and information to continue developing the body of knowledge. Contributions could include new techniques, categories, clarifying information, examples, other platforms or environments, methods of detection or mitigation.