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Malware analysis is the study or process of determining the functionality, origin and potential impact of a given malware sample such as a virus, worm, trojan horse, rootkit, or backdoor. [1] Malware or malicious software is any computer software intended to harm the host operating system or to steal sensitive data from users, organizations or ...
A code quality analysis tool that uses static code analysis. RIPS: 2020-02-17 (3.4) No; proprietary — — Java — — — PHP A static code analysis solution with many integration options for the automated detection of complex security vulnerabilities. SAST Online: 2022-03-07 (1.1.0) No; proprietary — — Java — — — Kotlin, APK
Memory forensics tools are used to acquire or analyze a computer's volatile memory (RAM). They are often used in incident response situations to preserve evidence in memory that would be lost when a system is shut down, and to quickly detect stealthy malware by directly examining the operating system and other running software in memory.
Static analysis can be done manually as a code review or auditing of the code for different purposes, including security, but it is time-consuming. [7] The precision of SAST tool is determined by its scope of analysis and the specific techniques used to identify vulnerabilities. Different levels of analysis include:
Antivirus software typically uses two techniques to detect malware: (i) static analysis and (ii) dynamic/heuristic analysis. [60] Static analysis involves studying the software code of a potentially malicious program and producing a signature of that program. This information is then used to compare scanned files by an antivirus program.
CodeSonar is a static code analysis tool from CodeSecure, Inc. CodeSonar is used to find and fix bugs and security vulnerabilities [1] in source and binary code. [2] [3] [4] It performs whole-program, inter-procedural analysis with abstract interpretation on C, C++, C#, Java, as well as x86 and ARM binary executables and libraries.
Research in combining static and dynamic malware analysis techniques is also currently being conducted in an effort to minimize the shortcomings of both. Studies by researchers such as Islam et al. [13] are working to integrate static and dynamic techniques in order to better analyze and classify malware and malware variants.
A study in 2012 by VDC Research reported that 28.7% of the embedded software engineers surveyed use static analysis tools and 39.7% expect to use them within 2 years. [9] A study from 2010 found that 60% of the interviewed developers in European research projects made at least use of their basic IDE built-in static analyzers.