Every organization nowadays wants to deliver applications that don’t have any security vulnerabilities. These vulnerabilities can pose a threat to an organization and its data. Hence, they need to be detected and patched in the initial phase of the development. Most of the time these organizations don’t have a big enough budget to have a highly capable security team. So, they use automated tools mostly known as static application security testing (SAST) in order to perform vulnerability assessments on the softwares they have developed.
These tools use some of the automated scripts and scenarios and do work without human intervention (just configure and run). And other times, they don’t have complete information about the issue, or they detect a vulnerability that is not exploitable or not a vulnerability itself. This type of vulnerability is known as the false positive.
Since SAST tools create a large number of false positives, the process of patching and vulnerability management can be time-consuming and difficult at times. In addition, if these reports are forwarded straight to the development team, it is likely that they will spend a significant amount of time analyzing the vulnerabilities, deleting false positives, and then patching the remaining vulnerabilities.
This approach will take a significant amount of time and will not be cost effective in the long run. We may require the services of a security engineer who can run the test and filter out the false positives, but this will necessitate a significant amount of human intervention, indicating that a better solution is required in order to eliminate the false positives and perform vulnerability assessments efficiently.
How Can We Minimize the False Positives?
Getting false positives when using DAST or SAST tools is common. However, it is necessary to keep it to a minimum because it will be more cost effective and will conserve resources. Incorrect results from SAST tools can be corrected with relative ease.
A combination of security testing and software intelligence should be employed in the SAST tool, and there are a variety of solutions available that combine artificial intelligence with vulnerability assessments to assist organizations in accomplishing this goal. Using these tools, it is possible to identify whether or not certain sections of a software include “dead code” or if certain libraries are just not being used.
A false positive can be caused by a variety of factors, including the fact that the inputs are not being reflected anywhere or transmitted to any queries. In this situation, if the tool detects XSS or SQLi, it is considered a false positive by the tool.
A tool that makes use of artificial intelligence may execute a wide range of advanced functions and tasks for the user. There are a number of different SAST programmes available, each of which searches for vulnerabilities and then seeks to exploit them in different ways. Because of this, a vulnerability will be reported as a vulnerability, and a false positive will be flagged as a false positive if no exploit is attempted to exploit the vulnerability.
Due to this, organizations should invest in better technologies that discover more vulnerabilities or conduct manual vulnerability assessments and penetration tests within their own organizations in order to limit the number of false positives.
All SAST tools, whether open source or enterprise license, produce false positives a majority of the time. It is necessary to reduce the number of false positives produced because they can cause delays in the patching of legitimate vulnerabilities and increase costs needlessly. As a result, solutions that incorporate artificial intelligence and security intelligence should be implemented in organizations in order to ensure that proper patching is performed and that dangers are identified and remedied.
Automating SAST and the culling out of false positives will improve efficiency, costs, and the product development process, making it a highly desirable addition to your SDLC.