The technological age we're living in today brings numerous cybersecurity tools and applications for organizations to choose from. For instance, dynamic code scanning tools like AppScan, Fortify or FindBugs are often used; however, they can sometimes result in false positives due to their reliance on pre-determined rules that may not accurately detect threats. This could mean wasted resources and time spent responding to an alarm when there isn't actually a threat present - risking important security breaches going undetected.
According to the Security Magazines report, 81% of surveyed information technology (IT) professionals declared that more than 20% of cloud security alerts are false positives. Again, 43% of employees highlighted that more than 40% of cybersecurity alerts are false positives. As every team works to improve efficiencies, a high number of false positives can be detrimental.
This article will give a comprehensive guide on what false positives are in penetration testing and cybersecurity. We will also dig into how Packetlabs sets itself apart from its competition when providing penetration testing reports with zero false positives.
What is a false positive in penetration testing and cybersecurity?
A false positive in penetration testing and cybersecurity triggers a false alarm when a security testing tool mistakenly flags a vulnerability. Since most penetration testing is performed by scanning and testing tools, they sometimes incorrectly flag a security vulnerability during software testing. The same happens in automated cybersecurity checks. Tools like Intrusion Prevention Systems (IPS) or Web Application Firewalls (WAFs) incorrectly generate alarms for cyber threats.
In other words, a false positive is a scenario where the system or tool identifies a situation as a threat when it is not really a threat. When a penetration testing tool or security scanner sends out a false positive alert, it requires manual verification. This is not only time-consuming and tedious but also diverts essential IT bandwidth from other activities. The more false positives that arise during the scanning process, the more burdensome this work becomes for IT professionals and resources become scarce as a result. One well-known example of a false positive is when a Microsoft program erroneously determined Chrome browser as "Win32/Zbot," also known as Zeus Trojan, and deleted the entire browser.
Consider that your enterprise is conducting a penetration testing drill using automated tools like Nikto2 or Legion. Suppose the automatic testing and scanning tool generates a false positive alarm. The web application security scanner indicates that the tested web app has a vulnerability, such as cross-site scripting (XSS) or SQL injection. But in reality, the application is secure from cross-site scripting (XSS) and SQL injection. There is nothing to fix. In this situation, penetration testers will waste time reevaluating the test cases. In other areas of cybersecurity, like automated malware scanning or intrusion detection, one false positive can send security professionals on a wild goose chase, examining for non-existent cyberattacks.
Why are false positives a concern?
False positives are often misleading security alerts that serve no real purpose. Automated vulnerability testing can be beneficial to IT professionals, yet they tend to generate a plethora of false positives which eliminates the advantages automation was meant to provide.
Reducing false positives
False positives are both wasteful and time-consuming, not to mention they can easily deceive security experts and penetration testers who run the risk of overlooking valid threats. Thankfully, there exist certain strategies that allow us to reduce false positives significantly; here are a few: Leverage manual testing:
Use multiple, high-quality tools: If hiring a third-party partner to conduct manual testing is out of the question, you can opt to use several pentesting tools in order to catch some of the false positives. This method is not 100% - but it can help eliminate some flagged vulnerabilities.
Tweak settings: Again, if using automated tools are your only option, customize the settings to reduce the number of false positive claims. Security professionals can tweak conditions so that the testing app triggers the right alarm.
Self-verification and PoC: Another way you can reduce the false positive is by making the tool automatically verify its findings by exploiting the recognized vulnerability. It should then generate a report and present the security professionals with a comprehensive proof of concept (PoC) for exploitation.
Use AI & ML: Security professionals and penetration testers can also implement emerging technologies like Artificial Intelligence (AI) and Machine Learning (ML) to reduce false positives. Professionals can train the machine to differentiate between false positives and genuine problems. These systems must get training with reliable and quality data.
Despite all these measures, there is no guarantee that an automated tool will not generate false positives. VA scans can only access limited data and often cannot precisely detect the presence or absence of vulnerabilities, leading to inaccurate results.
On the other hand, manual testing can give you a much more accurate assessment of your security posture. By completing 95% of the testing manually, Packetlabs analysis reports guarantee no false positives. Interested in learning more? Contact the Packetlabs team today!