Continuous Automated Red Teaming (CART)

Automated Red Teaming is a continuous, automated process of testing the security of a system by simulating the activities of an adversary with the goal of uncovering weaknesses in the system. It uses a combination of automated tools and processes such as vulnerability scans, port scans, and other scanning techniques to detect potential vulnerabilities. Manual red teaming and penetration testing cannot be continuous processes due to limitations in time and budget and expertise. Automated Red Teaming is also more effective at uncovering weaknesses that may have been overlooked by manual testing. Automated Red Teaming can be used to supplement manual red teaming and penetration testing, providing a more comprehensive security evaluation.

FireCompass automates red teaming by providing a platform that allows users to define and execute attack scenarios and tests via predefined and custom playbooks. It operates on a “continuous attack model” that monitors and tests systems on an ongoing basis. FireCompass can detect and alert on malicious activities, such as lateral movement and privilege escalation. It also provides a suite of tools for performing reconnaissance, exploitation, and post-exploitation activities. This helps organizations to detect and respond to potential threats before they become a problem and can validate blue team processes that detect these activities.

Automated Red Teaming can improve compliance by providing organizations with continuous monitoring of their networks, systems, and data. This helps to identify any potential risks or weaknesses in their security posture, allowing them to take action to address any issues and ensure that they are meeting their compliance requirements. Automated Red Teaming can also provide regular reports on the state of the organization’s security posture, making it easy to track progress and ensure compliance.

Automated Red Teaming can improve Blue Teaming by providing a more efficient and effective way to test security controls. Automation provides a consistent and repeatable way to simulate real-world attacks, which can help Blue Teams identify vulnerabilities, misconfigurations, or other weaknesses that would be difficult to find manually. Automated Red Teaming also helps Blue Teams better understand the adversary’s tactics, techniques, and procedures, which can help them better prepare for and respond to real-world attacks.

FireCompass uses trained Machine Learning algorithms to help reduce false positives by 99%. The platform analyzes the context of the risks and threats, and looks at the behavior of the attacker and the target, and learns the characteristics of successful malicious activity. FireCompass also leverages threat intelligence and reputation data to further refine output and filter out false positives. With its deep insights, FireCompass can accurately identify assets and risks to reduce false positives by 99%.