3 Levels of Automated Remediation 

The concept of automated remediation has emerged as a game-changer. It represents an advanced stage in the evolution of defense, where systems not only detect threats but also autonomously respond. The levels of Automated Remedition have progressed over the years with the help of AI and Machine Learning technologies. Vendors may promise actionable insights as the peak of their offering, but disregard the manual steps needed to seal security gaps. Managing risk, the high turnover of practitioners, and the scarcity of experts highlight the need for safe remediation offered by vendors.

At the basic level, automated remediation started off as basic automated responses to common security threats. This level is characterized by: 

• Pre-Defined Responses: Systems execute specific actions in response to known threats For instance, automatically quarantining a suspicious file or blocking an IP address involved in a brute force attack. 
• Immediate Threat Mitigation: These responses are immediate, minimizing the window of vulnerability between threat detection and response. 
• Low Complexity Solutions: Reactive approaches are suitable for straightforward, well-understood security scenarios where the risks of false positives are minimal. 

Level 2: Addition of Context-Aware Automation – Intelligent and Adaptive Responses 

Moving up, the second level of automated remediation introduced context-aware automation. Key features include: 

• Dynamic Decision-Making: Systems at this level can assess the context of a security alert and decide on the best course of action. This could mean varying responses based on the severity of the threat or the sensitivity of the affected assets. 
• Integration with Analytics: By incorporating analytics, these systems can learn from past incidents and adjust their responses accordingly. 
• Reduced False Positives: Advanced algorithms help to reduce false positives, a critical factor in ensuring that automated actions do not disrupt legitimate business activities. 

The third and most advanced level of automated remediation is predictive and proactive in nature. It’s characterized by: 

• Anticipatory Actions: Here, systems not only respond to threats but anticipate and mitigate them before they materialize. This involves analyzing patterns and predicting potential vulnerabilities while eliminating false positives. This is done across all security layers at their configuration level. 
• Advanced AI and Machine Learning: Identifying risk at the root cause to close all security gaps and remove exposures. Utilizing AI and machine learning, these systems continuously evolve, becoming more effective over time. 
• Strategic Security Posture: At this level, automated remediation becomes a strategic tool, shaping an organization’s overall security posture. It involves a holistic approach, integrating insights from various sources and proactively strengthening defenses. 

One of the standout features at this level is the reduction of false positives. Veriti’s automated remediation solution is adept at distinguishing between real threats and benign anomalies. This precision is crucial in preventing the overwhelming of Security Operations Center (SOC) analysts with false alerts, thus optimizing their focus on genuine threats. It also plays a significant role in simplifying investigations and dramatically lowering the Mean Time to Respond (MTTR) to security incidents. 

Veriti’s platform integrates cross-vendor security solutions into a consolidated security posture management system. This holistic approach ensures comprehensive visibility across the entire security estate. It maps all security assets, their preventative maintenance levels, and relevant vulnerabilities and risk, thereby enhancing the organization’s overall cybersecurity posture.