Challenges Faced by Security Teams Employing SOAR

Large Volumes of Data Human-Machine Collaboration Integration with Diverse Security Tools False Positives and Negatives Lack of Standardized Playbooks

SOAR and AI in Cybersecurity: Reshaping your Security Operations

Challenges Faced by Security Teams Employing Legacy SOAR Platforms

Can an AI Cybersecurity Solution Resolve these Challenges?

AI-Powered SOAR: Top Security Operations Use Cases

Move Forward with Cyware’s AI-powered SOAR Platform

Summing Up

View More guides on Security Orchestration Automation and Response

SOAR and AI in Cybersecurity: Reshaping your Security Operations

Security Orchestration Automation and Response

Posted on: December 01, 2023

In this ever-evolving cybersecurity landscape, with potential threats lurking around every corner and gaining sophistication, security professionals are turning to security orchestration, automation, and response (SOAR) solutions that leverage artificial intelligence (AI) capabilities.

The intersection of SOAR and AI in cybersecurity is transforming how a security team detects, responds to, and mitigates cyber threats. From leveraging machine learning (ML) algorithms for advanced threat detection to automating incident response with intelligent bots, generative AI is revolutionizing the cybersecurity landscape. Organizations are still unraveling the use cases of AI in SOAR and uncovering the game-changing possibilities it presents to protect their digital assets in today’s ever-evolving threat landscape.

Challenges Faced by Security Teams Employing Legacy SOAR Platforms

While traditional SOAR platforms do offer some benefits, there are several challenges that security teams often face when implementing and using SOAR platforms. Some of the challenges faced by security teams in SOAR include:

Large Volumes of Data: As the volume of threat data continues to surge, legacy SOAR platforms often struggle to efficiently process and correlate the sheer magnitude of information. The manual handling of massive datasets poses a risk of delays, oversight, and potential information overload for security teams, hindering their ability to extract timely insights. While such platforms have limited predictive capabilities, they struggle to detect emerging patterns and anomalies, leaving security teams in a reactive rather than proactive stance.

Human-Machine Collaboration: Traditional SOAR platforms automate security workflows, but human expertise is still crucial for effective decision-making, analysis, and response. Achieving seamless collaboration between security analysts and the SOAR platform is difficult, as it requires clear demarcation of roles and responsibilities, training, and effective communication to ensure that both humans and machines work together efficiently.

Integration with Diverse Security Tools: Traditional SOAR platforms need to integrate with a wide range of security tools, such as SIEMs, threat intelligence platforms, endpoint security solutions, and others. However, integrating different security tools with a SOAR platform can be complex and time-consuming, as different tools may have different APIs, data formats, and protocols. Ensuring seamless integration and interoperability among various security tools often becomes challenging for security teams.

False Positives and Negatives: SOAR platforms rely on security alerts generated by various security tools and those alerts can often result in false positives or negatives, leading to inefficient or ineffective response actions. Fine-tuning and optimizing the alert handling and response actions in a SOAR platform is a daunting task that requires continuous monitoring, analysis, and adjustment to reduce false positives and negatives.

Lack of Standardized Playbooks: The playbooks or runbooks in a SOAR platform define automated workflows and response actions. However, the absence of standardized playbooks can lead to inconsistency in response actions and delays in resolving incidents. While achieving consistent and efficient incident response workflows is important, creating effective and comprehensive playbooks is time-consuming. As a resolution, security teams need to invest in creating and maintaining playbooks tailored to their specific environment and use cases.

Can an AI Cybersecurity Solution Resolve these Challenges?

AI plays a significant role in addressing the challenges faced by security teams using legacy SOAR platforms. Here are some ways AI can help:

Automation: AI possesses the capacity to automate repetitive tasks and streamline complex workflows in SOAR platforms, making it easier to configure and manage the platform. AI algorithms can automate critical security operations processes such as data processing, data analysis, data enrichment. Other security operations enhancements include improving decision-making processes when facing cyberattacks and reducing the complexity and time required for manual configuration.

Human-Machine Collaboration: AI-powered SOAR solutions augment threat detection, provide contextualized insights, enhance incident response, and most importantly, continuously learn and improve. The power of continuous learning from data and feedback improves the accuracy and effectiveness of AI-driven SOAR solutions over time. Moreover, human analysts can provide feedback on the accuracy of AI-generated insights, which can be used to train and fine-tune ML algorithms. This feedback loop enables AI to constantly improve its performance and provide more valuable insights to human analysts.

Intelligent Alert Handling: AI has the capability to analyze security alerts and help reduce false positives and negatives. ML algorithms can be trained on historical data to automatically classify and prioritize alerts, enabling more accurate and efficient response actions. AI-powered algorithms can also adapt and learn from feedback to continuously optimize the handling of alerts in real time.

Playbook Creation: Security teams can leverage AI in the creation of playbooks. By analyzing historical security incidents, AI may help automatically generate or suggest playbook templates that can be customized by security teams. This can help accelerate the playbook creation process, ensuring that comprehensive and effective playbooks are available for different scenarios.

Threat Intelligence and Analysis: Large volumes of threat intelligence can be processed using AI and can be automatically correlated with security events, providing valuable context and insights to security teams. AI algorithms can identify patterns, trends, and anomalies in security data, helping security teams detect and respond to advanced threats more effectively.

Predictive Analytics: AI can analyze security data and provide predictive analytics, identifying potential security risks and vulnerabilities before they are exploited. By leveraging ML algorithms, AI can detect patterns and anomalies in data, helping security teams proactively identify and mitigate threats.

Needless to say, AI has the potential to revolutionize decision-making processes by determining whether certain actions require human intervention. With data analysis, pattern recognition, and ML capabilities, AI can automate routine and repetitive tasks, freeing up human effort for more critical and complex decision-making. However, it is important to note that while AI has made significant advancements, there is still progress to be made. AI systems need to continuously evolve and improve to effectively cover a wide range of use cases, handle varying levels of complexity, and adapt to changing environments. Nevertheless, the combination of human expertise and AI capabilities has the potential to significantly enhance operational efficiency and decision-making in the SOAR space, allowing humans to focus on the most critical and strategic aspects of their roles.

AI-Powered SOAR: Top Security Operations Use Cases

Some organizations have already embraced the transformative power of AI and are actively leveraging its capabilities for a multitude of SOAR use cases to improve their security posture. The scope of AI in SOAR is vast as there are several key areas where AI can be leveraged to enhance security operations. Some of these areas are:

Threat Detection and Analysis: As per a report by Accenture highlighted that 74% of organizations believe that AI can help their cybersecurity teams identify and prioritize threats more effectively. Recognizing the potential of AI, several organizations are pioneering its integration into SOAR, making real-time threat detection and analysis possible. AI-powered SOAR platforms integrate with the detection and monitoring technologies within an organization, enabling security teams to respond quickly to potential incidents. AI-powered SOAR tools can sift through vast amounts of data sourced from detection as well as intelligence collected by threat intelligence platforms to identify patterns and anomalies that may raise suspicion of a potential cyber threat. Organizations that are already leveraging AI-based solutions are demonstrating significant value in terms of prioritizing incidents and taking appropriate actions based on the severity and potential impact of incidents

Threat Hunting and Investigation: An AI-enabled SOAR platform can automatically analyze vast amounts of security data from various technologies and help connect the dots between threat elements that may indicate potential threats. This enables security analysts to proactively investigate and respond to threats in real time, reducing the mean time to detect (MTTD) and mean time to respond (MTTR). Additionally, the power of AI in SOAR solutions streamlines the investigation process by automating repetitive tasks, such as data enrichment, incident triage, and evidence collection, allowing security analysts to focus on higher-level analysis and decision-making. This improves the accuracy of threat identification and enhances overall threat hunting and investigation capabilities.

Automated Incident Triage and Response: A study by Capgemini found that 69% of organizations believe that AI is essential for responding to cyber threats effectively. AI can automate and optimize incident response processes, enabling organizations to respond faster and more accurately to security incidents. When security alerts are generated from various sources, AI-powered SOAR platforms can automatically triage and prioritize incidents based on severity, relevance, and potential impact. ML algorithms can analyze the alerts, enrich them with contextual information, and trigger automated response actions, such as blocking an IP address, quarantining a suspicious file, or resetting user credentials, based on predefined playbooks.

Threat Intelligence Analysis, Actioning and Sharing: With AI-powered capabilities, SOAR solutions support automated threat intel ingestion, analysis, and correlation from various sources, such as threat feeds, vulnerability databases, open-source intelligence, security research reports, etc. AI can quickly identify relevant indicators of compromise (IOCs) and provide contextual information to aid in decision-making. Additionally, AI can automate threat intelligence sharing across different security tools and platforms, allowing organizations to quickly disseminate critical threat information to relevant stakeholders for proactive threat mitigation. This helps organizations to stay updated with the latest threat landscape, prioritize and respond to threats effectively, and collaborate with other organizations for collective defense. AI-enabled SOAR solutions significantly enhance the speed, accuracy, and efficiency of threat intelligence and information sharing, enabling organizations to better protect their assets and prevent cyberattacks.

Security Operations Analytics: AI-powered SOAR solutions can be used for security analytics to identify areas of inefficiency, such as high false positive rates or slow response times, and provide recommendations for improving security operations. By analyzing vast amounts of security data, AI-based SOAR platforms can identify potential security risks and vulnerabilities before they can be exploited. This allows security teams to take a more proactive approach to security, identifying and mitigating potential threats before they can cause harm.

Security Workflow Automation: AI-based SOAR platforms can automate various security workflows, such as incident response, threat intelligence automation, and access control. For example, ML algorithms can automatically trigger and orchestrate predefined workflows based on the type, severity, and context of security incidents. This can help organizations streamline security operations, reduce response times, and improve overall security posture.

Move Forward with Cyware’s AI-powered SOAR Platform

Cyware’s SOAR platforms, Respond (CFTR) and Orchestrate, are powered by AI and ML technologies that help organizations automate and streamline their security operations. The AI capabilities enable the platforms to automatically analyze and classify security incidents, identify patterns and anomalies, and provide real-time insights and recommendations to security teams. The automation features enable it to automatically trigger appropriate responses to security incidents, such as blocking IP addresses, quarantining infected machines, and launching countermeasures to neutralize threats.

Cyware’s SOAR solutions are uniquely decoupled - which essentially means that the case management and orchestration/automation modules can work independently of each other yet are tightly coupled for relevant use cases. This eliminates the need to route every orchestration and automation workflow through case management or incident response and builds direct, independent automated workflows between detection, threat hunting, vulnerability management, and other security and IT technologies.

Orchestrate serves as a vendor-agnostic, low-code/no-code orchestration and automation platform for connecting and integrating cyber, IT, and DevOps workflows across cloud, on-premise, and hybrid environments. On the other hand, Respond is an automated incident analysis and threat response platform that helps automate and streamline incident response processes, enabling quick and efficient threat response with a reduced workload on security teams. These solutions offer advanced SOAR capabilities enabling security teams to automate and orchestrate their security operations regardless of their sizes, security maturities, and infrastructure complexities.

Summing Up

AI has emerged as a key enabler of SOAR, providing advanced capabilities that can help security teams respond quickly and effectively to cyber threats. With the increasing sophistication of cyberattacks, it is essential for organizations to adopt AI-powered SOAR technologies that can help them stay ahead of emerging threats. The scope of AI in SOAR is vast, and organizations that leverage AI in their security operations will be better equipped to protect themselves from cyberattacks in the near future.

To learn more about how your security team can benefit from Cyware’s AI-powered SOAR platform, book a free demo now.