Artificial intelligence (AI) has become an indispensable tool for security teams in today’s fast-paced cybersecurity landscape. From detecting threats to automating routine tasks, AI has already and continues to transform how Security Operations Centers (SOCs) work, making them more efficient and effective.
Here, we explore the top four ways security teams can leverage AI to enhance their cybersecurity efforts.
1. Enhancing Threat Detection
Chances are, if you’re using modern threat detection systems like Endpoint Detection and Response (EDR), Network Detection and Response (NDR), or Security Information and Event Management (SIEM) platforms, you’re already leveraging AI. Most next-gen detection tools come equipped with built-in AI and machine learning capabilities that significantly improve detection rates and identify previously unknown threats. AI enhances these systems’ ability to sift through vast amounts of data, pinpoint anomalies, and flag potential threats that might go unnoticed by traditional methods. By integrating AI into your detection arsenal, you’re not just reacting to threats but proactively identifying and mitigating them before they can cause harm.
2. Automating Alert Triage with AI
Automating alert triage with AI is a game-changer for Security Operations Centers (SOCs), addressing some of the most pressing challenges security teams face today. By integrating Autonomous SOC systems that function like an extension of your team, SOCs can enhance their efficiency, accuracy, and overall security posture. Here’s a closer look at the four main benefits of integrating around-the-clock AI analysts for triage:
Reducing Analyst Burnout
Teams need good security analysts more than ever. But the constant influx of security alerts can overwhelm even the most seasoned analysts, leading to alert fatigue and burnout. AI alleviates this burden by automating the initial triage process. By automatically sorting and prioritizing alerts based on severity, AI Analysts ensure that our human analysts stay focused on the most critical issues. This not only reduces the manual effort required but also allows analysts to engage in more meaningful and less repetitive work, decreasing burnout and improving job satisfaction.
Solving Talent Shortage Problems
The cybersecurity industry faces a well-documented talent shortage, making it challenging for organizations to scale their SOC teams. Research from ISC2 indicates the “workforce gap” in the global cybersecurity workforce grew larger last year with fewer cybersecurity professionals available for hire, while economic factors and cost-saving cutbacks (including hiring freezes and layoffs) made it even harder for organizations to hire and retain talent.
AI-driven alert triage helps bridge this gap by enabling existing teams to handle a much larger volume of alerts with fewer resources. AI empowers analysts to focus on strategic, high-impact activities by automating routine tasks. This allows organizations to maximize the productivity of their current staff without the need for constant expansion to keep up with rising alert volumes.
Streamlining Incident Investigation and Accelerating MTTD/MTTR
Speed is crucial in cybersecurity, where the mean time to detect (MTTD) and respond (MTTR) to threats can mean the difference between a minor incident and a major breach. AI significantly accelerates these processes by quickly analyzing and triaging alerts, ensuring that only the most relevant and severe threats are escalated to human analysts. This rapid identification and prioritization enable faster incident response, reducing the window of vulnerability and minimizing potential damage.
Automatically Prioritizing Alerts and Auto-Resolving False Positives
One of the most frustrating aspects of manual alert triage is the high volume of false positives that analysts must sift through. AI addresses this by automatically prioritizing alerts and filtering out those that are non-threatening. Using machine learning and historical data, AI can accurately distinguish between true threats and false positives, ensuring that analysts’ time is spent on real security issues. This not only streamlines the triage process but also enhances the overall accuracy and efficiency of the SOC.
3. Augmenting Threat Hunting
AI is also revolutionizing the way security teams conduct threat hunting. With the advent of AI-powered chatbots like Microsoft Copilot, CrowdStrike’s Charlotte, and SentinelOne’s PurpleAI, security analysts can dramatically accelerate threat hunting and in-depth investigations. These tools enable analysts to create complex queries and pivot investigations using simple natural language, making the process faster and more intuitive. Additionally, several SIEM platforms have introduced AI capabilities that allow users to generate queries and rules through natural language, further simplifying and speeding up the threat-hunting process. By leveraging these AI tools, security teams can uncover sophisticated threats more efficiently and with greater accuracy.
4. Accelerating Malware Analysis
Modern cyber threats increasingly come in the form of text-based scripts, such as command lines, VBS scripts, Python scripts, PowerShell commands, and malicious emails. These are perfect candidates for AI-driven analysis, particularly with the use of Large Language Models (LLMs) like ChatGPT. These models can quickly analyze, understand, and summarize the nature of these scripts, answering the critical questions of “what this is” and “is it bad” within seconds.
While some scripts may need to be deobfuscated before being fed into an LLM, the ability to rapidly reverse engineer and understand these scripts has previously been a significant challenge. However, it’s important to note that AI’s capabilities are currently limited to text-based analysis — for thorough analysis, compiled software and binary code also require the use of reverse engineering techniques.
How Intezer Can Help You Leverage AI for Security Automation
Intezer’s Autonomous SOC solution is designed to empower your security team by automating the alert triage process, enhancing your ability to detect, prioritize, and respond to threats efficiently. Our solution integrates advanced AI and machine learning technologies to automatically analyze and categorize alerts, drastically reducing the manual workload on your analysts.
Here’s how it works: Intezer’s Autonomous SOC continuously monitors your environment, using AI to triage every alert at a granular level. The system intelligently filters out false positives, escalates only the most critical threats, and provides detailed context and recommendations for further action. This automation accelerates your Mean Time to Detect (MTTD) and Mean Time to Respond (MTTR), ensuring that your team can respond to threats faster and with greater accuracy.
AI as a Practical Tool for the Modern SOC
AI is not a futuristic concept anymore. We have multiple types of AI available now with real-world use cases. Ultimately, AI is a practical and powerful tool that security teams can leverage today.
By enhancing threat detection, augmenting threat hunting, automating alert triage, and accelerating malware analysis, AI helps SOCs operate more efficiently and effectively. As cyber threats continue to evolve, integrating AI into your security strategy is not just beneficial — it’s essential. To see how AI can transform your SOC, consider exploring Intezer’s Autonomous SOC solution, designed to mimic the expertise of seasoned security analysts and enhance your team’s capabilities.
Ready to automate your security operations?
Book a demo to see what Intezer can do for your SOC.
The post AI in Action: Top 4 Ways Security Teams Can Leverage AI Today appeared first on Intezer.
Article Link: AI in Action: Top 4 Ways Security Teams Can Leverage AI Today
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Artificial intelligence (AI) has become an indispensable tool for security teams in today’s fast-paced cybersecurity landscape. From detecting threats to automating routine tasks, AI has already and continues to transform how Security Operations Centers (SOCs) work, making them more efficient and effective.
Here, we explore the top four ways security teams can leverage AI to enhance their cybersecurity efforts.
1. Enhancing Threat Detection
Chances are, if you’re using modern threat detection systems like Endpoint Detection and Response (EDR), Network Detection and Response (NDR), or Security Information and Event Management (SIEM) platforms, you’re already leveraging AI. Most next-gen detection tools come equipped with built-in AI and machine learning capabilities that significantly improve detection rates and identify previously unknown threats. AI enhances these systems’ ability to sift through vast amounts of data, pinpoint anomalies, and flag potential threats that might go unnoticed by traditional methods. By integrating AI into your detection arsenal, you’re not just reacting to threats but proactively identifying and mitigating them before they can cause harm.
2. Automating Alert Triage with AI
Automating alert triage with AI is a game-changer for Security Operations Centers (SOCs), addressing some of the most pressing challenges security teams face today. By integrating Autonomous SOC systems that function like an extension of your team, SOCs can enhance their efficiency, accuracy, and overall security posture. Here’s a closer look at the four main benefits of integrating around-the-clock AI analysts for triage:
Reducing Analyst Burnout
Teams need good security analysts more than ever. But the constant influx of security alerts can overwhelm even the most seasoned analysts, leading to alert fatigue and burnout. AI alleviates this burden by automating the initial triage process. By automatically sorting and prioritizing alerts based on severity, AI Analysts ensure that our human analysts stay focused on the most critical issues. This not only reduces the manual effort required but also allows analysts to engage in more meaningful and less repetitive work, decreasing burnout and improving job satisfaction.
Solving Talent Shortage Problems
The cybersecurity industry faces a well-documented talent shortage, making it challenging for organizations to scale their SOC teams. Research from ISC2 indicates the “workforce gap” in the global cybersecurity workforce grew larger last year with fewer cybersecurity professionals available for hire, while economic factors and cost-saving cutbacks (including hiring freezes and layoffs) made it even harder for organizations to hire and retain talent.
AI-driven alert triage helps bridge this gap by enabling existing teams to handle a much larger volume of alerts with fewer resources. AI empowers analysts to focus on strategic, high-impact activities by automating routine tasks. This allows organizations to maximize the productivity of their current staff without the need for constant expansion to keep up with rising alert volumes.
Streamlining Incident Investigation and Accelerating MTTD/MTTR
Speed is crucial in cybersecurity, where the mean time to detect (MTTD) and respond (MTTR) to threats can mean the difference between a minor incident and a major breach. AI significantly accelerates these processes by quickly analyzing and triaging alerts, ensuring that only the most relevant and severe threats are escalated to human analysts. This rapid identification and prioritization enable faster incident response, reducing the window of vulnerability and minimizing potential damage.
Automatically Prioritizing Alerts and Auto-Resolving False Positives
One of the most frustrating aspects of manual alert triage is the high volume of false positives that analysts must sift through. AI addresses this by automatically prioritizing alerts and filtering out those that are non-threatening. Using machine learning and historical data, AI can accurately distinguish between true threats and false positives, ensuring that analysts’ time is spent on real security issues. This not only streamlines the triage process but also enhances the overall accuracy and efficiency of the SOC.
3. Augmenting Threat Hunting
AI is also revolutionizing the way security teams conduct threat hunting. With the advent of AI-powered chatbots like Microsoft Copilot, CrowdStrike’s Charlotte, and SentinelOne’s PurpleAI, security analysts can dramatically accelerate threat hunting and in-depth investigations. These tools enable analysts to create complex queries and pivot investigations using simple natural language, making the process faster and more intuitive. Additionally, several SIEM platforms have introduced AI capabilities that allow users to generate queries and rules through natural language, further simplifying and speeding up the threat-hunting process. By leveraging these AI tools, security teams can uncover sophisticated threats more efficiently and with greater accuracy.
4. Accelerating Malware Analysis
Modern cyber threats increasingly come in the form of text-based scripts, such as command lines, VBS scripts, Python scripts, PowerShell commands, and malicious emails. These are perfect candidates for AI-driven analysis, particularly with the use of Large Language Models (LLMs) like ChatGPT. These models can quickly analyze, understand, and summarize the nature of these scripts, answering the critical questions of “what this is” and “is it bad” within seconds.
While some scripts may need to be deobfuscated before being fed into an LLM, the ability to rapidly reverse engineer and understand these scripts has previously been a significant challenge. However, it’s important to note that AI’s capabilities are currently limited to text-based analysis — for thorough analysis, compiled software and binary code also require the use of reverse engineering techniques.
How Intezer Can Help You Leverage AI for Security Automation
Intezer’s Autonomous SOC solution is designed to empower your security team by automating the alert triage process, enhancing your ability to detect, prioritize, and respond to threats efficiently. Our solution integrates advanced AI and machine learning technologies to automatically analyze and categorize alerts, drastically reducing the manual workload on your analysts.
Here’s how it works: Intezer’s Autonomous SOC continuously monitors your environment, using AI to triage every alert at a granular level. The system intelligently filters out false positives, escalates only the most critical threats, and provides detailed context and recommendations for further action. This automation accelerates your Mean Time to Detect (MTTD) and Mean Time to Respond (MTTR), ensuring that your team can respond to threats faster and with greater accuracy.
AI as a Practical Tool for the Modern SOC
AI is not a futuristic concept anymore. We have multiple types of AI available now with real-world use cases. Ultimately, AI is a practical and powerful tool that security teams can leverage today.
By enhancing threat detection, augmenting threat hunting, automating alert triage, and accelerating malware analysis, AI helps SOCs operate more efficiently and effectively. As cyber threats continue to evolve, integrating AI into your security strategy is not just beneficial — it’s essential. To see how AI can transform your SOC, consider exploring Intezer’s Autonomous SOC solution, designed to mimic the expertise of seasoned security analysts and enhance your team’s capabilities.
Ready to automate your security operations?
Book a demo to see what Intezer can do for your SOC.
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Article Link: AI in Action: Top 4 Ways Security Teams Can Leverage AI Today
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