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Using Microsoft Copilot for SEIM Tuning

Microsoft Copilot empowers security professionals to respond rapidly and process signals at machine speed by combining an innovative language model with dedicated capabilities informed by Microsoft's unique global threat intelligence, processing over 78 trillion security signals daily.

Integrating generative AI into security workflows can accelerate response times and accelerate new analyst learning curves, but should never replace training, mentoring, and job shadowing activities.

Use Cases

Microsoft Copilot is an invaluable tool for streamlining workflows and providing recommendations in various applications, from email composing to document drafting. However, its recognition of natural language remains under development; for this reason plugins exist that allow it to access external data like Google Search or Spotify for more precise context.

Connecting security teams with these tools enables them to provide more accurate and detailed context to alerts and notifications in a modern SOC. Analysts can use these tools to quickly identify relevant parameters to monitor, streamlining investigation and response processes and ultimately reducing noise while improving accuracy and accelerating threat management.

Copilot offers additional security-focused features, such as alerting, remediation scenarios and device/file summaries. Furthermore, it integrates seamlessly with existing Microsoft security solutions like Defender XDR, Sentinel and Intune for an exemplary system of protection.

Security Copilot integrates seamlessly with enterprise infrastructure and data sources to provide an in-depth view of security posture in real time. It can also boost internal security team productivity by filling skill gaps and performing ongoing risk analyses; additionally, Security Copilot assists with planning and executing cybersecurity programs - such as training sessions, awareness campaigns and prevention plans - helping teams work more effectively together.

Copilot's foundation language model is constructed on an exclusive proprietary platform combining high-performance hardware and sophisticated AI technologies to form an extremely efficient information processing machine capable of processing large amounts of complex data quickly and securely. Furthermore, this system employs a scalable, secure, and trusted architecture designed to protect sensitive information at all times.

Integration between Microsoft Defender platform and other security products enables organizations to streamline SIEM, XDR and threat intelligence tasks from one central location via Defender portal. Furthermore, Defender works hand in hand with Intune for device protection.

Microsoft Copilot is an integral part of a centralized platform designed to increase efficiency within Security Operations Center staff and eliminate redundant efforts. By seamlessly integrating with existing security tools and processes, this application offers automated alerting, response, investigation and multilingual support features as well as augmenting existing reports.

Map to the MITRE Attack Framework

Copilot is a powerful tool designed to optimize the efficiency of security operations teams. It reduces time it takes to investigate incidents by automatically analyzing alerts with machine speed and providing actionable guidance, saving hours in investigation time for investigations. When combined with other Microsoft tools such as XDR and SIEM, Copilot allows your security operations team to identify cyberthreats faster.

Security teams face an enormous challenge when it comes to detecting and responding to malicious files, with detection often being an impossible feat without advanced protection technology and analytics. Malicious files can quickly bypass protection methods, leading to serious business risks. Check Point's engines provide each file with information regarding an attack's tactics and techniques as well as any correlations with known adversaries (MITRE ATT&CK matrix or known adversaries), so these correlations can be analyzed and search for incidents based on specific attack types or methods allowing security teams to search and investigate incidents related to specific attacks.

This control detects changes to Windows registry and file system artifacts on endpoints, such as software installations or files, such as those caused by updates. Furthermore, it can prevent changes to immutable folders and root files in containers to protect critical data against unauthorised modification. Unfortunately, however, it doesn't offer protection from exploiting sub-techniques of this technique (modifying local filesystem) and therefore is assessed as Minimal.

This control enables you to protect sensitive information and meet compliance requirements by securing Azure production data with strong controls. These include monitoring access to sensitive files, enforcing policies for password strength enforcement and complying with security standards such as HIPAA. Furthermore, it is an effective solution against threats which are difficult to identify with other means.

Enable Generative AI

Generative AI is an emerging technology that can bolster security teams' defenses both now and into the future. Cybercriminals take time planning their attacks against organizations; by simulating how malicious actors attack, Gen AI allows security teams to better recognize them and respond accordingly.

Vendors envision generative AI tools assisting human analysts in performing tedious triage, documentation, and remediation tasks so that more time can be dedicated to investigations and responding accordingly. Generative AI may also translate natural language queries into vendor-specific languages for searches conducted across other security tools as well as quickly prioritize alerts and notifications.

An obstacle associated with generative AI is its reliance on rules and guidelines. Security teams may require to implement several checks and balances in order to trust its function - for instance requiring higher-level analysts to verify recommended actions or setting up detailed logs and audit trails.

Generative AI offers another potential application in data augmentation by creating synthetic data that closely reflects real-world cybersecurity datasets in order to help overcome limitations of underperforming machine learning models. Generative AI can produce such synthetic data by analyzing existing threat actor profiles and then producing new profiles based on any patterns it detects.

Generative AI can also aid organizations by helping to optimize workflows by identifying common roadblocks that impede productivity. If an issue repeatedly arises when training new employees, for instance, then generative AI could suggest ways to modify how an organization delivers its training sessions.

Early generative AI tools will likely do best in environments that are well-planned, consistent and documented, to limit instances in which an AI assistant acts contrary to its reasoning capabilities - for instance if the SecOps team asked its AI assistant to shut down any PC that may contain malware X but it followed this directive by shutting down CEO's computer while giving a presentation before board of directors!

Implementation

Copilot will make an invaluable difference for any security team, but its AI tools become even more effective when combined with other components to form an integrated and comprehensive solution. Defender XDR integrates with Copilot to bolster incident response and threat intelligence tasks with features such as script/code analysis and automated phishing submission resubmission and verification; using all these capabilities together provides device protection, faster threat identification and remediation, improved visibility across security ecosystems and greater protection.

Microsoft Sentinel integrates EDR and SIEM capabilities for improved threat correlation and automated remediation within a security operations center (SOC). When integrated with Defender, Microsoft Sentinel offers comprehensive end-to-end protection that protects devices, prevents data exposure, enhances compliance and auditing functions.

Defender for endpoints provides contextual and visibility into the threat landscape through advanced analytics and granular security events, providing quick investigation, analysis, and response of cyberthreats on attack surfaces with dynamic risk scoring.

Partnership with Copilot also affords MSSP and MSP customers the chance to cut analyst workload by automating many essential tasks - freeing them up for more complex ones. An analyst could save 40 hours annually just by ditching KQL queries or PowerShell scripts altogether in favor of natural language search to find their target data points.

Security teams who utilize natural language text analysis and response for incident analysis and management find using it significantly reduces response times to incidents, providing timely responses to new threats which might otherwise slip by them. This represents an enormous productivity increase for experienced practitioners.

As security teams become familiar with Copilot, its generative AI will assist them with increasingly sophisticated tasks such as writing complex queries or analyzing more sophisticated phishing submissions. Of course, their ability to do these things will still depend on the security skills and knowledge available within their SOC team; hence why investing in cybersecurity training, mentorship, and job shadowing must remain a top priority.

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