In recent years, the advancement of artificial intelligence (AI) technology has brought about significant improvements in various industries. One area that has seen notable progress is the use of AI to add context to the chaos within cybersecurity as the volume and complexity of cyberattacks continue to increase. 

At the forefront of harnessing AI's potential to enhance cybersecurity measures, is Microsoft. The company’s long-standing commitment to AI research and development – and collaboration with Open AI – in the past 4-5 years has been instrumental in driving innovation in the field of AI. Microsoft has been actively incorporating AI technology into various aspects of its operations, including Bing search engine, GitHub coding tools, Microsoft 365 productivity bundle, Azure cloud platform, and even a GRC angle with Purview

One of the recent groundbreaking advancements for AI is the introduction of Microsoft Security Copilot, which was launched on May 28th, 2023. Along with that, Microsoft is also putting forward Purview. Both Security Copilot and Purview have their own focus on major challenges companies face within cyber.

  Related Webinar:    The Impact of AI on the Cybersecurity Landscape



Example Applications of AI in Cybersecurity

Microsoft Security Copilot – Using AI for Defending at Machine Speed

“Microsoft Security Copilot is the first security product to enable defenders to move at the speed and scale of AI. Security Copilot combines this advanced large language model (LLM) with a security-specific model from Microsoft. This security-specific model in turn incorporates a growing set of security-specific skills and is informed by Microsoft’s unique global threat intelligence and more than 65 trillion daily signals. Security Copilot also delivers an enterprise-grade security and privacy-compliant experience as it runs on Azure’s hyperscale infrastructure.” Press Release

In addition, Security Copilot also integrates with the end-to-end Microsoft Security products. Over time, it will expand to a growing ecosystem of third-party products. So, in short, Security Copilot is not only a large language model, but rather a system that learns, to enable organizations to truly defend at machine speed.

So, why was Microsoft Security Copilot created?

In a nutshell, the core essence of security is about people. The key to effective security lies in empowering and supporting individuals to complete their jobs with greater efficiency, accuracy, and ease. That is where Security Copilot comes in. 

  • Accelerate incident investigation and response. – Copilot uses natural language-based investigation to offer context into each security event as well as step-by-step guidance on how to investigate and respond to a given security event.

  • Catch what others miss. – Attackers conceal themselves in noise and weak signals. Now, Defenders can uncover hidden malicious behavior and threat signals that would otherwise go undetected. Security Copilot identifies and prioritizes real-time threats while predicting attackers' next moves using Microsoft's global threat intelligence while also incorporating security analysts' expertise in threat hunting, incident response, and vulnerability management.

  • Address the talent gap. – A security team’s capacity will always be limited by the team’s size and the natural limits of human attention. Security Copilot boosts defenders' skills by answering security-related questions and providing guidance. It learns and adapts to enterprise preferences, supports learning for new team members, and enables security teams to achieve more secure outcomes with fewer resources, operating like larger organizations.

Source: Introducing Microsoft Security Copilot: Empowering Defenders at the Speed of AI


Microsoft Purview – Using AI for GRC Challenges

As AI continues to evolve, its role in cybersecurity is poised to become even more significant and transformative. One area where AI can make a substantial impact is in the integration of Governance, Risk, and Compliance (GRC) practices into the security stack.

In the context of Microsoft's security landscape, Purview, their GRC platform, plays a pivotal role. Purview provides a unified and holistic view of an organization's risk and compliance posture, leveraging AI to automate processes, streamline workflows, and provide actionable insights. By integrating Purview into their security operations, businesses can strengthen their cybersecurity defenses and effectively manage risks.

However, realizing the full potential of AI in cybersecurity requires ongoing development and collaboration. It is essential for organizations, AI researchers, and security professionals to work together to address the limitations and challenges associated with AI integration. This collaborative effort will drive innovation, refine AI algorithms, and push the boundaries of what AI can achieve in enhancing cybersecurity.

At the end of the day, what does cybersecurity in AI mean? If you were to ask Microsoft, their position is clear: By harnessing the power of AI, organizations can stay ahead of evolving threats and mitigate risks more effectively.

And this development raises two important considerations – what are the advantages and what are the potential risks of AI in cybersecurity?



Dual Perspectives: Positive Applications and Potential Risks of AI in Cybersecurity

The introduction of Microsoft Security Copilot has sparked discussions and raised important questions about the benefits, risks, and limitations of AI in the context of cybersecurity. 

Positive Applications of AI in Cybersecurity  

Think of AI like drinking Red Bull vs. tea – AI can help cybersecurity professionals run at 100 miles an hour.

  • Transforming Security Operations Centers (SOCs): In the early stages of its implementation, AI can transform SOCs by consolidating and analyzing disparate data sources, uncovering blind spots that were previously undetectable. 

  • Enabling more efficient threat detection and response: AI has the ability to handle low-level alerts and understand detection rules and correlations. When trained appropriately, AI can be highly effective in analyzing and responding to such alerts, streamlining the process and enabling more efficient threat detection and mitigation.

  • Increasing incident response speed: A key positive factor of AI in cybersecurity is that it can expedite incident response by identifying anomalies in real-time, writing scripts faster, and helping to create response plans promptly. With AI's speed and efficiency, organizations can stay one step ahead of potential threats, giving them more than just a leg up against attackers.

  • Leveling the playing field between companies: AI has the potential to enable small businesses to approach cybersecurity in a way that was once only accessible to large enterprises with enormous cyber budgets. For instance, AI can bridge the gap between business risk managers and IT personnel, enabling a better understanding of fraud detection in insurance or other specific industry requirements. Moreover, geographical considerations, such as privacy laws, influence how AI is implemented and regulated in different regions.

These solutions offer increased efficiency, improved accuracy, and enhanced decision-making capabilities. By harnessing the power of AI, organizations can achieve significant improvements in various domains, such as day-to-day customer service, threat intelligence data analysis, and resource optimization.


Potential Risks of AI in Cybersecurity  

When there is good, there is also the potential for bad. This is especially true when it comes to AI in cybersecurity, as its implementation brings certain risks that need to be carefully considered, such as:

  • The malicious use of AI: Now that AI technology is more accessible, it is also within reach of threat actors. And as many of us are aware, threat actors are known to adapt very quickly to advancements in technology as they have already started implementing AI to enhance their malicious activities. AI has empowered threat actors with new capabilities, such as automated reconnaissance, intelligent evasion techniques, and more sophisticated social engineering. This enables them to launch highly targeted and effective cyberattacks. The reality is that organizations risk their own security by not adopting AI in this day and age – it is like bringing a knife to a gunfight. 

  • The ease of AI-generated ransomware code: In a recent Avertium case study, two Cyber Response Unit (CRU) members were able to successfully instruct ChatGPT to write ransomware code – proving the astounding potential of the AI platform. However, it is important to note that AI code generation cannot be done with such ease when there are mixed coding languages. While AI models have shown promise in generating code snippets, the task becomes considerably more complex on the development side to fix it which can be counterintuitive. 


Limitations of AI in Cybersecurity  

In cybersecurity, you are not fighting machines – you are fighting humans. 

  • The loss of human touch: While AI offers numerous benefits, there is a concern about becoming overly reliant on it and potentially losing the human touch. A worry that expert researchers have is that people may become complacent or blindly follow AI recommendations without critical thinking. This concern has already arisen during testing on a couple of occasions. To address this, a "trust but verify" approach is necessary, where humans and machines work together. It is crucial to maintain focus until the AI model reaches a high level of accuracy, such as 99.99%. Before complete reliance, rigorous testing, similar to other systems, is required to ensure reliability and mitigate risks.
  • The need for human touch: AI will generate a lot of efficiency gains, but AI is not human and those threat actors are the humans we need to protect against. Humans possess critical skills such as intuition, creativity, and critical thinking that complement AI's analytical power. Additionally, human analysts can provide contextual understanding, adapt to new and complex threats, and make judgment calls in uncertain situations. Ultimately, a collaborative approach that combines the strengths of AI and human expertise is necessary to tackle the evolving challenges in cybersecurity. 

Conclusion: The Future of AI in Cybersecurity is Maximum Efficiency

Over the next 6-12 months, AI is expected to provide operational efficiency, with refined models and improved applications (such as detection and automation). As the technology matures, it will continue to disrupt the security landscape.

In the long term, AI has the potential to revolutionize predictive modeling, address complex scientific challenges, and enable accurate demand forecasting, among many other possibilities. But for now, organizations should not rely on AI to fully comprehend and make accurate or even unbiased decisions – instead, organizations can rely on AI to improve their cybersecurity operations and detection capabilities.  


Partnering for Success

In a recent webinar with Avertium’s Chief Revenue Office, Ben Masino, Microsoft’s Corporate Vice President, Kelly Bissell shares his advice on how organizations can start implementing AI into their cybersecurity operations today. 

  1. Learn up on AI: Think about how your organization’s environment fits with AI and what it can do for you, your team, and the overall company.

  2. Test the AI in your environment: Go ahead and evaluate your organization’s internal controls to make sure they are up-to-date and in good standing. It is highly recommended that organizations work with a partner, such as Avertium, to help answer the questions: “Are we prepared?” and “Are we ready to get AI?”

  3. Develop scenarios of AI work: It is important to identify the specific problems your organization wants to solve or improve to consider how your environment can integrate with AI effectively. 

Implementing AI within a cybersecurity framework requires careful planning and collaboration. Organizations should work closely with Microsoft trusted partners, such as Avertium, to navigate access controls, integrate AI into existing security tools, and ensure a secure deployment. By leveraging partnerships, businesses can effectively utilize AI capabilities to augment their security operations.







This document and its contents do not constitute, and are not a substitute for, legal advice. The outcome of a Security Risk Assessment should be utilized to ensure that diligent measures are taken to lower the risk of potential weaknesses be exploited to compromise data.

Although the Services and this report may provide data that Client can use in its compliance efforts, Client (not Avertium) is ultimately responsible for assessing and meeting Client's own compliance responsibilities. This report does not constitute a guarantee or assurance of Client's compliance with any law, regulation or standard.



Avertium is a cyber fusion company with a programmatic approach to measurable cyber maturity outcomes. Organizations turn to Avertium for end-to-end cybersecurity solutions that attack the chaos of the cybersecurity landscape with context. By fusing together human expertise and a business-first mindset with the right combination of technology and threat intelligence, Avertium delivers a more comprehensive approach to cybersecurity. 

That's why over 1,200 mid-market and enterprise-level organizations across 15 industries turn to Avertium when they want to be more efficient, more effective, and more resilient when waging today's cyber war. 

Avertium. Show No Weakness.®


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