Cloud Security plays a crucial role in the field of information security operations, handling much of the heavy lifting needed to protect systems and data. Starting in 2016, the security industry recognized that scaling security operations effectively required the integration of artificial intelligence. This awareness led to the emergence of new AI tools specifically designed for enhancing security operations. While AI has been around in this space for some time, the advancements in Generative AI are revolutionizing the landscape. With these improvements, the future of security operations looks promising and robust thanks to Gen AI.
Why is Artificial Intelligence not new in Cloud Security Operation?
AI’s role in security operations is certainly not a recent development but it has been evolving for quite some time. A notable example is the rise of Cloud Security Posture Management (CSPM) tools, which have been actively identifying and addressing security configuration issues in cloud environments for years.
These tools typically function either through an agentless scanning approach for cloud workload scans or a role-based read access for cloud metadata or configuration management scans. To monitor the cloud assets effectively, these tools require the setup of a role or a programmatic user with read-only access to the cloud environment. This access allows the CSPM tools to gather essential cloud metadata and configuration data. By running periodic scans, they feed this information into their rule engines, which analyze the data to produce actionable security findings.
An example of Metadata or Cloud config scan could be an S3 bucket in your AWS account that allows read access to all the objects via a bucket policy, the tool’s rule engine will detect this vulnerability. It will produce a finding indicating that there is an S3 bucket with insecure policies allowing unrestricted access to all objects within the bucket. This proactive detection helps organizations immediately address potential security risks and enhance their overall cloud security posture.
Conversely, an example of a workload scan could involve a virtual machine running Ubuntu 22.04, where the CSPM tool executes an agentless scan on that VM.
During scans, these tools can evaluate the configuration of cloud assets. For example, they can determine if an asset is completely exposed to the internet without any IP firewall restrictions, if it is an internet-exposed asset with firewall restrictions, or if it is completely non-internet facing. Based on these assessments, the CSPM tool can then decide the severity of the findings, providing organizations with valuable insights to address potential security vulnerabilities
These tools also allow customers to add custom rules or mark certain findings as false positives based on their specific environment. For instance, imagine you have an AWS account and receive a finding indicating that some snapshots or backups are missing encryption. If you have compensating controls in place, you can configure the tool to recognize this finding as a false positive in your environment. Consequently, future findings of this nature will be flagged as false positives, streamlining the review process and reducing unnecessary alerts. While most CSPM platforms today rely on rule-based suppression or manual exceptions for this purpose, some leading tools are starting to incorporate machine learning to generalize from user feedback and automatically suppress similar findings in the future.
Many leading CSPM tools have incorporated AI/ML for risk prioritization and anomaly detection, but traditional rule-based engines are still common. The depth of AI integration in these tools has increased over time, with GenAI being the most recent and transformative advancement. Their ongoing evolution continues to enhance security practices, making them an integral part of an organization’s security strategy.
What’s New and Game Changing: Generative AI & Cloud Security
Generative AI or GenAI is truly changing the game in cloud security operations, making it easier and more intuitive for security teams to work with their tools and data. Imagine you’re a CISO logging into your CSPM tool and, instead of sifting through complicated dashboards, you’re greeted by a friendly chatbot. You simply type, “Show me the users without MFA who have access to my most critical assets.” Within moments, you get a clear list. This is just one way that security tools are beginning to use large language models to let users ask questions in everyday language, simplifying the process tremendously.
Take AskAI from wiz.io, for example. With this feature, security teams can ask natural questions like, “What are the critical risks for my publicly exposed resources?” The GenAI engine takes these prompts and turns them into complex security queries, returning clear, actionable insights in response. This is especially helpful for security analysts who may not have deep expertise in cloud security; now they can get guidance on what actions to take. For instance, by asking, ‘What steps do I need to fix my over-permissive S3 buckets?’ they could get instant, practical advice from AskAI.
Another great example of how GenAI is making an impact is with Microsoft Copilot for Security. This tool acts as a virtual assistant for security analysts, helping them sift through mountains of security data, summarize incidents, suggest ways to respond, and even automatically generate scripts for investigations. Imagine how empowering that is!
With GenAI in the mix, security tools are becoming not just more user-friendly but also incredibly powerful. They’re transforming how teams approach cloud security, making it accessible and manageable for everyone involved.
The Road Ahead: GenAI Shaping the Future of Cloud Security
As we look to the future, cloud security operations are about to get a whole lot smarter and more helpful. Today’s security tools already do a great job of spotting issues and even fixing some of them automatically. But what’s coming next is even more exciting.
Soon, with GenAI, cloud security tools will go beyond simply answering your questions or generating scripts. They will be able to create comprehensive, end-to-end security plans tailored to your unique cloud environment by learning from every interaction and continuously analyzing alerts and behaviors. Instead of just reacting to threats or responding to isolated incidents, these systems will proactively assess your entire cloud landscape, identify evolving risks, and recommend or even orchestrate coordinated defenses across all platforms-no matter how complex your setup is. By anticipating vulnerabilities and adapting to new challenges in real time, GenAI-powered tools will help you stay ahead of threats and ensure your cloud infrastructure remains secure from end to end.
In the coming years, we’ll see security operations become more collaborative, with humans and AI working side by side. GenAI will handle the repetitive and complex tasks, freeing up people to focus on strategy and big picture thinking. The future of cloud security isn’t just about automation but it’s about making security smarter, more intuitive, and accessible for everyone.
About the Author
Ranjan Kathuria has over nine years of experience in the security industry, where he has played a key role in developing and mentoring security engineers for recent employers. Currently, he serves as a Cloud Security Architect at a data security company, where his focus is on safeguarding the cloud environment. Additionally, he is recognized as a top-tier security researcher for HubSpot and Quora’s Bug Bounty Programs on Bugcrowd, contributing to the enhancement of security measures on these platforms.
