Cloud security teams are facing a growing number of risks due to the complex and dynamic nature of cloud environments. Prioritizing and remediating these vulnerabilities and misconfigurations before threat actors can exploit them is a significant challenge given the sheer number of alerts that security teams must address, as well as the ongoing cyber talent shortage.
Microsoft’s 2024 State of Multicloud Security Report found that 65% of repositories contained source code vulnerabilities, which remained for 58 days on average. This represents a large window of time for threat actors to leverage existing risks to exfiltrate, manipulate, or otherwise compromise critical cloud resources.
Security teams are also dealing with expanding attack surfaces thanks to the rapid adoption of AI. Not only are threat actors developing new attack vectors that specifically target AI, but organizations are also adopting AI without the proper visibility or security controls in place to protect AI workloads. Over three-quarters (78%) of employees have used AI tools that were not proved by their organization, opening their companies up to increased risk since these tools are not being monitored by internal security teams.
Security practitioners need a better way to identify and remediate risks before threat actors can capitalize on them. One solution is a cloud-native application protection platform (CNAPP)—an all-in-one platform that unifies security and compliance capabilities across the full cloud lifecycle to prevent, detect, and respond to cloud security risks. When integrated as part of a CNAPP, AI-powered workflows can act as the final missing puzzle piece to accelerate remediation times and enhance overall security team effectiveness.
Exploring cloud security use cases powered by AI
AI can be an invaluable tool for enhancing cloud security, particularly when it comes to accelerating risk assessment and remediation across multiple cloud environments.
For example, cloud security risks are often multi-faceted and require security teams to analyze numerous data points to determine the root cause of the issue. While a CNAPP can help provide greater visibility and contextualization by correlating insights across all cloud security solutions, AI takes this capability to the next level by quickly and accurately reasoning through complex security issues to determine which issues should be prioritized first.
Rather than asking a human defender to manually sift through data, AI can analyze multiple insights at once to quickly identify the root vulnerability and provide a recommended remediation. This not only ensures increased accuracy but also accelerates human defenders’ ability to assess and remediate cloud-based risks—empowering teams to proactively fix issues and prevent a potential security breach.
Additionally, because a CNAPP unifies security and compliance capabilities across the full application lifecycle, AI can also scan developer code and runtime environments to proactively identify risks before they’re exploited. This can massively strengthen a company’s cloud security posture by empowering them to address their existing vulnerabilities and prevent them from re-occurring.
Similarly, AI-powered workflows within a CNAPP can help prioritize incoming alerts on active attacks so security teams can ensure they’re defending what matters most. This allows security teams to better detect, investigate, and respond to active threats in near-real-time. After the attack has been detected and resolved, AI can also be used to investigate the incident and generate executive-level incident reports detailing what happened, where the attack originated, and how it was contained. Collecting and organizing this information can be a highly manual process, so automating incident reporting is another way to lighten the load for already overburdened security teams.
The future of AI-powered tools in cloud security
The future of AI-powered toolsin cloud security is evolving rapidly. Currently, most AI-powered tools act as assistants to human defenders, helping them assess and respond to threats more efficiently. However, the next stages of AI-powered security tools will likely transition into semi-automated solutions and, eventually, fully autonomous AI agents that can operate independently alongside human teams. These agents will not only help assess risks and analyze attack impacts, they will also autonomously make decisions and perform remediation tasks without affecting the business—revolutionizing the way cloud security is managed.
As cloud security teams look to enhance their effectiveness in an evolving threat landscape, it’s imperative they learn how to properly scale AI-powered security tools within their organization while the technology is still relatively nascent. By starting small and experimenting with specific use cases and pre-vetted tools from trusted vendors, security teams can control the pace of innovation while still seizing the current AI opportunity at hand.
As cloud applications continue to grow more complex and dynamic, organizations that have adopted and tested AI assistants within their environment will be better prepared to manage risk and strengthen their cloud security posture.
For more information on Microsoft’s CNAPP solution, Microsoft Defender for Cloud, visit the Microsoft cloud security solutions page.
To explore the latest AI-powered tools in Defender for Cloud, check out Copilot for Security in Defender for Cloud.
