Cloud security teams are facing an increasing number of risks due to the complex and dynamic nature of cloud environments. Prioritizing and remediating these vulnerabilities and vulnerabilities before threat actors are able to exploit them is a major challenge given the number of alerts security teams must deal with, and the ongoing cyber talent shortage.
Microsoft’s State of Multicloud Security Report 2024 found that 65% of repositories contained source code vulnerabilities, which lasted 58 days on average. This represents a large window of time for threat actors to exploit existing vulnerabilities to outsource, control, or compromise critical cloud services.
Security teams are also faced with expanding attack surfaces due to the rapid adoption of AI. Not only are threat actors creating new attack vectors that specifically target AI, but organizations are also adopting AI without proper visibility or security controls in place to protect AI workloads. More than three-quarters (78%) of employees have used AI tools that have not been proven by their organization, opening their companies to additional risk as these tools are not monitored by internal security teams.
Security professionals need a better way to identify and remediate vulnerabilities before malicious actors can take advantage of them. One solution is the cloud application security platform (CNAPP)—an all-in-one platform that integrates security and compliance capabilities across the full cloud lifecycle to prevent, detect, and respond to cloud security threats. When integrated as part of CNAPP, AI-enabled workflows can act as the last missing piece of the puzzle to speed up turnaround times and improve security team efficiency.
It explores the use cases of AI-powered cloud security
AI can be an invaluable tool for improving cloud security, especially when it comes to speeding up risk assessment and remediation across multiple cloud environments.
For example, cloud security vulnerabilities are often multifaceted and require security teams to analyze multiple data points to find the root of the problem. While CNAPP can help provide greater visibility and contextualization by correlating information across cloud security solutions, AI takes this capability to the next level by quickly and accurately thinking 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 data points at once to quickly identify root vulnerabilities and provide recommended remediation. This not only ensures improved accuracy but also accelerates human defenders’ ability to assess and remediate cloud-based threats—giving teams the ability to quickly fix problems and prevent potential security breaches.
Additionally, because CNAPP integrates security and compliance capabilities across the full lifecycle of an application, AI can also scan developer code and runtime environments to anticipate risks before they are exploited. This can greatly strengthen a cloud security company’s position by giving it the ability to address existing vulnerabilities and prevent them from reoccurring.
Similarly, AI-powered workflows within CNAPP can help prioritize incoming alerts on active attacks so security teams can ensure they are protecting what matters most. This allows security teams to better identify, investigate, and respond to active threats in near real time. After an attack has been detected and resolved, AI can then be used to investigate the incident and issue high-level reports that explain what happened, where the attack started, and how it was contained. Collecting and organizing this information can be a manual process, so automated incident reporting is another way to reduce the burden on already overburdened security teams.
The future of AI-enabled tools in cloud security
The future of AI-powered tools in cloud security is rapidly emerging. Currently, many powerful AI tools act as assistants to human defenders, helping them to assess and respond to threats more effectively. However, the next phases of AI-powered security tools will likely shift to automated solutions and, eventually, autonomous AI agents that can work independently alongside human teams. These agents will not only help assess vulnerabilities and analyze the impact of attacks, they will also make autonomous decisions and perform remedial actions without affecting the business—changing the way cloud security is managed.
As cloud security teams look to improve their performance in the changing threat landscape, it’s important that they learn how to properly scale AI-enabled security tools within their organization while the technology is still evolving. By starting small and experimenting with specific use cases and pre-tested tools from trusted vendors, security teams can control the pace of innovation while 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 in their environment will be better prepared to manage risks and strengthen their cloud security posture.
Because Additional Information for Microsoft’s CNAPP solution, Microsoft Defender for Cloud, visit the Microsoft cloud security solutions page.
It depends check latest AI-powered tools in Defender for Cloud, check out Copilot for Security in Defender for Cloud.
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