Traditional cloud defenses fall short against modern threats

Cloud security is facing unprecedented complexity, and enterprises must adopt AI-driven defenses to keep pace with evolving threats, according to Forbes.  

Karan Alang of Versa Networks emphasizes that with global data volumes surpassing 200 zettabytes, half of which will reside in the cloud, traditional rule-based defenses are overwhelmed. Phishing, credential theft, misconfigurations, and ransomware dominate breaches, while billions of signals from APIs, IAM events, logs, and workloads require context-aware interpretation. Large language models provide that layer, detecting anomalies, correlating events, and reasoning about policy drift across environments. Foundational controls remain essential, including least-privilege access, centralized secret management, workload identity federation, and security-as-code. LLMs enhance these by continuously auditing permissions, detecting dormant accounts, and monitoring TLS or certificate risks.

Alang advocates pairing log pipelines with retrieval-augmented AI, using agentic layers for real-time analysis, and enforcing human-in-the-loop governance. The article concludes that resilient cloud defense demands the convergence of cloud-native engineering and explainable LLM intelligence to anticipate threats rather than merely respond.