AgentWard: A Lifecycle Security Architecture for Autonomous AI Agents

Autonomous AI agents extend large language models into full runtime systems that load skills, ingest external content, maintain memory, plan multi-step actions, and invoke privileged tools. In such systems, security failures rarely remain confined to a single interface; instead, they can propagat...

Uncovering Security Threats and Architecting Defenses in Autonomous Agents: A Case Study of OpenClaw

The rapid evolution of Large Language Models LLMs into autonomous, tool-calling agents has fundamentally altered the cybersecurity landscape. Frameworks like OpenClaw grant AI systems operating-system-level permissions and the autonomy to execute complex workflows. This level of access creates...

Lifecycle-Integrated Security for AI-Cloud Convergence in Cyber-Physical Infrastructure

The convergence of Artificial Intelligence AI inference pipelines with cloud infrastructure creates a dual attack surface where cloud security standards and AI governance frameworks intersect without unified enforcement mechanisms. AI governance, cloud security, and industrial control system...

How Public Container Registries Have Become a Silent Risk Multiplier in a Modern Supply Chain

Key Takeaways Pulling container images from public registries is a trust decision, not a neutral operational step. The impact extends to infrastructure stability, cloud spend, and security risk. Cryptomining is the most common form of malicious abuse in public container images, driven by the ease...

Securing Agentic AI Systems -- a Multilayer Security Framework

Securing Agentic Artificial Intelligence AI systems requires addressing the complex cyber risks introduced by autonomous, decision-making, and adaptive behaviors. Agentic AI systems are increasingly deployed across industries, organizations, and critical sectors such as cybersecurity, finance, an...

New Best Practices Guide for Securing AI Data Released

Today, CISA, the National Security Agency, the Federal Bureau of Investigation, and international partners released a joint Cybersecurity Information Sheet on AI Data Security: Best Practices for Securing Data Used to Train & Operate AI Systems. This information sheet highlights the critical role...

Trend Secures AI Infrastructure with NVIDIA

Together, we are focused on securing the full AI lifecycle—from development and training to deployment and inference—across cloud, data center, and AI factories...

Trend Joins NVIDIA to Secure AI Infrastructure with NVIDIA

Together, we are focused on securing the full AI lifecycle—from development and training to deployment and inference—across cloud, data center, and AI factories...

Offensive Security for AI Systems: Concepts, Practices, and Applications

As artificial intelligence AI systems become increasingly adopted across sectors, the need for robust, proactive security strategies is paramount. Traditional defensive measures often fall short against the unique and evolving threats facing AI-driven technologies, making offensive security an...

[Free Webinar] Guide to Securing Your Entire Identity Lifecycle Against AI-Powered Threats

How Many Gaps Are Hiding in Your Identity System? It's not just about logins anymore. Today's attackers don't need to "hack" in—they can trick their way in. Deepfakes, impersonation scams, and AI-powered social engineering are helping them bypass traditional defenses and slip through unnoticed...