AI Security
Learn how to secure AI models and the cloud systems that support them. These articles explore emerging risks, evolving attack techniques, and the safeguards teams use to protect models, pipelines, and inference workflows — while also showing how AI can boost core security operations.
AI Data Classification: Definition and Process Explained
Team di esperti Wiz
AI data classification is the process of using machine learning to automatically sort and label data based on its content and sensitivity.
AI-BOM: Building an AI Bill of Materials
An AI bill of materials (AI-BOM) is a complete inventory of all the assets in your organization’s AI ecosystem. It documents datasets, models, software, hardware, and dependencies across the entire lifecycle of AI systems—from initial development to deployment and monitoring.
Dark AI Explained
Team di esperti Wiz
Dark AI involves the malicious use of artificial intelligence (AI) technologies to facilitate cyberattacks and data breaches. Dark AI includes both accidental and strategic weaponization of AI tools.
AI runtime security in the cloud: Secure your AI when it matters most
AI runtime security safeguards your AI apps, models, and data during active operation. Going beyond traditional security’s focus on static pre-deployment analysis, runtime security monitors AI behavior at inference while it actively processes user requests and sensitive data.
Securing Agentic AI: What Cloud Teams Need to Know
Agentic AI security protects AI systems that autonomously make decisions, use tools, and take action in live environments. Agentic AI doesn't just answer questions—it acts on them.
AI Governance: 85% of Orgs Use AI, but Security Lags
AI governance is trailing behind adoption, leaving organizations vulnerable to emerging threats. Learn best practices for securing your cloud environment.
AI Compliance in 2025: Definition, Standards, and Frameworks
AI compliance standards are changing fast, yet 85% of organizations still use AI tools. Get best practices and frameworks to protect your cloud environment.
Generative AI Security: Risks & Best Practices
Team di esperti Wiz
Generative AI (GenAI) security is an area of enterprise cybersecurity that zeroes in on the risks and threats posed by GenAI applications. To reduce your GenAI attack surface, you need a mix of technical controls, policies, teams, and AI security tools.
LLM Security for Enterprises: Risks and Best Practices
Team di esperti Wiz
LLM models, like GPT and other foundation models, come with significant risks if not properly secured. From prompt injection attacks to training data poisoning, the potential vulnerabilities are manifold and far-reaching.
Essential AI Security Best Practices
To manage risks associated with AI, organizations need a strategic and well-coordinated security approach that extends traditional cybersecurity measures to the unique needs of AI.
7 AI Security Tools to Prepare You for Every Attack Phase
Learn the main advantages and limitations of 7 popular AI security tools. Plus, see the top criteria for choosing a tool to secure your AI and ML applications.
Model Context Protocol Security
MCP acts as a universal security control plane that standardizes policy enforcement across enterprise AI workflows.
AI Security: Using AI Tools to Protect Your AI Systems
Team di esperti Wiz
AI security involves using AI tools for cybersecurity and protecting your AI systems themselves. Learn how to do both to mitigate evolving AI security risks.
What is a Prompt Injection Attack?
Prompt injection attacks are an AI security threat where an attacker manipulates the input prompt in natural language processing (NLP) systems to influence the system’s output.
ChatGPT Security for Enterprises: Risks and Best Practices
ChatGPT security is the process of protecting an organization from the compliance, brand image, customer experience, and general safety risks that ChatGPT introduces into applications.
Data Poisoning: Current Trends and Recommended Defense Strategies
Team di esperti Wiz
Data poisoning threatens the cloud, especially when 70% of cloud environments use AI services. Learn about the top threats and how to protect your organization.
AI Security Solutions in 2025: Tools to secure AI
Team di esperti Wiz
In this guide, we'll help you navigate the rapidly evolving landscape of AI security best practices and show how AI security posture management (AI-SPM) acts as the foundation for scalable, proactive AI risk management.
How AI is Transforming Cloud Security (and how you can leverage it)
Team di esperti Wiz
AI is transforming cloud security operations by enabling real-time threat detection, automated response, and predictive risk analysis, helping teams stay ahead of attackers.
AI-Powered SecOps: A Brief Explainer
Team di esperti Wiz
In this article, we’ll discuss the benefits of AI-powered SecOps, explore its game-changing impact across various SOC tiers, and look at emerging trends reshaping the cybersecurity landscape.
7 Serious AI Security Risks and How to Mitigate Them
There are many sneaky AI security risks that could impact your organization. Learn practical steps to protect your systems and data while still leveraging AI's benefits.
AI Threat Detection Explained
AI threat detection uses advanced analytics and AI methodologies such as deep learning (DL) and natural language processing (NLP) to assess system behavior, identify abnormalities and potential attack paths, and prioritize threats in real time.
What is AI Red Teaming?
Team di esperti Wiz
Traditional security testing isn’t enough to deal with AI's expanded and complex attack surface. That’s why AI red teaming—a practice that actively simulates adversarial attacks in real-world conditions—is emerging as a critical component in modern AI security strategies and a key contributor to the AI cybersecurity market growth.
AWS AI Security: Securing AI workloads on AWS
AWS offers a complete, scalable suite for AI that covers everything from data prep to model deployment, making it easier for developers to innovate quickly.
The role of Kubernetes in AI/ML development
In this blog post, you’ll discover how Kubernetes plays a crucial role in AI/ML development. We’ll explore containerization’s benefits, practical use cases, and day-to-day challenges, as well as how Kubernetes security can protect your data and models while mitigating potential risks.
AI/ML in Kubernetes Best Practices: The Essentials
Our goal with this article is to share the best practices for running complex AI tasks on Kubernetes. We'll talk about scaling, scheduling, security, resource management, and other elements that matter to seasoned platform engineers and folks just stepping into machine learning in Kubernetes.
The AI Bill of Rights Explained
Team di esperti Wiz
The AI Bill of Rights is a framework for developing and using artificial intelligence (AI) technologies in a way that puts people's basic civil rights first.
What is AI-SPM? [AI Security Posture Management]
AI-SPM (AI security posture management) is a new and critical component of enterprise cybersecurity that secures AI models, pipelines, data, and services.
NIST AI Risk Management Framework: A tl;dr
Team di esperti Wiz
The NIST AI Risk Management Framework (AI RMF) is a guide designed to help organizations manage AI risks at every stage of the AI lifecycle—from development to deployment and even decommissioning.
What is Shadow AI? Why It's a Threat and How to Embrace and Manage It
Team di esperti Wiz
Shadow AI is the unauthorized use or implementation of AI that is not controlled by, or visible to, an organization’s IT department.
The EU Artificial Intelligence Act: A tl;dr
Team di esperti Wiz
In this post, we’ll bring you up to speed on why the EU put this law in place, what it involves, and what you need to know as an AI developer or vendor, including best practices to simplify compliance.
Will AI Replace Cybersecurity? Exploring AI’s Evolving Role in Security
Team di esperti Wiz
The short answer is no, AI is not expected to replace cybersecurity or take cybersecurity jobs. It will, however, augment cybersecurity with new tools, methods, and frameworks.
AI Data Security: Key Principles and Best Practices
AI data security is a specialized practice at the intersection of data protection and AI security that’s aimed at safeguarding data used in AI and machine learning (ML) systems.
AI Risk Management: Essential AI SecOps Guide
AI risk management is a set of tools and practices for assessing and securing artificial intelligence environments. Because of the non-deterministic, fast-evolving, and deep-tech nature of AI, effective AI risk management and SecOps requires more than just reactive measures.
The Threat of Adversarial AI
Team di esperti Wiz
Adversarial artificial intelligence (AI), or adversarial machine learning (ML), is a type of cyberattack where threat actors corrupt AI systems to manipulate their outputs and functionality.
What is LLM Jacking?
LLM jacking is an attack technique that cybercriminals use to manipulate and exploit an enterprise’s cloud-based LLMs (large language models).