Cyber Risk Series: AI & LLM - How Secure are Your Generative Sheep?

As AI and large language models (LLMs) rapidly transform industries, they also introduce new vulnerabilities that traditional cybersecurity methods can't fully address—data leaks, non-compliance, intellectual property theft, and more. In fact, 94% of IT leaders have allocated budgets to safeguard AI in 2024, and this number is expected to rise significantly as AI and LLM adoption continues. The modern attack surface has evolved, making AI and LLMs prime targets for cyberattacks.

In this edition of the Cyber Risk Series, we’ll tackle the most pressing AI security challenges, explore the hidden risks in your AI and LLM workloads, and forecast the 2025 AI security landscape. This event will bring AI security to the forefront, empowering security leaders to defend against emerging threats.

Key topics we’ll cover:
• Full AI & LLM Workload Discovery: How to uncover all your AI and LLM assets, including shadow models that may pose hidden risks.
• AI Vulnerability Management: Strategies for detecting and mitigating risks like prompt injection, jailbreaks, and model theft.
• Risk-Based Prioritization: How to focus on the most critical vulnerabilities in your AI infrastructure using risk-based frameworks.
• Compliance & Legal Protection: Ensuring your AI models comply with data protection regulations like GDPR and CCPA to avoid penalties.

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