Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

GPT-5 Realizes its Mistake...

Can GPT-5 Write SAFE Code?

The Data Problem: Why LLM Security Is So Complex Large language models are trained on terabytes of data, but what happens when that data is flawed? In this video, A10 Networks' security experts, Jamison Utter, Madhav Aggarwal, and Diptanshu Purwar, discuss a critical, often-overlooked aspect of AI security: the training data itself. They explain that LLMs are inseparable from the data they're trained on, which means if the data contains biases, toxic content, or other vulnerabilities, those flaws are vulnerable to exploitation by attackers.

On this episode of the Cybersecurity Defenders Podcast we speak with Peter Ruta, Founder / CEO, Arcanna.ai.

In this demo, we will look at three different use cases for the AI Security Assistant including general security knowledge, ticket context and data visualization.

Examine the function of AI in security tools, and how this double-edged sword can be used for good or ill in the cybersecurity sphere. Plus, see its integration into an identity fabric and get a glimpse into its responsible use – paired with the human element – in One Identity Safeguard.

GPT-5 Made Up its Own Language...

Securing AI and LLMs: A New Security Paradigm When interacting with AI tools like ChatGPT, it's clear that there's a thought process behind their responses. But what happens when an attacker hijacks that process? In this clip from "Securing AI Part 2: What Makes Protecting AI a Unique Challenge?", A10 Networks' security leaders — Jamison Utter, Madhav Aggarwal, and Diptanshu Purwar — discuss this new security paradigm.