Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

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.

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.

A10's Carlo Alpuerto speaks with Beau Hamilton from SourceForge discussing the high-level SaaS deployment of the ThreatX platform. He explains that with this model, the ThreatX SOC team handles the deployment and management on behalf of the customer, taking a significant load off their plates.

A10's ThreatX: API & Application Protection at the Edge A10's Carlo Alpuerto discusses how ThreatX provides comprehensive protection for APIs and applications at the edge. He explains that while the company offers a SaaS-first approach, the solution can be deployed on-premise, on a physical server, or in virtualized and cloud environments like AWS, Azure, and GCP.

Why Data Unification is a Major Challenge for Enterprises In this SourceForge video, Carlo Alpuerto of A10 Networks identifies a significant challenge in cybersecurity: the unification of data. He explains that while the goal is for systems to feed one another, many solutions are "Frankensteined together," making it difficult to achieve this integration.

Defending Against WAF, API, and DDoS Attacks In this video from SourceForge, Carlo Alpuerto of A10 Networks explains the "outside-in" protection philosophy behind ThreatX. He uses the metaphor of a castle wall, stating that the defense focuses on who and what is attacking it, rather than what is behind it. Alpuerto details the flexibility of the A10's ThreatX solution, which can be deployed in various hybrid scenarios, including on-premise physical or virtual environments, as well as different cloud environments like AWS, Azure, and GCP.

AI in Healthcare: Navigating Data Privacy and Medical Advice In this video, A10 Networks security experts Jamison Utter, Madhav Aggarwal, and Diptanshu Purwar explore the critical security challenges of deploying AI and Large Language Models (LLMs). They focus on protecting sensitive data—especially in areas such as healthcare—and offer key insights on how organizations can effectively secure these powerful technologies.

Defending Against WAF, API, and DDoS Attacks In this SourceForge video, Carlo Alpuerto of A10 Networks shares insights on how ThreatX protects WAF, API, DDoS, and bot attacks, processing all the information within a single database. Alpuerto highlights the platform's ability to apply these protections and actionability, showcasing how users can create and manage specific rules. He also notes that the ThreatX security operations center (SOC) team curates these rules daily, utilizing threat intelligence, CVE notifications, and zero-day news to provide comprehensive, up-to-date protection.

ThreatX by A10 Networks: API Vulnerabilities and Attack Surface Management In this video, Carlo Alpuerto of A10 Networks discusses API security with Beau Hamilton of SourceForge. He explains that API security is a broad term that includes addressing vulnerabilities in the development cycle, which takes time and involves various stages like QA, staging, and UAT.

Adapting to the Changing AI Threat Landscape In this video, A10 Networks' security leaders, Jamison Utter, Madhav Aggarwal, and Diptanshu Purwar, discuss the evolving security risks associated with AI and Large Language Model (LLM) adoption, as well as what organizations must do to stay protected. Diptanshu Purwar outlines key shifts in the approach to AI security.

LLMs as Compression Systems: Security Implications In this video, A10 Networks' security leaders Jamison Utter, Madhav Aggarwal, and Diptanshu Purwar discuss the evolving security landscape in the age of AI and Large Language Models (LLMs). Madhav Aggarwal highlights a crucial aspect to understand about LLMs and their security implications.

AI and Compliance: Preventing PII Information Leakage In this video, A10 Networks' security leaders, Jamison Utter, Madhav Aggarwal, and Diptanshu Purwar, delve into the growing security risks associated with the adoption of conversational AI bots and Large Language Models (LLMs), particularly in sensitive fields such as healthcare. Diptanshu Purwar highlights several key concerns.

Why Human Oversight is Crucial for AI A10 Networks' security leaders, Jamison Utter, Madhav Aggarwal, and Diptanshu Purwar, delve into critical aspects of AI security, particularly concerning sensitive data and the role of human oversight.