Welcoming Jim Nightingale to Mindgard | Advancing AI Security Research

Updated on

February 23, 2026

Welcoming Jim Nightingale to Mindgard

Welcoming Jim Nightingale to Mindgard as he expands our adversarial AI research, uncovering real-world vulnerabilities in modern AI systems and safety controls.

Fergal Glynn

TABLE OF CONTENTS

Key Takeaways

I’m incredibly excited to announce that Jim Nightingale has joined the Mindgard team, working on Red Teaming and Adversarial Testing.

Jim brings a unique blend of academic experience, deep curiosity, and a passion for understanding how advanced AI systems can be tested, poked, and prodded to uncover the weaknesses that matter most.

Some of you will already be familiar with Jim’s work from his recent research posts:

In Bypassing Image Safeguards in ChatGPT, Jim explored how memory manipulation techniques can circumvent image filtering constructs and revealed where current protective layers fall short.
In Feeling Lucky, or Liable? Bypassing Safety Content Restrictions in Google Search AI, he demonstrated how extracting system instructions from a major AI interface can materially weaken safety constraints, and why defenders need to treat system prompts as sensitive assets.

These pieces are great illustrations of Jim’s mindset: deeply analytical investigations, relentless about uncovering real security risk, and always laser-focused on practical impact. Jim doesn’t just ask “can we do this?” he focuses on “what does this mean for the safety, reliability, and real-world deployment of AI?” That perspective is exactly what we need as we push the frontier of AI risk discovery and security testing.

Jim isn’t only active here at Mindgard, you can follow more of his insights and research explorations at Jim the AI Whisperer on Medium, where he regularly writes about AI behavior, prompt engineering, attack vectors, and the evolving landscape of model security.

Please join me in welcoming Jim.

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Mindgard, the leading provider of Artificial Intelligence security solutions, helps enterprises secure their AI models, agents, and systems across the entire lifecycle. Mindgard’s solution uncovers shadow AI, conducts automated AI red teaming by emulating adversaries, and delivers runtime protection against attacks like prompt injection and agentic manipulation. Trusted by leading organizations in finance, healthcare, and technology, Mindgard is backed by investors including .406 Ventures, IQ Capital, Atlantic Bridge, and Lakestar.