Discover how the MIT AI Risk Repository is helping AI red teamers and pen testers tackle complex security challenges with actionable insights.

Red teaming is a proactive cybersecurity strategy where ethical hackers simulate real-world attacks—spanning technical, human, and physical vulnerabilities—to identify and address security weaknesses before malicious actors exploit them.

Red teaming LLMs involves simulating adversarial attacks to uncover vulnerabilities such as bias, security risks, and information leakage, ensuring models are secure, ethical, and robust before deployment. Techniques like automated testing, prompt injection, bias testing, and data poisoning simulations help organizations proactively address threats and improve AI safety at scale.

Unlike traditional red teaming, which occurs periodically, CART operates 24/7, reducing human error, enabling scalability, and allowing immediate threat mitigation, making it a critical tool for securing modern digital and AI-driven environments.

Red team operations follow a structured five-phase approach—planning, reconnaissance, attack simulation, reporting, and remediation—ensuring organizations stay resilient against evolving threats.

This post compares and contrasts the recent UK and US governments' ambitious AI development plans.

The UK’s longest running index of disruptive new startups, the Startups 100, has named Mindgard among the most ground-breaking new businesses in its 2025 edition.

This blog highlights concerns about AI safety benchmarks, which often reflect general capability improvements rather than true safety advancements, a practice termed "safetywashing."

Mindgard is proud to be recognized in OWASP’s Q1 2025 LLM and GenAI Security Solutions Landscape, highlighting our dedication to enhancing security and safety for AI systems.

Red teams simulate offensive attacks to identify vulnerabilities, while blue teams focus on defense by detecting and mitigating threats in real time. Together, they help organizations improve their security posture through proactive testing and continuous improvement, with both teams working in tandem to uncover weaknesses and strengthen defenses.

Red teaming involves ethical hackers simulating real-world cyberattacks to test an organization’s ability to detect, respond to, and recover from advanced threats. Unlike traditional penetration testing, red team exercises go beyond set parameters to mimic malicious tactics, offering a comprehensive view of an organization’s security weaknesses.

In a significant milestone for AI security innovation, Mindgard is proud to announce its $8 million funding round led by .406 Ventures, alongside key strategic appointments of two industry leaders, Dave Ganly and Fergal Glynn. With this funding and expanded leadership, Mindgard is poised to transform the AI security landscape, addressing the critical risks associated with AI adoption.

When it comes to assessing the security and resilience of systems, "Red Teaming" and "Penetration Testing" are two methodologies that are often compared. While they share similarities in their objectives, these approaches are distinct in their execution, scope, and purpose.

Red teaming, a concept originally rooted in military strategy, involves deploying a dedicated team to challenge an organization’s defenses. When applied to AI, this approach goes beyond traditional testing methodologies by simulating real-world adversarial scenarios to evaluate how AI systems perform under pressure.

Mindgard is proud to announce its recognition as a winner of the Enterprise Security Tech 2024 Cybersecurity Top Innovations Award.

We've been busy developing new features to add even more value to your Mindgard experience, and we're excited for you to try them out. Here's what's new: Improved Attack Page plus OWASP Top 10 and MITRE Atlas Techniques Mapping, Test your own Custom Datasets & Prompts, New Attacks Released, Introducing Mindgard Academy