Inside Google’s AI Red Teaming Strategy for Cybersecurity

As artificial intelligence becomes deeply embedded in enterprise systems, securing it requires more than extending traditional cybersecurity practices.

The urgency is already clear. According to the Global Cybersecurity Outlook 2026 survey, 87 percent of respondents identified AI-related vulnerabilities as the fastest-growing cyber risk in 2025. This signals a turning point – it demands a fundamental rethink of how threats are anticipated, simulated, and mitigated.

Within Google, this shift has taken shape through the evolution of its red teaming philosophy. Under the leadership of Daniel Fabian, this task is to uncover vulnerabilities in AI systems before adversaries can exploit them.

Here’s an inside look at Google’s AI red team and its approach to building safer, more secure AI systems.

Emergence of Google’s AI Red Team

Reaching this point is the result of significant organic growth. The Red Team was founded in 2016 as a “20% project” – an internal initiative that allows Googlers to pursue interesting work outside their day-to-day responsibilities. However, the insights generated proved so strong that the team quickly recognized the value of applying a hacker mindset to security challenges.

Since then, the red team has become an integral part of Google’s security approach, providing insights and context about vulnerabilities that significantly strengthen its ability to keep people and systems safe.

Google’s AI Red team at scale: How it works?

Here’s how the team hacks their way to better security.

Break things to understand them

The Red Team is guided by the simple principle: ‘break things to understand them.’ They treat disruption as a deliberate method of learning – an intentional pathway to deeper understanding.

By safely probing systems and intentionally pushing them beyond normal operating conditions, the team gains a deeper clarity of how defenses hold up under real-world attack scenarios.

Google’s Red Team has a strong track record for operating safely and responsibly. As a result, they explore security boundaries with relatively few constraints. This flexibility allows them to shine light into areas that are often difficult to observe through conventional testing methods. In fact, this approach enables more direct discovery of weaknesses that might otherwise remain hidden.

And because multiple exercises run in parallel, the team carefully logs every action and shares it with defense teams. This ensures transparency. It provides defenders with a reliable audit trail and helps them quickly distinguish between internal testing activity and genuine malicious behavior.

Most of the issues identified through this ‘break to understand’ approach are resolved quickly once shared. And the specific conditions that enabled them are rarely repeatable in the same way again.

The intent is not only to find vulnerabilities. But to understand why they exist, how they can be triggered, and what system properties allow them to persist.

Ultimately, by breaking systems in controlled environments, the Red Team can study the mechanics of failure, isolate the technical pathways exploited by real attackers, and translate those insights into stronger, more resilient defenses.

Practices open communication

The Red Team actively follows a philosophy of open communication, grounded in the belief that teams should share security knowledge openly. It collaborates closely with defensive teams across Google, including the Google Threat Intelligence Group (GTIG) and internal threat detection and response teams, fostering strong trust and coordination.

Likewise, strong stakeholder management practices are in place, with key stakeholders engaged early in the planning stages of each exercise. They are kept informed at a high level about the scope, targets, and overall intent of the activity

Most importantly, the individuals conducting offensive exercises are not the same as those responsible for post-exercise remediation tracking. This separation ensures objectivity and focus during follow-up.

Once an exercise concludes, communication channels remain open to support remediation efforts and ensure that identified issues are fully addressed.

Using adversarial research

As part of testing, the team pays close attention to what’s happening in the world.

It actively tracks advancements in threat intelligence and consistently investigates emerging attack vectors as they surface in real-world environments.

Rather than treating testing as a static exercise, the team integrates ongoing research into its workflow, ensuring that its understanding of adversarial techniques evolves alongside the threats themselves. This constant attention to external signals helps ensure that testing remains relevant, forward-looking, and aligned with the latest methods being used by real attackers.

For example, you might be worried that a nation-state actor like the Russian hacking group APT29 might use a zero-day attack to target your CEO’s devices. But GTIG research shows that these types of groups are more likely to launch supply chain attacks targeting third-party vendors to gain access to organizations. Therefore, we (and you) should focus on scenarios as realistic as possible.

 Combine traditional security and AI expertise

The Red Team combines traditional security expertise with specialized AI knowledge to create realistic adversarial simulations. They understand that accurately modeling modern threats requires integrating both established cybersecurity skills and a deep understanding of AI systems wherever possible.

To support this approach, the team regularly collaborates with traditional security teams to exchange ideas, techniques, and skill sets. It strengthens their ability to execute end-to-end adversarial scenarios that closely resemble real-world attacks.

This blended model has proven highly effective for the team. It helps uncover potential weaknesses more realistically and equips defensive teams to better anticipate and prepare for future threats.

Having a strong attacker mindset

The team at Google understands that it is important to have a strong attacker mindset. Being able to think like a threat actor, imagining the most likely attack paths, strategies, tools, and approaches, is what leads to the most realistic exercises and the best lessons on how to stop them. Creativity, curiosity, and strategic thinking often prove more valuable than deep theoretical knowledge.

A continuous cycle of learning

Google’s AI red teaming strategy reflects a broader philosophy: security is not a static goal but an ongoing process of learning and adaptation. By proactively simulating attacks, refining methodologies, and integrating insights across teams, the organization builds resilience against both current and future threats.

Moreover, it adopts the practice of ‘learning from failure’. It treats every outcome as an opportunity to improve systems – an approach that is deeply embedded in engineering culture at Google.

Likewise, it doesn’t use the ‘blame game’. The team believes that security responsibility should not rest on end users. Instead, it focuses on identifying and addressing the underlying factors that enable successful system compromise.

In an environment where the rules are still being written, this approach helps foster trust, strengthens relationships with other teams, and ensures the shared goal remains focused on improving security for Google and its users rather than assigning blame when issues are discovered.

Key takeaways for CTOs and security leaders:

The lesson for CTOs is straightforward: if you’re not actively trying to break your own systems, someone else will. Structured adversarial testing needs to be part of how AI is built and deployed.

Security is a system problem, not just a model problem

Vulnerabilities rarely exist in isolation. They emerge from interactions between infrastructure, pipelines, integrations, and human processes.

Red teaming must evolve from periodic testing to continuous simulation

Effective security is no longer about occasional audits; it requires ongoing, large-scale adversarial simulation that mirrors real attacker behavior in real time.

Blending AI expertise with traditional cybersecurity is essential

Modern attack surfaces require joint thinking across AI researchers, security engineers, and traditional red teamers.

Open communication and early stakeholder alignment are critical at scale

Transparency before, during, and after exercises ensures faster remedy and reduces operational friction across teams.

Security is a continuous lifecycle, not a one-time milestone

Defenses must evolve in lockstep with adversaries, requiring constant iteration, feedback loops, and adaptation.

Core message

Google’s approach highlights a fundamental shift:

Securing AI is not about preventing isolated failures, but about building resilient systems that can anticipate, absorb, and adapt to evolving adversarial behavior.

For CTOs and other business leaders, this means rethinking security from the ground up, focusing on behavior, integration, and continuous adversarial testing rather than static defenses.

In brief

Google’s AI Red Team is at the forefront of enhancing the security and reliability of AI systems through the practice of red teaming. By simulating real-world adversarial scenarios, the Red Team identifies potential vulnerabilities and weaknesses in AI technology, enabling organizations to strengthen their defenses against emerging threats.