Learn from two leaders in their fields about cyber risks in Formula 1 and McLaren's unique approach. Explore cyber risks and strategies that set McLaren apart.
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Written by
Nicole Eagan
Co-founder and Strategic Advisor
Written by
Zak Brown
CEO, McLaren Racing
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03
May 2022
Nicole Eagan, Darktrace’s Chief Strategy Officer and AI Officer, catches up with Zak Brown, CEO at McLaren Racing, on innovation, cyber-attacks, and what sets McLaren apart.
Nicole: Thanks for joining us, Zak. I’d like to start this off by speaking about innovation. As you know, the pace of change is very rapid in both cyber security and Formula 1. At Darktrace, our aim is to outpace the attackers, which we do by heavily investing in our R&D and our AI specifically. As the CEO of McLaren Racing, how important is innovation?
Zak: Innovation is our life blood. To give you an idea: if you took the car that qualified first in the first race of the season, and you didn’t touch it throughout the year, it would come last in the final race of the season. We’re developing a new part for our race car about every 15 minutes, 365 days a year. These facts illustrate the pace of development here at McLaren. As we say in motor racing – if you’re sitting still, you’re actually going backwards.
Nicole: Talk about pace of innovation! We’ve observed at Darktrace that in any industry, no two organizations operate the same way. In fact, the closer you get, the more you realize how different they are. This is one of the reasons we think taking a self-learning approach to security is so important. In your view, what sets McLaren apart from other teams?
Zak: Whilst all teams are pushing for a similar outcome – to be the fastest racing team in the world –we go about it in different ways. At McLaren, it’s all about the people, as well as understanding and leaning into our technology and technology partners.
Nicole: As you know, cyber-attacks can trickle over into business disruption – and sometimes even effect physical operations. What impact can a cyber-attack have for McLaren Racing?
Zak: There are so many ways a cyber-attack could disrupt our racing and our business. Wherever we’re racing around the world, it all starts back at our factory in the UK. Everything is real time, and if a cyber-attack were to shut down our technology, we wouldn’t be able to go onto the track. We also need to protect our Intellectual Property and our supply chain, as a lot of critical information is being passed back and forth between us and our suppliers.
A real-life incident I can recall happened in 1998, well before we became partners with Darktrace. Someone tapped into our radio communications as our driver at the time, Mika Häkkinen, was leading the Australian Grand Prix. The attacker told Mika to pit, and he did! It almost cost him the race. These actions have consequences that can cost us on track performance which in turn, can lead to much bigger business implications.
Nicole: That’s an amazing story, and really shows how extreme the disruption can be. As a high-profile target, I’m aware that you also received a personal attack at the Italian Grand Prix last season. Can you share the story of this attack with us?
Zak: I get about 300 emails a day, and I’m constantly on the run. Fortunately, Darktrace stopped the attack before it even hit my desk. When I’m going at 100 miles an hour and receive such a large volume of emails daily, these attacks are extremely well disguised. You have to rely on technology to catch the bad guys.
Nicole: I absolutely agree. And that’s exactly where our Autonomous Response technology comes in. It’s constantly working in the background, not needing human action, and stopping attackers from even hitting your desktop. Which leads us on to my next question: what are some of the cyber security tips you would share with other high-level executives?
Zak: I take security very seriously – I’ve seen it and experienced it. During the course of the pandemic, the digital landscape has expanded and opened up more opportunities for the bad guys to try and get in. In my opinion, it’s only going to get worse, and so I’d say that a priority for me is to make sure other high-level executives are fully aware that we’re staying cutting edge with Darktrace.
Nicole: Well, with the pace of innovation at McLaren, the level of IP you have and the risk of physical disruption a cyber-attack could cause, it’s great to hear how seriously you take cyber security.
So in wrapping up, I know there’s huge excitement building for the race in Miami this weekend. How important will this new race be in garnering excitement about Formula 1 across the US?
Zak: Formula 1 has really taken off now across North America and this weekend is going to be huge: tickets have sold out, the track looks amazing… it’s the hottest ticket in Formula 1 right now. Netflix has worked wonders for Formula 1 around the world, especially in the US, and broadcast numbers are growing rapidly. With all these factors working together, I think Formula 1 has successfully penetrated North America and is going to go from strength to strength.
Nicole: Well, thank you for your time today Zak and best of luck to you and the whole McLaren team this weekend…
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Security After Signatures: Operating in a World of Pre‑CVE Disclosure Exploitation, Collapsed Trust Boundaries, and Autonomous Systems
Three shifts have reshaped what it means to defend an enterprise securely.
First, exploitation often begins before defenders have a Common Vulnerabilities and Exposures (CVE) identifier, a security advisory, or an entry in the Cybersecurity and Infrastructure Security Agency's (CISA) Known Exploited Vulnerabilities (KEV) catalog.
Secondly, the trust boundary has moved beyond the network edge into identities, tokens, APIs, and Software-as-a-Service (SaaS) workflows.
Third, an increasing share of business activity is executed through automation, integrations, and AI agent-like systems that can act faster than teams can verify intent.
If your security model still relies on detecting known bad artefacts, triaging isolated alerts, and waiting for confirmation before acting, you are already behind the threat.
This is not a failure of security teams; it’s a failure of the operating model to keep pace with how the environment has changed.
A SOC built around alerts and signatures assumes that malicious activity will eventually surface as an event. In real incidents, however, the decisive evidence is rarely a single event. Instead, it is a chain of individually explainable actions that only appears malicious once you connect the dots across identity, non-human identity, cloud, email, SaaS, operational technology (OT), and network telemetry.
The defenders succeeding today observe behaviors, link them into sequences, understand what those sequences mean, and contain impact before the full story unfolds. That is the operating model the current threat environment demands.
In one example, Darktrace observed a sequence of subtle but strategically significant anomalies within a customer environment that later aligned with exploitation of CVE‑2025‑0994 in Trimble Cityworks by likely Chinese-nexus threat actors. Behavioral indicators were visible at least 18 days before public disclosure, with related anomalies emerging 40 to 50 days earlier during the intrusion window.
This case illustrates a familiar pattern: clusters of weak‑signal anomalies combing to form an actionable picture of intrusion long before a CVE is published. Such activity reflects long‑horizon, option‑preserving operator models often associated with mature state‑linked activity.
Figure 1: Darktrace’s detection of malicious exploitation of CVE 2025-0994, later tied to Chinese-nexus threat actors targeting critical national infrastructure (CNI) in the US, weeks before public disclosure.
Throughout 2025 and 2026, Darktrace has continued to observe the value of anomaly-based detections across a range of incidents.
CVE
CVE Public Disclosure Date
Darktrace Detection Date
Days Between Detection of Exploitation and CVE Public Disclosure
CVE 2025 0994 (Trimble City Works)
2025-02-06
2025-01-19
18 Days
CVE 2025-24183 (Apache)
2025-03-10
2025-02-18
20 days
CVE 2025-10035 (Fortra GoAnywhere)
2025-09-18
2025-09-11
7 days
Identity is the real control plane
The second shift is that identity has replaced perimeter as the primary control plane. As Darktrace’s Annual Threat Report 2026 illustrated, identity remains the main challenge in defending against modern intrusions. A clear example is the Adversary-in-the-Middle (AiTM) case published by Darktrace in December 2025. A phishing email led to the compromise of an Office 365 account. Session hijacking bypassed multi-factor authentication (MFA), and the compromised account was used for follow-on phishing and persistence activities including the creation of malicious email rules.
Every step in that sequence mattered. A successful login alone does not prove legitimacy. An inbox rule, on its own, may not appear catastrophic. Mail activity, viewed in isolation, may seem operationally normal. But the behavioral chain tells a different story: credential theft, token abuse, persistence, and onward compromise through a trusted identity.
This is why the question is no longer “Did the user authenticate successfully”. The more important question is, “Does this identity action make sense right now, in this context, given what came before it?” The AiTM case shows how identity can be compromised. In practice, however, attacks rarely remained confined to identity alone.
In another Darktrace case, a compromised SaaS account triggered activity across the email, SaaS, and network layers, including inbox rule changes, phishing propagation, and connections to suspicious infrastructure. Viewed in isolation, none of these events were decisive. Together, however, they formed a behavioral sequence that revealed the intrusion, with the full attack story automatically correlated and surfaced to defenders by Darktrace’s Cyber AI Analyst.
Figure 2: Cyber AI Analyst correlated and appended additional events to the incident, including other users who connected to the suspicious redirect link after outbound phishing emails were sent.
AI accelerates the threat
The third shift is the one many teams still underestimate: trusted tooling, integrations, and AI agent-like systems can create actions that appear legitimate but are strategically dangerous.
The shift becomes clearer when examining how governments are now framing AI risk. In 2026, guidance published by CISA, UK’s National Cyber Security Centre (NCSC) and Five Eyes partners warned that agentic systems expand attack surfaces, accumulate privilege, and can behave in ways that are difficult to predict or explain [1]. The advice is simple: assume unexpected behavior and design controls around it.
The real risk is not AI usage. It is unknown autonomy: systems with credentials, data access, and action paths that can execute workflow steps without sufficient behavioral validation, traceability, or human oversight. Darktrace’s Model Context Protocol (MCP) risk analysis provides a useful framework for understanding this challenge. Over-privileged agents, content injection, and tool abuse become high-consequence risks when connected systems can dynamically retrieve data, execute actions, and communicate externally.
Whether security teams like it or not, AI is already in the enterprise. It will help drive innovation, but it will also be abused, whether accidentally or maliciously. In each of the cases below, AI either scaled the attacker, built the tooling, or existed within the environment as something to exploit or misuse.
1. AI as an Attack Multiplier
In one campaign targeting Mexican government entities, a single operator used commercial AI platforms to generate exploits, automate reconnaissance, and process large volumes of data, compressing work that would traditionally have required an entire team into a single workflow [2].
Attempted AI exploitation is now appearing within customer environments. In one case involving an automation technology manufacturer, a compromised LLM proxy was seemingly used as a stepping stone to access additional AI services. When that attempt failed, the attacker pivoted to cryptomining.
What is clear is that the AI layer has already become an asset worth probing, exploiting, and pivoting through. It is also clear that defenders benefit from rapidly understanding how these activities connect. In this case, Cyber AI Analyst automatically pieced together the intrusion, while Darktrace’s Managed Threat Detection service alerted to the customer, enabling the activity to be contained before it could progress further.
Figure 3: Cyber AI Analyst's investigation into a compromised LLM proxy that was abused for cryptomining activity.
AI as a trusted but dangerous actor
This does not require a cinematic vision of “rogue AI.” The Salesloft incident provides a more grounded example, where AI and automation operate with legitimate access but served malicious intent. In that case, attackers abused compromised OAuth tokens associated with the Drift AI chat agent to export significant volumes of data from Salesforce environments.
The activity resembled legitimate API usage and relied on trusted SaaS integrations rather than malware or other obvious signs of intrusion. That is precisely the challenge. Traditional security controls are good at detecting forced entry, but far less effective when a trusted application integration behaves in a way that is technically permitted yet operationally harmful.
In these scenarios, the security challenge shifts from validating access to validating behavior.
This is what that looks like in practice: AI-linked identities executing legitimate actions that require behavioral validation rather than access validation.
Figure 4: Darktrace / SECURE AI highlights anomalous activity across AI identities, surfacing critical behavior that requires validation and containment.
Early observations from Darktrace / SECURE AI deployments reinforce this reality. Across Darktrace's observed fleet, AI service connections per deployment increased 13% during the first half of 2026, reaching over 16 million connections overall. The typical organisation now interacts with seven different AI providers, evidence that AI is no longer operating at the edges of the enterprise. It is increasingly woven into day-to-day business activity.
The most common risks are not compromised models or advanced AI attacks. Instead, they stem from employees and business functions exposing sensitive information through entirely legitimate-looking interactions. Darktrace has observed repeated submission of personally identifiable information (PII), tax information, identification documents, and medical data into LLM prompts, alongside widespread use of unsanctioned (shadow) AI services and growing AI activity from mobile devices.
For defenders, the challenge is increasingly one of context: understanding when legitimate business use crosses into material risk, while preserving privacy and user trust.
Conclusion
Across all three shifts, the pattern is the same: behavior precedes understanding. Security teams are not losing because adversaries have become invisible. An increasingly outdated security model assumes that malicious activity will reveal itself cleanly and early. It no longer does.
In 2026 and beyond, defenders win by understanding behavioral sequences, continuously validating trust, and acting before certainty becomes hindsight. That is security after signatures. That is security in the AI era.
Credit to: Daniel Levy, Threat Hunting Data Scientist
