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October 9, 2022

Piloting Airline Cyber Security With Artificial Intelligence (AI)

The airline industry is constantly exposed to cyber threats. Darktrace has some tips to help airline professionals bolster their cyber-security efforts.
Inside the SOC
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
Tony Jarvis
VP, Field CISO
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09
Oct 2022

A Thin Margin for Error

The airline industry has long been known for its thin profit margins, and the high costs of unexpected downtime. 2010’s Eyjafjallajökull eruption in Iceland and the resulting six-day airspace ban across Europe cost airlines $1.7 billion, just a taste of the impact that would come ten years later as a result of the pandemic. The industry collectively amassed more than $180 billion in debt in 2020, and some predictions suggest that by 2024 the industry's debt could exceed its revenue.

Given the impact that further sustained downtime could have on an already ailing industry, airlines are having to take cyber security seriously. Last year’s Colonial Pipeline ransomware attack in the US led to a six-day shutdown of pipeline operations – the same length of time that flights were grounded by the Eyjafjallajökull eruption. But while the industry hasn’t seen a volcanic eruption on that scale in over twelve years, ransomware attacks are striking airlines weekly. Just this year a ransomware attack on SpiceJet left hundreds of passengers stranded at airports across India, despite being contained relatively quickly.  

Fraud, Fines and Safety Risks

It isn’t just ransomware which is concerning many in the industry. Data breaches remain one of the biggest threats to airlines, organizations which are responsible at any one time for the personal and financial information of millions of customers. In 2019, British Airways had the data of 380,000 customers stolen, including addresses, birth dates and credit card information, and was fined £20 million (reduced from £183 million due in part to the impact of the pandemic) by the UK’s Information Commissioner’s Office (ICO), the largest issued fine in the ICO’s history. The European airline EasyJet is currently facing a class-action suit seeking £18 billion in damages after failing to properly disclose the loss of 2,208 customers’ credit-card information in 2020. 

Airlines are also losing out to card and air mile fraud, with thousands of fraudulent loyalty program accounts being sold on the dark web, as well as the usual roster of attacks including phishing and insider threats which affect businesses of every size and industry. The airlines themselves are not being complacent. In a 2021 report by SITA, 100% of airlines surveyed named cyber security as a key investment for the next three years. Making sure that those investments count will be the next challenge.

There are few industries for which safety and security measures are so important, and while no impact on flight safety as a result of a cyber-attack has yet been reported, agencies like Eurocontrol are already urging caution. Airlines and airports should look at smarter ways to proactively protect their digital environments. 

As attacks grow faster and less predictable, organizations are increasingly turning to preventative AI security measures. For airlines, which operate with broad attack surfaces and plenty of valuable data, using tools which can identify and monitor every asset and potential attack path in an organization and take the necessary steps to secure them is the best way to stay ahead of attackers.

Securing Airspace, Securing Cyberspace

As a recreational pilot myself, I understand the extent of the safety measures that go into every flight: the flight plans, pre-flight checks and all of the long-practiced, deep-embedded knowledge. It is this comprehensive and meticulous approach which ought to be reflected in organizations’ cyber security efforts – whether they be airlines, airports or any other type of business. The parallels between the processes of flying and running a digital organization safely give us a helpful way to understand what proper, AI-driven cyber security can do for any organization, airlines included.

Cleared for Takeoff 

For the pilot, safety measures start long before they’re sat in the cockpit. Flight planning, which includes planning heading and bearing, taking things like elevation, terrain, and weather conditions into consideration, must be completed in addition to plenty of pre-flight checks. The checklist the pilot works through when performing a walk around and pre-flight inspection will often be ordered so that they work in a circle around the perimeter of the whole plane. These checks prevent potential threats, covering everything from water having mixed with the fuel to birds making nests inside the engine cowling.

Darktrace PREVENT, released in July 2022, serves a similar purpose. The AI autonomously identifies and tests every single user and asset that makes up a business in order to spot potential vulnerabilities and harden defenses where necessary. Like a walk around, PREVENT/Attack Surface Management examines the full range of external assets for threats. Then, by identifying and testing potential attack pathways and mitigating against weak points and worst-case scenarios, PREVENT/End-to-End takes steps to win the fight before an attack has been launched. 

Maintaining Good Visibility

When you’re piloting a plane, first and foremost you need a way to detect key variables. Your fundamental flight instruments in the cockpit are known as the six pack:

1. Airspeed Indicator
2. Attitude Indicator or Artificial Horizon 
3. Altimeter
4. Turn Coordinator 
5. Heading Indicator
6. Vertical Speed Indicator

These six instruments provide the critical information needed by any pilot to safely fly the aircraft. While additional instruments are required to conduct flights In low-visibility or ‘Instrument Meteorological Conditions’ (IMC) conditions, these will be essential when getting out of dangerous situations such as inadvertently flying into cloud.

Understanding an environment and adapting to its changes is also fundamental to Darktrace DETECT: an AI-driven technology which focuses on building a comprehensive knowledge of an organization’s environment in order to spot threats the moment they appear. Because it understands what is ‘normal’ for the organization, Darktrace DETECT is able to correlate multiple subtle anomalies in order to expose emerging attacks – even those which have never been seen before. Like those essential flight instruments, DETECT offers visibility into otherwise obscure regions of the environment, and ensures that any potential problems are spotted as early as possible. 

Mayday, Mayday

In aviation and security, moving quickly once a threat has been detected is critical. When an engine stalls at 3,000 feet above ground level, you don’t have time to get the training books out and start figuring out what to do. Pilots are taught to “always have an out” and be ready to use it.

In aviation, an effective response relies for the most part on the knowledge and quick reactions of the pilot, but in cyber security, AI is making response faster and more effective than ever. Darktrace RESPOND uses DETECT’s contextual understanding in order to take the optimum action to mitigate a threat. Adaptability of this response is crucial: a single cyber-attack can come in any number of configurations, and Darktrace RESPOND is able to tailor its actions appropriately. Attacks today move too fast for human teams to be expected to keep up, but with AI taking actions at machine speed organizations can remain protected. 

Always Learning

One of the best pieces of advice a pilot can take is to always be learning. Every flight is an opportunity to learn something new and become a better and safer pilot.

Darktrace DETECT, RESPOND, and PREVENT are all driven by Self-Learning AI, a technology which not only builds but continuously evolves its understanding of each business. This means that as an organization grows, adding more users, assets, or applications, its Darktrace coverage grows too, using each new data point to enhance its understanding and the accuracy of its actions and detections. Darktrace’s separate technologies also learn from each other. Each of the three product families continuously feeds data into the others, helping to enhance their capabilities and improving their ability to keep organizations secured against threats. 

As cyber-attacks proliferate and increase in sophistication, they will continue to target organizations like airlines, which have large attack surfaces and copious amounts of customer data, and which cannot afford to weather sustained downtime. But with AI offering effective, proactive measures and clear-sky visibility, security teams can be confident in their ability to fight back.

Inside the SOC
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
Tony Jarvis
VP, Field CISO

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July 22, 2025

Global Telecom Provider: Powering and Protecting the World's Data Giants

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This global leader plays a critical role in keeping the world connected. The company works with some of the largest and most influential public and private organizations in the world to enable ultra-fast data transmission.

Safeguarding the systems that keep the world connected

Standing at the forefront of global connectivity, this industry leader designs and manages large-scale communications systems that power the world’s most data-intensive enterprises – including social media giants, hyperscale cloud providers, and major data center operators. Given the scale, confidentiality, and sensitivity of the systems and data it helps transport, the company faces complex cybersecurity challenges.

Protecting sensitive customer data

Most of the organization’s projects are custom-designed and highly proprietary, making data privacy and Intellectual Property (IP) protection critical to maintaining trust and confidentiality with customers. In an industry where every competitor knows the landscape intimately, any loss of data could cause significant damage.

International security implications

The company faces a broad range of advanced cyber threats – from corporate espionage and supply chain risks to cyber-physical attacks on critical infrastructure. Its international footprint adds complexity, including cross-border regulatory compliance. A successful attack could disrupt business, compromise IP, or trigger wider consequences like disruptions to international data transfers and other critical services.

The global leader works closely with communities to anticipate threats that could impact the global communications network at large.

In this environment, cybersecurity is a foundation for international trust,” said the organization’s CISO.

Building a resilient cybersecurity strategy from the ground up

The CISO had the rare opportunity to build the IT and cybersecurity infrastructure from scratch. "Initially, we bought what everyone else buys,” referencing the traditional mix of firewalls, routers, and antivirus tools. “But I knew we needed to do more.”

Self-Learning AI – “the missing piece”

With solid perimeter defenses in place, the security team sought deeper protection inside the network. Darktrace’s Self-Learning AI stood out. “Unlike other solutions, Darktrace’s AI looks beyond known threat signatures, learning what’s normal for our environment and flagging what’s not. That was the missing piece – something that could help us even when everything else failed.”

A solution and partnership that delivered

The CISO said he appreciated the ability to observe Darktrace in action before full deployment, noting that the Darktrace team was there every step of the way, providing guidance and expertise to ensure he got the most out of his investment.

Partnership was especially valuable given the company’s explosive 400% growth over the last six years. As resources were stretched and priorities shifted, “Darktrace remained patient and responsive. We’re slow and methodical, but the Darktrace support team was phenomenal, never losing momentum and earning our trust.”

A unified cybersecurity ecosystem

Today, the global leader is using the Darktrace ActiveAI Security Platform™ as a core part of its layered defense strategy, including:

The CISO appreciates how, as a unified cybersecurity platform, Darktrace has an intuitive user interface, which makes it easier for his team to investigate alerts visually, even without deep technical expertise.

Advancing defenses while impacting the bottom line

A 24/7 “safety net”

The fact that this company has never been hacked is the clearest proof it made the right decision with Darktrace, said the CISO. Initially rolled out in Human Confirmation Mode, meaning it would not take autonomous action without explicit approval from the security team, Darktrace immediately uncovered threats and anomalies that other tools had missed.

Darktrace acts as a must-have safety net—ready to step in when other tools fall short,” said the CISO.

From monitoring internal behavior and identifying unusual attack patterns, to autonomously neutralizing threats after hours, the platform provides peace of mind in a high-stakes industry. “Darktrace is my dark horse – the thing I have in my back pocket if everything else fails. It’s here to save the day, save my company, and maybe even save my career.”

Autonomous capabilities free up time for skilled analysts

Darktrace’s AI-powered detection and response capabilities are deeply embedded in the team’s day-to-day operations, autonomously investigating and responding to the majority of potential threats. Cyber AI Analyst conducted a total of 2,776 total investigations within three months, averaging just 12 minutes to autonomously investigate an incident. Of those 2,776 investigations, Darktrace resolved 2,671 (96%) autonomously and escalated only 105 (4%) to analysts. Darktrace has dramatically reduced alert fatigue and freed up analysts to focus on what really matters, saving the security team 486 analyst hours on investigations within a 20-day period.

From noise to actionable insight

Darktrace delivers meaningful data and meaningful alerts. “If Darktrace escalates an incident, we drop everything and work on that. We trust in Darktrace.” When analysts do need to investigate an incident, Darktrace’s forensic logs and guided remediation suggestions have slashed the time analysts spend on investigations by four to five times.

Stronger security. Lower cost.

The CISO says, “Darktrace is a money-saver for our organization, making continued investments an easy sell to the CEO and the board.”  When he found himself down a resource after a member of the security team left the organization, the CISO turned to Darktrace Managed Threat Detection and Response services for 24/7 expert support. “It was a no brainer. We got better coverage, higher skill levels, and around-the-clock support – all for less than what we would pay to employ a single analyst.”

Scaling securely into the future

Securing networks in motion  

The organization is preparing to scale both its operations and security posture across existing distributed, mobile and deployable communications networks that historically have been disconnected. Some of these networks are in constant motion and operating in some of the world’s most volatile regions. “Darktrace will act as an autonomous defender, monitoring for anomalous behavior and intervening, when necessary, especially during those dangerous times when an asset ‘goes dark’ and becomes disconnected from the broader network,” said the CISO.

Applying AI strategically

As the organization continues to evaluate where and how to apply AI, its emphasis will be on technologies that can act independently to contain threats – especially in environments where human response may be delayed. “It’s about using the right kind of AI for the right challenge. That’s why we’re investing in Darktrace, with tools that can adapt and learn even in isolation and provide real-time protection wherever we operate.”

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July 17, 2025

Introducing the AI Maturity Model for Cybersecurity

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AI adoption in cybersecurity: Beyond the hype

Security operations today face a paradox. On one hand, artificial intelligence (AI) promises sweeping transformation from automating routine tasks to augmenting threat detection and response. On the other hand, security leaders are under immense pressure to separate meaningful innovation from vendor hype.

To help CISOs and security teams navigate this landscape, we’ve developed the most in-depth and actionable AI Maturity Model in the industry. Built in collaboration with AI and cybersecurity experts, this framework provides a structured path to understanding, measuring, and advancing AI adoption across the security lifecycle.

Overview of AI maturity levels in cybersecurity

Why a maturity model? And why now?

In our conversations and research with security leaders, a recurring theme has emerged:

There’s no shortage of AI solutions, but there is a shortage of clarity and understanding of AI uses cases.

In fact, Gartner estimates that “by 2027, over 40% of Agentic AI projects will be canceled due to escalating costs, unclear business value, or inadequate risk controls. Teams are experimenting, but many aren’t seeing meaningful outcomes. The need for a standardized way to evaluate progress and make informed investments has never been greater.

That’s why we created the AI Security Maturity Model, a strategic framework that:

  • Defines five clear levels of AI maturity, from manual processes (L0) to full AI Delegation (L4)
  • Delineating the outcomes derived between Agentic GenAI and Specialized AI Agent Systems
  • Applies across core functions such as risk management, threat detection, alert triage, and incident response
  • Links AI maturity to real-world outcomes like reduced risk, improved efficiency, and scalable operations

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How is maturity assessed in this model?

The AI Maturity Model for Cybersecurity is grounded in operational insights from nearly 10,000 global deployments of Darktrace's Self-Learning AI and Cyber AI Analyst. Rather than relying on abstract theory or vendor benchmarks, the model reflects what security teams are actually doing, where AI is being adopted, how it's being used, and what outcomes it’s delivering.

This real-world foundation allows the model to offer a practical, experience-based view of AI maturity. It helps teams assess their current state and identify realistic next steps based on how organizations like theirs are evolving.

Why Darktrace?

AI has been central to Darktrace’s mission since its inception in 2013, not just as a feature, but the foundation. With over a decade of experience building and deploying AI in real-world security environments, we’ve learned where it works, where it doesn’t, and how to get the most value from it. This model reflects that insight, helping security leaders find the right path forward for their people, processes, and tools

Security teams today are asking big, important questions:

  • What should we actually use AI for?
  • How are other teams using it — and what’s working?
  • What are vendors offering, and what’s just hype?
  • Will AI ever replace people in the SOC?

These questions are valid, and they’re not always easy to answer. That’s why we created this model: to help security leaders move past buzzwords and build a clear, realistic plan for applying AI across the SOC.

The structure: From experimentation to autonomy

The model outlines five levels of maturity :

L0 – Manual Operations: Processes are mostly manual with limited automation of some tasks.

L1 – Automation Rules: Manually maintained or externally-sourced automation rules and logic are used wherever possible.

L2 – AI Assistance: AI assists research but is not trusted to make good decisions. This includes GenAI agents requiring manual oversight for errors.

L3 – AI Collaboration: Specialized cybersecurity AI agent systems  with business technology context are trusted with specific tasks and decisions. GenAI has limited uses where errors are acceptable.

L4 – AI Delegation: Specialized AI agent systems with far wider business operations and impact context perform most cybersecurity tasks and decisions independently, with only high-level oversight needed.

Each level reflects a shift, not only in technology, but in people and processes. As AI matures, analysts evolve from executors to strategic overseers.

Strategic benefits for security leaders

The maturity model isn’t just about technology adoption it’s about aligning AI investments with measurable operational outcomes. Here’s what it enables:

SOC fatigue is real, and AI can help

Most teams still struggle with alert volume, investigation delays, and reactive processes. AI adoption is inconsistent and often siloed. When integrated well, AI can make a meaningful difference in making security teams more effective

GenAI is error prone, requiring strong human oversight

While there is a lot of hype around GenAI agentic systems, teams will need to account for inaccuracy and hallucination in Agentic GenAI systems.

AI’s real value lies in progression

The biggest gains don’t come from isolated use cases, but from integrating AI across the lifecycle, from preparation through detection to containment and recovery.

Trust and oversight are key initially but evolves in later levels

Early-stage adoption keeps humans fully in control. By L3 and L4, AI systems act independently within defined bounds, freeing humans for strategic oversight.

People’s roles shift meaningfully

As AI matures, analyst roles consolidate and elevate from labor intensive task execution to high-value decision-making, focusing on critical, high business impact activities, improving processes and AI governance.

Outcome, not hype, defines maturity

AI maturity isn’t about tech presence, it’s about measurable impact on risk reduction, response time, and operational resilience.

[related-resource]

Outcomes across the AI Security Maturity Model

The Security Organization experiences an evolution of cybersecurity outcomes as teams progress from manual operations to AI delegation. Each level represents a step-change in efficiency, accuracy, and strategic value.

L0 – Manual Operations

At this stage, analysts manually handle triage, investigation, patching, and reporting manually using basic, non-automated tools. The result is reactive, labor-intensive operations where most alerts go uninvestigated and risk management remains inconsistent.

L1 – Automation Rules

At this stage, analysts manage rule-based automation tools like SOAR and XDR, which offer some efficiency gains but still require constant tuning. Operations remain constrained by human bandwidth and predefined workflows.

L2 – AI Assistance

At this stage, AI assists with research, summarization, and triage, reducing analyst workload but requiring close oversight due to potential errors. Detection improves, but trust in autonomous decision-making remains limited.

L3 – AI Collaboration

At this stage, AI performs full investigations and recommends actions, while analysts focus on high-risk decisions and refining detection strategies. Purpose-built agentic AI systems with business context are trusted with specific tasks, improving precision and prioritization.

L4 – AI Delegation

At this stage, Specialized AI Agent Systems performs most security tasks independently at machine speed, while human teams provide high-level strategic oversight. This means the highest time and effort commitment activities by the human security team is focused on proactive activities while AI handles routine cybersecurity tasks

Specialized AI Agent Systems operate with deep business context including impact context to drive fast, effective decisions.

Join the webinar

Get a look at the minds shaping this model by joining our upcoming webinar using this link. We’ll walk through real use cases, share lessons learned from the field, and show how security teams are navigating the path to operational AI safely, strategically, and successfully.

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