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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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March 5, 2026

Inside Cloud Compromise: Investigating Attacker Activity with Darktrace / Forensic Acquisition & Investigation

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Investigating cloud attacks with Darktrace/ Forensic Acquisition & Investigation

Darktrace / Forensic Acquisition & Investigation™ is the industry’s first truly automated forensic solution purpose-built for the cloud. This blog will demonstrate how an investigation can be carried out against a compromised cloud server in minutes, rather than hours or days.

The compromised server investigated in this case originates from Darktrace’s Cloudypots system, a global honeypot network designed to observe adversary activity in real time across a wide range of cloud services. Whenever an attacker successfully compromises one of these honeypots, a forensic copy of the virtual server's disk is preserved for later analysis. Using Forensic Acquisition & Investigation, analysts can then investigate further and obtain detailed insights into the compromise including complete attacker timelines and root cause analysis.

Forensic Acquisition & Investigation supports importing artifacts from a variety of sources, including EC2 instances, ECS, S3 buckets, and more. The Cloudypots system produces a raw disk image whenever an attack is detected and stores it in an S3 bucket. This allows the image to be directly imported into Forensic Acquisition & Investigation using the S3 bucket import option.

As Forensic Acquisition & Investigation runs cloud-natively, no additional configuration is required to add a specific S3 bucket. Analysts can browse and acquire forensic assets from any bucket that the configured IAM role is permitted to access. Operators can also add additional IAM credentials, including those from other cloud providers, to extend access across multiple cloud accounts and environments.

Figure 1: Forensic Acquisition & Investigation import screen.

Forensic Acquisition & Investigation then retrieves a copy of the file and automatically begins running the analysis pipeline on the artifact. This pipeline performs a full forensic analysis of the disk and builds a timeline of the activity that took place on the compromised asset. By leveraging Forensic Acquisition & Investigation’s cloud-native analysis system, this process condenses hour of manual work into just minutes.

Successful import of a forensic artifact and initiation of the analysis pipeline.
Figure 2: Successful import of a forensic artifact and initiation of the analysis pipeline.

Once processing is complete, the preserved artifact is visible in the Evidence tab, along with a summary of key information obtained during analysis, such as the compromised asset’s hostname, operating system, cloud provider, and key event count.

The Evidence overview showing the acquired disk image.
Figure 3: The Evidence overview showing the acquired disk image.

Clicking on the “Key events” field in the listing opens the timeline view, automatically filtered to show system- generated alarms.

The timeline provides a chronological record of every event that occurred on the system, derived from multiple sources, including:

  • Parsed log files such as the systemd journal, audit logs, application specific logs, and others.
  • Parsed history files such as .bash_history, allowing executed commands to be shown on the timeline.
  • File-specific events, such as files being created, accessed, modified, or executables being run, etc.

This approach allows timestamped information and events from multiple sources to be aggregated and parsed into a single, concise view, greatly simplifying the data review process.

Alarms are created for specific timeline events that match either a built-in system rule, curated by Darktrace’s Threat Research team or an operator-defined created at the project level. These alarms help quickly filter out noise and highlight on events of interest, such as the creation of a file containing known malware, access to sensitive files like Amazon Web Service (AWS) credentials, suspicious arguments or commands, and more.

 The timeline view filtered to alarm_severity: “1” OR alarm_severity: “3”, showing only events that matched an alarm rule.
Figure 4: The timeline view filtered to alarm_severity: “1” OR alarm_severity: “3”, showing only events that matched an alarm rule.

In this case, several alarms were generated for suspicious Base64 arguments being passed to Selenium. Examining the event data, it appears the attacker spawned a Selenium Grid session with the following payload:

"request.payload": "[Capabilities {browserName: chrome, goog:chromeOptions: {args: [-cimport base64;exec(base64...], binary: /usr/bin/python3, extensions: []}, pageLoadStrategy: normal}]"

This is a common attack vector for Selenium Grid. The chromeOptions object is intended to specify arguments for how Google Chrome should be launched; however, in this case the attacker has abused the binary field to execute the Python3 binary instead of Chrome. Combined with the option to specify command-line arguments, the attacker can use Python3’s -c option to execute arbitrary Python code, in this instance, decoding and executing a Base64 payload.

Selenium’s logs truncate the Arguments field automatically, so an alternate method is required to retrieve the full payload. To do this, the search bar can be used to find all events that occurred around the same time as this flagged event.

Pivoting off the previous event by filtering the timeline to events within the same window using timestamp: [“2026-02-18T09:09:00Z” TO “2026-02-18T09:12:00Z”].
Figure 5: Pivoting off the previous event by filtering the timeline to events within the same window using timestamp: [“2026-02-18T09:09:00Z” TO “2026-02-18T09:12:00Z”].

Scrolling through the search results, an entry from Java’s systemd journal can be identified. This log contains the full, unaltered payload. GCHQ’s CyberChef can then be used to decode the Base64 data into the attacker’s script, which will ultimately be executed.[NJ9]

Decoding the attacker’s payload in CyberChef.
Figure 6: Decoding the attacker’s payload in CyberChef.

In this instance, the malware was identified as a variant of a campaign that has been previously documented in depth by Darktrace.

Investigating Perfectl Malware

This campaign deploys a malware sample known as ‘perfctl to the compromised host. The script executed by the attacker downloads a Go binary named “promocioni.php” from 200[.]4.115.1. Its functionality is consistent with previously documented perfctl samples, with only minor changes such as updated filenames and a new command-and-control (C2) domain.

Perctl is a stealthy malware that has several systems designed  to evade detection. The main binary is packed with UPX, with the header intentionally tampered with to prevent unpacking using regular tools. The binary also avoids executing any malicious code if it detects debugging or tracing activity, or if artifacts left by earlier stages are missing.

To further aid its evasive capabilities, perfctl features a usermode rootkit using an LD preload. This causes dynamically linked executables to load perfctl’s rootkit payload before other system modules, allowing it to override functions, such as intercepting calls to list files and hiding output from the returned list. Perctl uses this to hide its own files, as well as other files like the ld.so.preload file, preventing users from identifying that a rootkit is present in the first place.

This also makes it difficult to dynamically analyze, as even analysts aware of the rootkit will struggle to get around it due to its aggressiveness in hiding its components. A useful trick is to use the busybox-static utilities, which are statically linked and therefore immune to LD preloading.

Perctl will attempt to use sudo to escalate its permissions to root if the user it was executed as has the required privileges. Failing this, it will attempt to exploit the vulnerability CVE-2021-4034.

Ultimately, perfctl will attempt to establish a C2 link via Tor and spawn an XMRig miner to mine the Monero cryptocurrency. The traffic to the mining pool is encapsulated within Tor to limit network detection of the mining traffic.

Darktrace’s Cloudypots system has observed 1,959 infections of the perfectl campaign across its honeypot network in the past year, making it one of the most aggressive campaigns seen by Darktrace.

Key takeaways

This blog has shown how Darktrace / Forensic Acquisition & Investigation equips defenders in the face of a real-world attacker campaign. By using this solution, organizations can acquire forensic evidence and investigate intrusions across multiple cloud resources and providers, enabling defenders to see the full picture of an intrusion on day one. Forensic Acquisition & Investigation’s patented data-processing system takes advantage of the cloud’s scale to rapidly process large amounts of data, allowing triage to take minutes, not hours.

Darktrace / Forensic Acquisition & Investigation is available as Software-as-a-Service (SaaS) but can also be deployed on-premises as a virtual application or natively in the cloud, providing flexibility between convenience and data sovereignty to suit any use case.

Support for acquiring traditional compute instances like EC2, as well as more exotic and newly targeted platforms such as ECS and Lambda, ensures that attacks taking advantage of Living-off-the-Cloud (LOTC) strategies can be triaged quickly and easily as part of incident response. As attackers continue to develop new techniques, the ability to investigate how they use cloud services to persist and pivot throughout an environment is just as important to triage as a single compromised EC2 instance.

Credit to Nathaniel Bill (Malware Research Engineer)

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Nathaniel Bill
Malware Research Engineer

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February 19, 2026

CVE-2026-1731: How Darktrace Sees the BeyondTrust Exploitation Wave Unfolding

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Note: Darktrace's Threat Research team is publishing now to help defenders. We will continue updating this blog as our investigations unfold.

Background

On February 6, 2026, the Identity & Access Management solution BeyondTrust announced patches for a vulnerability, CVE-2026-1731, which enables unauthenticated remote code execution using specially crafted requests.  This vulnerability affects BeyondTrust Remote Support (RS) and particular older versions of Privileged Remote Access (PRA) [1].

A Proof of Concept (PoC) exploit for this vulnerability was released publicly on February 10, and open-source intelligence (OSINT) reported exploitation attempts within 24 hours [2].

Previous intrusions against Beyond Trust technology have been cited as being affiliated with nation-state attacks, including a 2024 breach targeting the U.S. Treasury Department. This incident led to subsequent emergency directives from  the Cybersecurity and Infrastructure Security Agency (CISA) and later showed attackers had chained previously unknown vulnerabilities to achieve their goals [3].

Additionally, there appears to be infrastructure overlap with React2Shell mass exploitation previously observed by Darktrace, with command-and-control (C2) domain  avg.domaininfo[.]top seen in potential post-exploitation activity for BeyondTrust, as well as in a React2Shell exploitation case involving possible EtherRAT deployment.

Darktrace Detections

Darktrace’s Threat Research team has identified highly anomalous activity across several customers that may relate to exploitation of BeyondTrust since February 10, 2026. Observed activities include:

Outbound connections and DNS requests for endpoints associated with Out-of-Band Application Security Testing; these services are commonly abused by threat actors for exploit validation.  Associated Darktrace models include:

  • Compromise / Possible Tunnelling to Bin Services

Suspicious executable file downloads. Associated Darktrace models include:

  • Anomalous File / EXE from Rare External Location

Outbound beaconing to rare domains. Associated Darktrace models include:

  • Compromise / Agent Beacon (Medium Period)
  • Compromise / Agent Beacon (Long Period)
  • Compromise / Sustained TCP Beaconing Activity To Rare Endpoint
  • Compromise / Beacon to Young Endpoint
  • Anomalous Server Activity / Rare External from Server
  • Compromise / SSL Beaconing to Rare Destination

Unusual cryptocurrency mining activity. Associated Darktrace models include:

  • Compromise / Monero Mining
  • Compromise / High Priority Crypto Currency Mining

And model alerts for:

  • Compromise / Rare Domain Pointing to Internal IP

IT Defenders: As part of best practices, we highly recommend employing an automated containment solution in your environment. For Darktrace customers, please ensure that Autonomous Response is configured correctly. More guidance regarding this activity and suggested actions can be found in the Darktrace Customer Portal.  

Appendices

Potential indicators of post-exploitation behavior:

·      217.76.57[.]78 – IP address - Likely C2 server

·      hXXp://217.76.57[.]78:8009/index.js - URL -  Likely payload

·      b6a15e1f2f3e1f651a5ad4a18ce39d411d385ac7  - SHA1 - Likely payload

·      195.154.119[.]194 – IP address – Likely C2 server

·      hXXp://195.154.119[.]194/index.js - URL – Likely payload

·      avg.domaininfo[.]top – Hostname – Likely C2 server

·      104.234.174[.]5 – IP address - Possible C2 server

·      35da45aeca4701764eb49185b11ef23432f7162a – SHA1 – Possible payload

·      hXXp://134.122.13[.]34:8979/c - URL – Possible payload

·      134.122.13[.]34 – IP address – Possible C2 server

·      28df16894a6732919c650cc5a3de94e434a81d80 - SHA1 - Possible payload

References:

1.        https://nvd.nist.gov/vuln/detail/CVE-2026-1731

2.        https://www.securityweek.com/beyondtrust-vulnerability-targeted-by-hackers-within-24-hours-of-poc-release/

3.        https://www.rapid7.com/blog/post/etr-cve-2026-1731-critical-unauthenticated-remote-code-execution-rce-beyondtrust-remote-support-rs-privileged-remote-access-pra/

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About the author
Emma Foulger
Global Threat Research Operations Lead
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