As Arrow McLaren SP looks back on a positive season, the team reflects on key challenges, success, and how AI and automation is leveraged in their work!
As Arrow McLaren SP looks back on a positive season and prepares to build momentum into next year, Taylor Kiel (Team President) and Craig Hampson (Director of Trackside Engineering) reflect on key challenges and successes. With Pato O’Ward’s No. 5 car in the running to win the championship until the final race of the season, they reveal the formula for success – and how the team leverages AI and automation in every aspect of their work – from driver simulation to cyber security.
Data as the lifeblood for performance
In INDYCAR qualifiying, the difference between P1 and P10 can be as little as half a second, and when margins are that tight, the finer details in preparation make the difference. For us, that preparation is driven by data. Every race weekend and every practice session, over 100 lightweight sensors and several computers on the cars produce masses of data that is stored and analyzed for performance optimization.
This ecosystem includes an engine controller, a gear shift controller computer, and a computer unit that controls the clutch, and these systems all talk to each other across what is called a Controller Area Network (CAN). So the key question for us becomes: how do we get useful insights from that data, securely, and in a short period of time?
If you can think of something that’s happening on the car, the likelihood is our team is doing everything we can to try and measure it. Air speed, acceleration, tyre temperature, and so much more – we currently record over 1,500 data channels on the car itself, and we then process another 838 ‘math channels’ from combinations of this data – giving us, for example, the ride height of and downforce on the car.
This is more data than we can ever process with human beings alone, and a lot of our work now is figuring out how to automate these processes, using AI to look for patterns that humans simply cannot identify.
Pitting: More than just a tyre change
Each of our cars have two cellular-based telemetry systems built into them, but we are still limited on the amount of throughput we can observe real time, which is why we need to offload this data each time we pit during practice. This involves plugging in what we call an ‘umbilical cord’ that has a communication line and also powers the car.
Figure 1: A typical INDYCAR would last only minutes on its own battery without the engine running
Any typical race produces between 2.5GB and 3.3GB of data, in addition to in-car video, and a GPS system recording the car’s position on the track, which not only goes back to us but also to the relevant television broadcasters. So, we need to have a lot of storage available both in the cloud and on hard drives using a server. That data needs to be available not just to us at trackside but virtually to engineers not present at the race. And most importantly, that data needs to be secure, and protected from outside interference.
The cyber side: Turning to AI
All that precious data coming from the car, residing in the cloud or elsewhere in our organization, is susceptible to tampering from insiders and outsiders who may – deliberately or indirectly – compromise our ability to access or use that data reliably. As the cyber-threat landscape evolves – with ransomware bringing organizations of all shapes and sizes to a halt – we need to make sure we’re prepared for whatever attack is around the corner.
Firewalls, email gateways, and other perimeter protections are one part of the puzzle. But while these tools are focussed on keeping an attacker out – we needed another layer of defense that ensures that if these defenses are bypassed, we have an autonomous system that knows our organization inside out and can fight back on our behalf to disrupt emerging threats.
That’s where Darktrace has provided a revolutionary solution – using Self-Learning AI that understands every person and device from the ground up and identifies subtle deviations that point to a cyber-threat. And if ransomware strikes, 24/7 Autonomous Response is there in the form of Darktrace Antigena, taking precise action to contain ransomware and other threats at machine speed.
Double wins at doubleheaders
Using automation and AI throughout our technology stack enables us to extract meaningful insights from large pools of data and take quick, decisive action in the form of changes to the car or on-the-fly changes in race strategy.
The ability to react and react quickly is really put to the test on doubleheader race weekends, where any room for improvement you identify from Saturday’s race can be rectified in the form of overnight changes and implemented on Sunday. We believe it’s no coincidence that both of Pato’s No. 5 car’s wins came on the back end of doubleheader events, at Texas and Detroit Belle Isle. With people working in harmony with technology, our engineering team were able to make significant improvements to the car, react on the fly, and ultimately ensure we ended up ahead of the competition.
Digital fakes: Breaking new ground at Nashville
This year’s INDYCAR season featured a brand new track in Nashville, an exciting but daunting prospect for both the drivers and the team as a whole. Having access to a driver simulator, thanks to our partners at Chevrolet, we were able to run a virtual version of our car to try different setups, different techniques, and in this case have the driver learn his way round a whole new circuit.
Figure 2: The Chevrolet simulator projects a digital twin of the Nashville circuit
The track is recreated down to the nearest millimetre using a laser scanner, and then there is a lot of digital rendering involved, making it as realistic as possible with stands, fencing, and sponsor banners. Using this ‘digital fake’ representation was super helpful to the drivers in determining the correct approaches to corners, and for our engineers, enabling them to use the outputs to characterize the track.
The setup of the car in the simulator is effectively the same as the setup of the car in the real world: you set the spring rate and the ride height, it has the aerodynamic map, it knows the inertias and the masses of the car. It’s an incredibly complicated and powerful physics engine, but it gives us the ability to test things out in a controlled environment, and contributed toward one of Felix Rosenqvist’s strongest races of the season in the No. 7 car.
Simulations like these are the way of the future – not just for new circuits but in general. Rather than going through tyres and engines, we can replicate practice sessions in digital form, and the software gets closer to reality every day.
Looking ahead
What is next for Arrow McLaren SP? As we are now a part of the McLaren Racing family, new efficiencies and synergies are realized every month. We’ll certainly continue to leverage that valuable partnership, as well as our technology partnership with Darktrace, continuing to roll out their technology across our digital estate, including our email and cloud services.
In the INDYCAR Series, if you stay still, you go backwards, and the competition hots up every year. We know that now more than ever, the answer lies in using cutting-edge technologies across every aspect of the business to make our lives easier and ultimately propel us to the very top.
Like this and want more?
Receive the latest blog in your inbox
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
Newsletter
Stay ahead of threats with the Darktrace blog newsletter
Get the latest insights from the cybersecurity landscape, including threat trends, incident analysis, and the latest Darktrace product developments – delivered directly to your inbox, monthly.
Thanks, your request has been received
A member of our team will be in touch with you shortly.
Oops! Something went wrong while submitting the form.
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.
Author
Taylor Kiel
Team President, Arrow McLaren SP
Taylor Kiel is a native of Indianapolis, Indiana. His career highlights include starting with Sam Schmidt Motorsports in 2007 in Indy Lights before rising the ranks of now Arrow McLaren SP to president of the team. Kiel has been part of the team’s nine NTT INDYCAR SERIES wins and two Indianapolis 500 pole positions. He was also the race strategist during Pato O’Ward’s first career victory at Texas Motor Speedway in 2021 and led the team to a third-place finish in the point standings.
Craig Hampson
Director of Trackside Engineering, Arrow McLaren SP
Craig Hampson is a mechanical engineering graduate from the University of Maryland. In Hampson’s career, he was the Indianapolis 500-winning R&D engineer for the team that fielded cars for Ryan Hunter-Reay (2014) and Alexander Rossi (2016) and was at the helm of all four of Sebastien Bourdais’ Champ Car World Series titles and 33 of his 37 career NTT INDYCAR SERIES wins. Now, Hampson is the R&D Engineer at Arrow McLaren SP, and in 2020, he took on an expanded role as the race engineer for Fernando Alonso during the 105th Indianapolis 500. During the 2021 season, he served as the race strategist for Felix Rosenqvist and Juan Pablo Montoya on a limited basis.
With the perimeter all but dissolved, Network Detection and Response (NDR) tools are quickly becoming a critical component of the security stack, as the main tool to span the modern network. NDRs connect on-premises infrastructure to cloud, remote workers, identities, SaaS applications, and IoT/OT – something not available to EDR that requires agents and isolates visibility to individual devices.
KuppingerCole Analysts AG designated Darktrace an ‘Overall Leader’ position because of our continual innovation around user-led security. Self-Learning AI together with automated triage through Cyber AI Analyst and real-time autonomous response actions have been instrumental to security teams in stopping potential threats before they become a breach. With this time saved, Darktrace is leading beyond reactive security to truly harden a network, allowing the team to spend more time in preventive security measures.
Network Detection and Response protects where others fail to reach
NDR solutions operate at the network level, deploying inside or parallel to your network to ingest raw traffic via virtual or physical sensors. This gives them unprecedented potential to identify anomalies and possible breaches in any network - far beyond simple on-prem, into dynamic virtual environments, cloud or hybrid networks, cloud applications, and even remote devices accessing the corporate network via ZTNA or VPN.
Rather than looking at processes level data, NDR can detect the lateral movement of an adversary across multiple assets by analyzing network traffic patterns which endpoint solutions may not be able to identify [1]. In the face of a growing, complex environment, organizations large and small, will benefit from using NDRs either in conjunction, or as the foundation for, their Extended Detection and Response (XDR) for a unified view that improves their overall threat detection, ease of investigation and faster response times.
Today's NDR solutions are expected to include advanced ML and artificial intelligence (AI) algorithms [1]
Traditional IDS & IPS systems are labor intensive, requiring continuous rule creation, outdated signature maintenance, and manual monitoring for false positives or incorrect actions. This is no longer viable against a higher volume and changing landscape, making NDR the natural network tool to level against these evolutions. The role of AI in NDRs is designed to meet this challenge, “to reduce both the labor need for analysis and false positives, as well as add value by improving anomaly detection and overall security posture” .
Celebrating success in leadership and innovation
Darktrace is proud to have been recognized as an NDR “Overall Leader” in KuppingerCole Analyst AG’s Leadership Compass. The report gave further recognition to Darktrace as a ‘Product Leader”, “Innovation Leader” and “Market Leader”.
Maximum scores were received for core product categories, in addition to market presence and financial strength. Particular attention was directed to our innovation. This year has seen several NDR updates via Darktrace’s ActiveAI Security Platform version 6.2 which has enhanced investigation workflows and provided new AI transparency within the toolset.
Positive scores were also received for Darktrace’s deployment ecosystem and surrounding support, minimizing the need for extraneous integrations through a unique platform architecture that connects with over 90 other vendors.
Figure 1: High Scores received in Darktrace’s KuppingerCole Spider Chart across Core NDR capability areas
Darktrace’s pioneering AI approach sets it apart
Darktrace / NETWORK’s approach is fundamentally different to other NDRs. Continual anomaly-based detection (our Self-Learning AI), understands what is normal across each of your network entities, and then examines deviations from these behaviors rather than needing to apply static rules or ML to adversary techniques. As a result, Darktrace / NETWORK can focus on surfacing the novel threats that cannot be anticipated, whilst our proactive solutions expose gaps that can be exploited and reduce the risk of known threats.
Across the millions of possible network events that may occur, Darktrace’s Cyber AI Analyst reduces that manual workload for SOC teams by presenting only what is most important in complete collated incidents. This accelerates SOC Level 2 analyses of incidents by 10x2, giving time back, first for any necessary response and then for preventive workflows.
Finally, when incidents begin to escalate, Darktrace can natively (or via third-party) autonomously respond and take precise actions based on a contextual understanding of both the affected assets and incident in question so that threats can be disarmed without impacting wider operations.
Within the KuppingerCole report, several standout strengths were listed:
Cyber AI Analyst was celebrated as a core differentiator, enhancing both visibility and investigation into critical network issues and allowing a faster response.
Darktrace / NETWORK was singled for its user benefits. Both a clear interface for analysts with advanced filtering and analytical tools, and efficient role-based access control (RBAC) and configuration options for administrators.
At the product level, Darktrace was recognized for complete network traffic analysis (NTA) capabilities allowing extensive analysis into components like application use/type, fingerprinting, source/destination communication, in addition to comprehensive protocol support across a range of network device types from IT, OT, IoT and mobiles and detailed MITRE ATT&CK mapping.
Finally, at the heart of it, Darktrace’s innovation was highlighted in relation to its intrinsic Self Learning AI, utilizing multiple layers of deep learning, neural networks, LLMs, NLP, Generative AI and more to understand network activity and filter it for what’s critical on an individual customer level.
Going beyond reactive security
Darktrace’s visibility and AI-enabled detection, investigation and response enable security teams to focus on hardening gaps in their network through contextual relevance & priority. Darktrace / NETWORK explicitly gives time back to security teams allowing them to focus on the bigger strategic and governance workflows that sometimes get overlooked. This is enabled through proactive solutions intrinsically connected to our NDR:
Darktrace / Proactive Exposure Management, which looks beyond just CVE risks to instead discover, prioritize and validate risks by business impact and how to mobilize against them early, to reduce the number of real threats security teams face.
Darktrace / Incident Readiness & Recovery, a solution rather than service-based approach to incident response (IR) that lets teams respond in the best way to each incident and proactively test their familiarity and effectiveness of IR workflows with sophisticated incident simulations involving their own analysts and assets.
Together, these solutions allow Darktrace / NETWORK to go beyond the traditional NDR and shift teams to a more hardened and proactive state.
Putting customers first
Customers continue to sit at the forefront of Darktrace R&D, with their emerging needs and pain points being the direct inspiration for our continued innovation.
This year Darktrace / NETWORK has protected thousands of customers against the latest attacks, from data exfil and destruction, to unapproved privilege escalation and ransomware including strains like Medusa, Qilin and AlphV BlackCat.
In each instance, Darktrace / NETWORK was able to provide a holistic lens of the anomalies present in their traffic, collated those that were important, and either responded or gave teams the ability to take targeted actions against their threats – even when adversaries pivoted. In one example of a Gootloader compromise, Darktrace ensured a SOC went from detection to recovery within 5 days, 92.8% faster than the average containment time of 69 days.
Results like these, focused on user-led security, have secured Darktrace’s position within the latest NDR Leadership Compass.
From Royal to BlackSuit: Understanding the Tactics and Impact of a Sophisticated Ransomware Strain
What is BlackSuit Ransomware?
Since late 2023, Darktrace has detected BlackSuit ransomware infiltrating multiple customer networks in the US. This ransomware has targeted a wide range of industries, including arts, entertainment, real estate, public administration, defense, and social security.
Emerging in May 2023, BlackSuit is believed to be a spinoff of Royal ransomware due to similarities in code and Conti, and most likely consists of Russian and Eastern European hackers [1]. Recorded Future reported that the ransomware had affected 95 organizations worldwide, though the actual number is likely much higher [2]. While BlackSuit does not appear to focus on any particular sector, it has targeted multiple organizations in the healthcare, education, IT, government, retail and manufacturing industries [3]. Employing double extortion tactics, BlackSuit not only encrypts files but also steals sensitive data to leverage ransom payments.
BlackSuit has demanded over USD 500 million in ransoms, with the highest individual demand reaching USD 60 million [4]. Notable targets include CDK Global, Japanese media conglomerate Kadokawa, multiple educational institutions, Octapharma Plasma, and the government of Brazil [5][6][7][8].
Darktrace’s Coverage of BlackSuit Ransomware Attack
Case 1, November 2023
The earliest attack on a Darktrace customer by BlackSuit was detected at the start of November 2023. The unusual network activity began on a weekend—a time commonly chosen by ransomware groups to increase their chances of success, as many security teams operate with reduced staff. Darktrace identified indicators of the attackers’ presence on the network for almost two weeks, during which a total of 15 devices exhibited suspicious behavior.
The attack commenced with unusual internal SMB (Server Message Block) connections using a compromised service account. An internal device uploaded an executable (zzza.exe) to a domain controller (DC) and shortly after, wrote a script (socks5.ps1) to another device. According to a Cybersecurity Advisory from the CISA (Cybersecurity and Infrastructure Security Agency, US), the script file was a PowerShell reverse proxy [9].
Approximately an hour and a half later, the device to which the script was written exhibited uncommon WMI (Windows Management Instrumentation) activity. Two hours after receiving the executable file, the DC was observed making an outgoing NTLM request, using PowerShell to remotely execute commands, distributing differently named executable files (<PART OF THE CUSTOMER’S NAME>.exe), and controlling services on other devices.
Eighteen hours after the start of the unusual activity, Darktrace detected another device making repeated connections to “mystuff.bublup[.]com”, which the aforementioned CISA Advisory identifies as a domain used by BlackSuit for data exfiltration [9].
About ten minutes after the suspicious executables were distributed across the network, and less than 24 hours after the start of the unusual activity, file encryption began. A total of ten devices were seen appending the “.blacksuit” extension to files saved on other devices using SMB, as well as writing ransom notes (readme.blacksuit.txt). The file encryption lasted less than 20 minutes.
Figure 1: An example of the contents of a BlackSuit ransom note being written over SMB.
During this compromise, external connections to endpoints related to ConnectWise’s ScreenConnect remote management tool were also seen from multiple servers, suggesting that the tool was likely being abused for command-and-control (C2) activity. Darktrace identified anomalous connectivity associated with ScreenConnect was seen up to 11 days after the start of the attack.
10 days after the start of the compromise, an account belonging to a manager was detected adding “.blacksuit” extensions to the customer’s Software-a-Service (SaaS) resources while connecting from 173.251.109[.]106. Six minutes after file encryption began, Darktrace flagged the unusual activity and recommended a block. However, since Autonomous Response mode was not enabled, the customer’s security team needed to manually confirm the action. Consequently, suspicious activity continued for about a week after the initial encryption. This included disabling authentication on the account and an unusual Teams session initiated from the suspicious external endpoint 216.151.180[.]147.
Case 2, February 2024
Another BlackSuit compromise occurred at the start of February 2024, when Darktrace identified approximately 50 devices exhibiting ransomware-related activity in another US customer’s environment. Further investigation revealed that a significant number of additional devices had also been compromised. These devices were outside Darktrace’s purview to the customer’s specific deployment configuration. The threat actors managed to exfiltrate around 4 TB of data.
Initial access to the network was gained via a virtual private network (VPN) compromise in January 2024, when suspicious connections from a Romanian IP address were detected. According to CISA, the BlackSuit group often utilizes the services of initial access brokers (IAB)—actors who specialize in infiltrating networks, such as through VPNs, and then selling that unauthorized access to other threat actors [9]. Other initial access vectors include phishing emails, RDP (Remote Desktop Protocol) compromise, and exploitation of vulnerable public-facing applications.
Similar to the first case, the file encryption began at the end of the working week. During this phase of the attack, affected devices were observed encrypting files on other internal devices using two compromised administrator accounts. The encryption activity lasted for approximately six and a half hours. Multiple alerts were sent to the customer from Darktrace’s Security Operations Centre (SOC) team, who began reviewing the activity within four minutes of the start of the file encryption.
Figure 2: Darktrace’s Cyber AI Analyst clustering together multiple events related to unusual activity on the network, including file encryption over SMB by BlackSuit.
Figure 3: A spike in model alerts on the day when file encryption by BlackSuit was observed in the network.
In this case, the threat actor utilized SystemBC proxy malware for command and control (C2). A domain controller (DC) was seen connecting to 137.220.61[.]94 on the same day the file encryption took place. The DC was also observed connecting to a ProxyScrape domain around the same time, which is related to the SOCKS5 protocol used by SystemBC. During this compromise, RDP, SSH, and SMB were used for lateral movement within the network.
Figure 4: A Cyber AI Analyst investigation alerting to a device on the VPN subnet making suspicious internal SSH connections due to malicious actors moving laterally within the network.
Signs of threat actors potentially being on the network were observed as early as two days prior to the file encryption. This included unusual internal network scanning via multiple protocols (ICMP, SMB, RDP, etc.), credential brute-forcing, SMB access failures, and anonymous SMBv1 sessions. These activities were traced to IP addresses belonging to two desktop devices in the VPN subnet associated with two regular employee user accounts. Threat actors were seemingly able to exploit at least one of these accounts due to LDAP legacy policies being in place on the customer’s environment.
Figure 5: A Cyber AI Analyst incident summary alerting to a device on the VPN subnet conducting internal reconnaissance.
Figure 6: Examples of the proposed Darktrace Autonomous Response actions on the day BlackSuit initiated file encryption.
Case 3, August 2024
The most recently observed BlackSuit compromise occurred in August 2024, when a device was observed attempting to brute-force the credentials of an IT administrator. This activity continued for 11 days.
Once the admin’s account was successfully compromised, network scanning, unusual WMI, and SAMR (Security Account Manager Remote protocol) activity followed. A spike in the use of this account was detected on a Sunday—once again, the attackers seemingly targeting the weekend—when the account was used by nearly 50 different devices.
The compromised admin’s account was exploited for data gathering via SMB, resulting in the movement of 200 GB of data between internal devices in preparation for exfiltration. The files were then archived using the naming convention “*.part<number>.rar”.
Around the same time, Darktrace observed data transfers from 19 internal devices to “bublup-media-production.s3.amazonaws[.]com,” totaling just over 200 GB—the same volume of data gathered internally. Connections to other Bublup domains were also detected. The internal data download and external data transfer activity took approximately 8-9 hours.
Unfortunately, Darktrace was not configured in Autonomous Response mode at the time of the attack, meaning any mitigative actions to stop the data gathering or exfiltration required human confirmation.
Figure 7: One of the compromised devices was seen sending 80 GB of data to bublup-media-production.s3.amazonaws[.]com within a span of 4 hours.
Once the information was stolen, the threat actor moved on to the final stage of the attack—file encryption. Five internal devices, using either the compromised admin account or connecting via anonymous SMBv1 sessions, were seen encrypting files and writing ransom notes to five other devices on the network. The attempts at file encryption continued for around two hours, but Darktrace’s Autonomous Response capability was able to block the activity and prevent the attack from escalating.
Conclusion
The persistent and evolving threat posed by ransomware like BlackSuit underscores the critical importance of robust cybersecurity measures across all sectors. Since its emergence in 2023, BlackSuit has demonstrated a sophisticated approach to infiltrating networks, leveraging double extortion tactics, and demanding substantial ransoms. The cases highlighted above illustrate the varied methods and persistence of BlackSuit attackers, from exploiting VPN vulnerabilities to abusing remote management tools and targeting off-hours to maximize impact.
Although many similar connection patterns, such as the abuse of Bublup services for data exfiltration or the use of SOCKS5 proxies for C2, were observed during cases investigated by Darktrace, BlackSuit actors are highly sophisticated and tailors their attacks to each target organization. The consequences of a successful attack can be highly disruptive, and remediation efforts can be time-consuming and costly. This includes taking the entire network offline while responding to the incident, restoring encrypted files from backups (if available), dealing with damage to the organization’s reputation, and potential lawsuits.
These BlackSuit ransomware incidents emphasize the need for continuous vigilance, timely updates to security protocols, and the adoption of autonomous response technologies to swiftly counteract such attacks. As ransomware tactics continue to evolve, organizations must remain agile and informed to protect their critical assets and data. By learning from these incidents and enhancing their cybersecurity frameworks, organizations can better defend against the relentless threat of ransomware and ensure the resilience of their operations in an increasingly digital world.
Credit to Signe Zaharka (Principal Cyber Analyst) and Adam Potter (Senior Cyber Analyst)
Darktrace’s First 6: Half-Year Threat Report 2024 highlights the latest attack trends and key threats observed by the Darktrace Threat Research team in the first six months of 2024.
Focuses on anomaly detection and behavioral analysis to identify threats
Maps mitigated cases to known, publicly attributed threats for deeper context
Offers guidance on improving security posture to defend against persistent threats
Appendices
Darktrace Model Detections
Anomalous Connection / Data Sent to Rare Domain
Anomalous Connection / High Volume of New or Uncommon Service Control
Anomalous Connection / New or Uncommon Service Control
Anomalous Connection / Rare WinRM Outgoing
Anomalous Connection / SMB Enumeration
Anomalous Connection / Suspicious Activity On High Risk Device
Anomalous Connection / Suspicious Read Write Ratio
Anomalous Connection / Suspicious Read Write Ratio and Unusual SMB
Anomalous Connection / Sustained MIME Type Conversion
.blacksuit - File extension – When encrypting the files, this extension is appended to the filename – High
readme.blacksuit.txt – ransom note - A file demanding cryptocurrency payment in exchange for decrypting the victim's files and not leaking the stolen data – High
mystuff.bublup[.]com, bublup-media-production.s3.amazonaws[.]com – data exfiltration domains related to an organization and project management app that has document sharing functionality – High
137.220.61[.]94:4001 – SystemBC C2 related IP address (this tool is often used by other ransomware groups as well) - Medium
173.251.109[.]106 – IP address seen during a SaaS BlackSuit compromise (during file encryption) – Medium
216.151.180[.]147 – IP address seen during a SaaS BlackSuit compromise (during an unusual Teams session) - Medium
MITRE ATT&CK Mapping
Tactic - Technqiue
Account Manipulation - PERSISTENCE - T1098
Alarm Suppression - INHIBIT RESPONSE FUNCTION - T0878
Application Layer Protocol - COMMAND AND CONTROL - T1071
Automated Collection - COLLECTION - T1119
Block Command Message - INHIBIT RESPONSE FUNCTION - T0803
Block Reporting Message - INHIBIT RESPONSE FUNCTION - T0804
![One of the compromised devices was seen sending 80 GB of data to bublup-media-production.s3.amazonaws[.]com within a span of 4 hours.](https://cdn.prod.website-files.com/626ff4d25aca2edf4325ff97/673513f1135d0e009caf256f_6735136a725738f4afe4de2b_Fig%25207.png)
