How Autonomous Response AI is Winning Automated Extortion
19
Jun 2019
Darktrace, creator of the first enterprise-grade autonomous response technology, leverages AI algorithms to stop malware in its tracks. Learn more here!
Just threat detection is not enough
At a time when automated cyber-attacks execute at machine speed, the reality is that merely detecting these attacks is no longer sufficient to stop them before the damage is done. According to the Ponemon Institute’s oft-cited study on the topic, US companies take an average of 206 days to identify a data breach. And even when security teams discover a potential compromise the moment it begins, human professionals are fundamentally overmatched by malicious code that can encrypt or exfiltrate data in under a minute.
In this era of fast-acting threats, the only way forward is to fight code with code, to pit algorithm against algorithm, and to counter machine-speed attacks with machine-speed defenses. Darktrace, creator of the first enterprise-grade autonomous response technology, leverages AI algorithms to stop malware in its tracks, allowing incident responders to investigate and take action at their own pace. And critically, Darktrace safeguards the digital estate day and night, weekend and holiday, because cyber-criminals don’t wait until business hours to strike.
Examined below are three sophisticated attacks that Darktrace neutralized on behalf of security teams that were either out of office or unable to react in time. Collectively, they demonstrate that the future of autonomous cyber defense has already arrived.
Automated extortion, absent security team
The quintessential example of a cyber-threat too rapid for human professionals to parry, ransomware has become a top-of-mind concern for organizations around the world. In fact, previous research has found that approximately 70% of companies simply hand over the ransom upon getting hit, regardless of the cost. However, Darktrace's Autonomous Response prevents ransomware from spreading by confining users and devices to their typical ‘patterns of life’. Rooted in a constantly refined understanding of ‘self’ versus ‘not self’, Darktrace AI surgically intervenes to shut off just the anomalous activity, while still allowing business operations to continue uninterrupted.
At 7:05 pm on a Friday, an employee at a large telecommunications firm accessed his personal email from a corporate smartphone and was tricked into downloading a malicious file that contained ransomware. Seconds later, the device began connecting to an external server on the Tor network — executing the attack just after the company’s security team had left the office for the weekend.
Darktrace AI, meanwhile, responded nine seconds after encryption began, raising a prioritized alert that called for immediate action. As the behavior persisted over the next few seconds, Darktrace activated AI-enabled autonomous response, which interrupted all attempts to write encrypted files before the ransomware spread across the telecom’s network. Critically, the autonomous response technology was on guard, even when the security team couldn’t be.
Darktrace anticipates the alphabet
Nearly 95% of all successful cyber-attacks begin with a phishing email, which dupe employees into breaching their organizations before the security team realizes that anything is wrong. Even more difficult to catch are personalized “spear phishing” emails that use reconnaissance gathered from either social media or physical surveillance to impersonate trusted colleagues. Thwarting an advanced spear phishing campaign requires understanding normal behavior for each user well enough to flag subtly suspicious emails, as well as the ability to autonomously disable their malicious links — a combination that only Darktrace AI has achieved.
On the network of a major US city, a sophisticated spear phishing campaign managed to bypass the city’s native email controls. The attackers, who had obtained the city’s address book, were emailing recipients alphabetically, from “A” to “Z,” with ostensibly harmless emails that contained a malicious payload. Despite the well-disguised nature of this attack, Darktrace immediately flagged the domain linked in the emails as abnormal for the city’s employees, an action only possible with the evolving understanding of ‘self’ that Darktrace AI learns.
Darktrace's Autonomouse Response was deployed in ‘Passive Mode’ at the time, a trust-building setting that restricts the AI to communicating what it would have done in response to the threat rather than actually interceding. Interestingly enough, however, this nuance served to demonstrate the technology’s ability to stop attacks that conventional tools miss. Whereas Darktrace detected the campaign at the letter “A,” the city’s array of legacy tools finally woke up to the threat at “R.” In ‘Active Mode’, Darktrace would have neutralized the attack before it reached a single user.
Serious threat at amusement park
Data exfiltration is among the most common objectives of cyber-criminals today, as stolen personal information and credentials can be sold on the Dark Web, used to commit identity theft, or leveraged to move laterally within a victim’s network. At a North American amusement park, an advanced attacker targeted an IoT device — a physical locker designed to store personal belongings — in an attempt to exfiltrate such data. As part of its default setting, the ‘smart’ locker regularly established contact with the supplier’s third-party online platform, a process that the attackers hijacked to compromise the device.
Once infiltrated, the locker started to transfer more than a gigabyte of unencrypted data across the network to a rare external site. The connections, which likely included identifying details and sensitive credentials, had the potential to be transmitted over the internet entirely unprotected — allowing the attackers to intercept the connections and use the information to breach the company’s network perimeter.
Due to the severity of the threat, Darktrace determined that an autonomous response was required. Within seconds, Darktrace AI took action by intelligently blocking all outgoing connections from the compromised locker. In doing so, it gave ample time for the security team to remove the smart locker from the internet — before any sensitive company or consumer data could be exfiltrated.
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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
Justin Fier
SVP, Red Team Operations
Justin is one of the US’s leading cyber intelligence experts, and holds the position of SVP, Red Team Operations at Darktrace. His insights on cyber security and artificial intelligence have been widely reported in leading media outlets, including the Wall Street Journal, CNN, The Washington Post, and VICELAND. With over 10 years’ experience in cyber defense, Justin has supported various elements in the US intelligence community, holding mission-critical security roles with Lockheed Martin, Northrop Grumman Mission Systems and Abraxas. Justin is also a highly-skilled technical specialist, and works with Darktrace’s strategic global customers on threat analysis, defensive cyber operations, protecting IoT, and machine learning.
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, eduction, 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
Onomastics Gymnastics: How Darktrace Detects Spoofing and Business Email Compromise in Multi-Name Users
Note: For privacy reasons, actual surnames and email addresses observed in these incidents below have been replaced with fictitious placeholder names, using the common Spanish names “Fulano” and “Mengano”.
Naming conventions
Modeling names and their variants of members of an organization is a critical component to properly detect if those same names and variants are being spoofed by malicious actors. For many predominantly English-speaking organizations, these variants can largely be captured by variants of a person’s given name (e.g. James-Jimmy-Jim) and a consistent, singular surname or family name (e.g. Smith). Naming conventions, however, are far from universal. This piece will review how Darktrace / EMAIL manages the common naming conventions of much of the Spanish-speaking world, and can use its modeling to create high-fidelity detections of multiple types of spoofing attempts.
A brief summary of the common convention across Spain and much of Spanish-speaking America: most people are given one or two given names (e.g. Roberto, Juan, María, Natalia), and their surnames are the first surname of their father, followed by the first surname of their mother. While there are various exceptions to this norm, the below graphic Wikipedia [1][2] highlights the general rule.
Figure 1: Example Spanish naming convention for father “José García Torres” and mother “María Acosta Gómez” for child “Pablo García Acosta”. If shortened to one surname, the convention holds the child would be referred to as “Pablo García” [1].
Detection of improper name usage
Implicit in the above comment that shortening to one surname follows the convention of using the first surname, shortening to the second surname is often a tell-tale sign of someone unfamiliar with the person or their broader culture. This can be a useful corroborating feature in detecting a spoof attempt – analogous to a spelling error.
In the case of a Spanish customer, this misuse of name shortening contributed to the detection of a spoof attempt trying to solicit a response by impersonating an internal user forwarding information about ‘Data Protection’.
Figure 2: The Cyber AI Analyst summary of the Darktrace / EMAIL detections shows the use of the Gmail sender impersonating Isabel Maria Fulano Mengano, but incorrectly uses the second surname Mengano.
While the limited communication history from the sender and the nature of the text content already marks the mail as suspicious, Darktrace / EMAIL notes the personal name used in the email is similar to a high-value user (‘whale’ to use the terminology of spearphishing). The additional context provided by the detection of the attempted spoof prompted more severe actioning of this email, leading to a ‘Hold’ action instead of a less-severe ‘Unspoof’ action via a banner on the email.
Figure 3: The content summary of the sender showing the ‘Personal’ field of the email being ‘Isabel Mengano’, breaking from the standard name-shortening convention. The additional metrics identify features that might be anomalous about the sender.
Malicious email properly using both surnames
Misusing the name-shortening convention is not the only way that Darktrace / EMAIL can detect spoofing attempts. In the case of another Spanish customer, Darktrace observed a whale impersonation being sent to 230 users with solicitation content, but no links or attachments. Although the name was modeled internally in the “Surname, Given-name” format, Darktrace identified the spoofing attempt targeting a high-value user and took action, blocking the series of emails from reaching end-user inboxes to prevent unsuspecting users from responding.
Figure 4: Cyber AI Analyst summary of a suspicious email. The personal field is visible as ‘juan fulano mengano’, which is consistent with the reverse-order modelled user ‘fulano mengano, juan’. The subject line ‘Urgent Request’ sent to 230 users gives an intuitive indicator of the emails potentially being part of a malicious solicitation campaign.
In Summary: A case of onomastics gymnastics
The variety in valid usage of human language can be a barrier to evaluating when a given text is benign or malicious. Despite this, Darktrace / EMAIL is designed to manage this variety, as exemplified by the detections of two spoofing attempts seen against organizations using the distinct Spanish-speaking world’s common naming convention. The scope of this design as seen in this onomastic context, extends to a wide range of detections surrounding emails and their behavioral anomalies.
Credit to Roberto Romeu (Principal Cyber Analyst), Justin Torres (Senior Cyber Analyst) and Natalia Sánchez Rocafort (Senior Analyst Consultant).
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![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)
