Unmasking Holiday Doppelgangers | Cyber AI Defense Strategy
Protect your online holiday shopping this season with Cyber AI. Learn how to spot doppelganger domains and prevent cyber-attacks in real time. Stay secure!
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
Justin Fier
SVP, Red Team Operations
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17
Dec 2019
Year after year, the holiday season witnesses an unprecedented exchange of cash in cyberspace, with American consumers alone projected to spend a record $143.7 billion on online holiday shopping in 2019.
And amid the desperation to take advantage of digital doorbusters, shoppers can find themselves racing between dozens of retail sites — all in pursuit of the dream deal.
Figure 1: The majority of holiday shopping is now done online. Data source: Adobe Digital Insights.
This frenzy of passwords, money, and credit card information changing hands over the winter months coalesces into the perfect storm for cyber-attacks. In November and December of last year, Darktrace observed a 128% rise in trojan attacks across our customer base relative to the previous two months. Such trojans, which leverage social engineering to mask their true nature, are often facilitated by “doppelganger” domains — slight variations of legitimate domain names that are used for malicious purposes. Indeed, doppelganger attacks in particular increased by 70% during the 2018 holidays, per Darktrace’s internal research.
For employees bombarded with time-sensitive discounts on their work devices and corporate email accounts, it is all too easy to miss the subtle signs of a doppelganger, while just a single click can cause an enterprise-wide breach. As a result, neither these employees nor traditional email security tools — which cannot be programmed in advance to spot the infinity of possible fake domains — are sufficient as a last line of defense. Rather, the only reliable way to sniff out convincing doppelgangers is Cyber AI. By learning the online behavior of each unique user and device that it protects, without preprogrammed rules or fixed IP blacklists, Cyber AI can distinguish between “naughty” and “nice” domains in real time.
Exposing a holiday doppelganger
Darktrace recently detected a doppelganger attack before it completed its objective: stealing sensitive financial information. Threat-actors typically attempt to recreate popular websites, and in this case, the duplicitous site masqueraded as an Amazon-associated page. Of course, the webpage had no connection to the genuine retail entity. Yet the targeted device’s firewall did not block it, since there is no way to anticipate all future doppelganger domains. And while the webpage also had misspellings and fake product images, the user — perhaps rushing to take advantage of a deal — did not notice.
Figure 2: The doppelganger page — only a close examination reveals the irregularities highlighted above.
Most major businesses today utilize the standard security protocol “https://,” especially when payment information is involved, to encrypt the sensitive data being transferred. This measure alone does not guarantee a safe connection if the website itself was created or compromised by malicious actors — notwithstanding the digital padlock that appears beside HTTPS URLs. This doppelganger site, though, used the unencrypted HTTP protocol shown below (hence the unsecure padlock in Figure 2):
http://amazoner.info/checkout/
Because a significant percentage of legitimate websites still use HTTP, blocking connections to all such sites would be a mistake. By contrast, Darktrace Cyber AI, which had developed a nuanced understanding of the user’s online activity, correlated several weak indicators of compromise to flag the doppelganger as a potential threat.
Figure 3: Darktrace flags the site as a 100% rare for the targeted user.
Once on the initial webpage, the user — engaged in what they believed to be regular online shopping — navigated to linked sites that were apparently associated with other popular clothing retailers:
ebay.amazoner.info
johnlewis.com.amazoner.info
asos.com.amazoner.inf
argos.co.uk.amazoner.info
indeed.co.uk.amazoner.info
Darktrace, again, determined that the escalating activity was highly unusual for the particular user. At this point, the security team was able to take the device offline for further investigation — before the user had entered any financial information.
’Tis the season to be secure
When it comes to what methods cyber-criminals will turn to next, the holiday season is full of unpredictability. No one knows what exactly the next doppelganger will look like, meaning that perimeter tools struggle to identify novel attacks before it’s too late.
As individual users, it is imperative to be wary of emails and ads that seem at all suspicious, even if it isn’t clear why. And when in doubt, it is always better to navigate directly to retail sites like Amazon from your browser, rather than clicking on an email link. The default disposition when shopping online — especially during the holidays — should be overcautiousness. Keep an eye out for broken language, typos, and design flaws that would all be rare on trustworthy retail sites, ensure URLs are legitimate before entering any information, and in general, trust your instincts when they sense something is amiss.
From an organizational standpoint, on the other hand, assume that employees won’t do any of the above. Human error is responsible for the vast majority of breaches, so expecting employees and conventional security tools to never allow attackers into the network is a recipe for compromise. Instead, to prepare for the inevitability of attack, what’s needed are Cyber AI tools that detect in-progress threats — not by predefining ‘bad’ but by understanding ‘self’. With self-learning Cyber AI, organizations are now readying themselves for the holidays, for sophisticated doppelgangers, and for the unpredictable.
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.
Bytesize Security: Insider Threats in Google Workspace
What is an insider threat?
An insider threat is a cyber risk originating from within an organization. These threats can involve actions such as an employee inadvertently clicking on a malicious link (e.g., a phishing email) or an employee with malicious intent conducting data exfiltration for corporate sabotage.
Insiders often exploit their knowledge and access to legitimate corporate tools, presenting a continuous risk to organizations. Defenders must protect their digital estate against threats from both within and outside the organization.
For example, in the summer of 2024, Darktrace / IDENTITY successfully detected a user in a customer environment attempting to steal sensitive data from a trusted Google Workspace service. Despite the use of a legitimate and compliant corporate tool, Darktrace identified anomalies in the user’s behavior that indicated malicious intent.
Attack overview: Insider threat
In June 2024, Darktrace detected unusual activity involving the Software-as-a-Service (SaaS) account of a former employee from a customer organization. This individual, who had recently left the company, was observed downloading a significant amount of data in the form of a “.INDD” file (an Adobe InDesign document typically used to create page layouts [1]) from Google Drive.
While the use of Google Drive and other Google Workspace platforms was not unexpected for this employee, Darktrace identified that the user had logged in from an unfamiliar and suspicious IPv6 address before initiating the download. This anomaly triggered a model alert in Darktrace / IDENTITY, flagging the activity as potentially malicious.
Figure 1: A Model Alert in Darktrace / IDENTITY showing the unusual “.INDD” file being downloaded from Google Workspace.
Following this detection, the customer reached out to Darktrace’s Security Operations Center (SOC) team via the Security Operations Support service for assistance in triaging and investigating the incident further. Darktrace’s SOC team conducted an in-depth investigation, enabling the customer to identify the exact moment of the file download, as well as the contents of the stolen documents. The customer later confirmed that the downloaded files contained sensitive corporate data, including customer details and payment information, likely intended for reuse or sharing with a new employer.
In this particular instance, Darktrace’s Autonomous Response capability was not active, allowing the malicious insider to successfully exfiltrate the files. If Autonomous Response had been enabled, Darktrace would have immediately acted upon detecting the login from an unusual (in this case 100% rare) location by logging out and disabling the SaaS user. This would have provided the customer with the necessary time to review the activity and verify whether the user was authorized to access their SaaS environments.
Conclusion
Insider threats pose a significant challenge for traditional security tools as they involve internal users who are expected to access SaaS platforms. These insiders have preexisting knowledge of the environment, sensitive data, and how to make their activities appear normal, as seen in this case with the use of Google Workspace. This familiarity allows them to avoid having to use more easily detectable intrusion methods like phishing campaigns.
Darktrace’s anomaly detection capabilities, which focus on identifying unusual activity rather than relying on specific rules and signatures, enable it to effectively detect deviations from a user’s expected behavior. For instance, an unusual login from a new location, as in this example, can be flagged even if the subsequent malicious activity appears innocuous due to the use of a trusted application like Google Drive.
Credit to Vivek Rajan (Cyber Analyst) and Ryan Traill (Analyst Content Lead)
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RansomHub Ransomware: investigación de Darktrace sobre la herramienta más nueva en ShadowSyndicate's Arsenal
What is ShadowSyndicate?
ShadowSyndicate, also known as Infra Storm, is a threat actor reportedly active since July 2022, working with various ransomware groups and affiliates of ransomware programs, such as Quantum, Nokoyawa, and ALPHV. This threat actor employs tools like Cobalt Strike, Sliver, IcedID, and Matanbuchus malware in its attacks. ShadowSyndicate utilizes the same SSH fingerprint (1ca4cbac895fc3bd12417b77fc6ed31d) on many of their servers—85 as of September 2023. At least 52 of these servers have been linked to the Cobalt Strike command and control (C2) framework [1].
What is RansomHub?
First observed following the FBI's takedown of ALPHV/BlackCat in December 2023, RansomHub quickly gained notoriety as a Ransomware-as-a-Service (RaaS) operator. RansomHub capitalized on the law enforcement’s disruption of the LockBit group’s operations in February 2024 to market themselves to potential affiliates who had previously relied on LockBit’s encryptors. RansomHub's success can be largely attributed to their aggressive recruitment on underground forums, leading to the absorption of ex-ALPHV and ex-LockBit affiliates. They were one of the most active ransomware operators in 2024, with approximately 500 victims reported since February, according to their Dedicated Leak Site (DLS) [2].
ShadowSyndicate and RansomHub
External researchers have reported that ShadowSyndicate had as many as seven different ransomware families in their arsenal between July 2022, and September 2023. Now, ShadowSyndicate appears to have added RansomHub’s their formidable stockpile, becoming an affiliate of the RaaS provider [1].
Darktrace’s analysis of ShadowSyndicate across its customer base indicates that the group has been leveraging RansomHub ransomware in multiple attacks in September and October 2024. ShadowSyndicate likely shifted to using RansomHub due to the lucrative rates offered by this RaaS provider, with affiliates receiving up to 90% of the ransom—significantly higher than the general market rate of 70-80% [3].
In many instances where encryption was observed, ransom notes with the naming pattern “README_[a-zA-Z0-9]{6}.txt” were written to affected devices. The content of these ransom notes threatened to release stolen confidential data via RansomHub’s DLS unless a ransom was paid. During these attacks, data exfiltration activity to external endpoints using the SSH protocol was observed. The external endpoints to which the data was transferred were found to coincide with servers previously associated with ShadowSyndicate activity.
Darktrace’s coverage of ShadowSyndicate and RansomHub
Darktrace’s Threat Research team identified high-confidence indicators of compromise (IoCs) linked to the ShadowSyndicate group deploying RansomHub. The investigation revealed four separate incidents impacting Darktrace customers across various sectors, including education, manufacturing, and social services. In the investigated cases, multiple stages of the kill chain were observed, starting with initial internal reconnaissance and leading to eventual file encryption and data exfiltration.
Attack Overview
Internal Reconnaissance
The first observed stage of ShadowSyndicate attacks involved devices making multiple internal connection attempts to other internal devices over key ports, suggesting network scanning and enumeration activity. In this initial phase of the attack, the threat actor gathers critical details and information by scanning the network for open ports that might be potentially exploitable. In cases observed by Darktrace affected devices were typically seen attempting to connect to other internal locations over TCP ports including 22, 445 and 3389.
C2 Communication and Data Exfiltration
In most of the RansomHub cases investigated by Darktrace, unusual connections to endpoints associated with Splashtop, a remote desktop access software, were observed briefly before outbound SSH connections were identified.
Following this, Darktrace detected outbound SSH connections to the external IP address 46.161.27[.]151 using WinSCP, an open-source SSH client for Windows used for secure file transfer. The Cybersecurity and Infrastructure Security Agency (CISA) identified this IP address as malicious and associated it with ShadowSyndicate’s C2 infrastructure [4]. During connections to this IP, multiple gigabytes of data were exfiltrated from customer networks via SSH.
Data exfiltration attempts were consistent across investigated cases; however, the method of egress varied from one attack to another, as one would expect with a RaaS strain being employed by different affiliates. In addition to transfers to ShadowSyndicate’s infrastructure, threat actors were also observed transferring data to the cloud storage and file transfer service, MEGA, via HTTP connections using the ‘rclone’ user agent – a command-line program used to manage files on cloud storage. In another case, data exfiltration activity occurred over port 443, utilizing SSL connections.
Lateral Movement
In investigated incidents, lateral movement activity began shortly after C2 communications were established. In one case, Darktrace identified the unusual use of a new administrative credential which was quickly followed up with multiple suspicious executable file writes to other internal devices on the network.
The filenames for this executable followed the regex naming convention “[a-zA-Z]{6}.exe”, with two observed examples being “bWqQUx.exe” and “sdtMfs.exe”.
Figure 1: Cyber AI Analyst Investigation Process for the SMB Writes of Suspicious Files to Multiple Devices' incident.
Additionally, script files such as “Defeat-Defender2.bat”, “Share.bat”, and “def.bat” were also seen written over SMB, suggesting that threat actors were trying to evade network defenses and detection by antivirus software like Microsoft Defender.
File Encryption
Among the three cases where file encryption activity was observed, file names were changed by adding an extension following the regex format “.[a-zA-Z0-9]{6}”. Ransom notes with a similar naming convention, “README_[a-zA-Z0-9]{6}.txt”, were written to each share. While the content of the ransom notes differed slightly in each case, most contained similar text. Clear indicators in the body of the ransom notes pointed to the use of RansomHub ransomware in these attacks. As is increasingly the case, threat actors employed double extortion tactics, threatening to leak confidential data if the ransom was not paid. Like most ransomware, RansomHub included TOR site links for communication between its "customer service team" and the target.
Figure 2: The graph shows the behavior of a device with encryption activity, using the “SMB Sustained Mimetype Conversion” and “Unusual Activity Events” metrics over three weeks.
Since Darktrace’s Autonomous Response capability was not enabled during the compromise, the ransomware attack succeeded in its objective. However, Darktrace’s Cyber AI Analyst provided comprehensive coverage of the kill chain, enabling the customer to quickly identify affected devices and initiate remediation.
Figure 3: Cyber AI Analyst panel showing the critical incidents of the affected device from one of the cases investigated.
In lieu of Autonomous Response being active on the networks, Darktrace was able to suggest a variety of manual response actions intended to contain the compromise and prevent further malicious activity. Had Autonomous Response been enabled at the time of the attack, these actions would have been quickly applied without any human interaction, potentially halting the ransomware attack earlier in the kill chain.
Figure 4: A list of suggested Autonomous Response actions on the affected devices."
Conclusion
The Darktrace Threat Research team has noted a surge in attacks by the ShadowSyndicate group using RansomHub’s RaaS of late. RaaS has become increasingly popular across the threat landscape due to its ease of access to malware and script execution. As more individual threat actors adopt RaaS, security teams are struggling to defend against the increasing number of opportunistic attacks.
For customers subscribed to Darktrace’s Security Operations Center (SOC) services, the Analyst team promptly investigated detections of the aforementioned unusual and anomalous activities in the initial infection phases. Multiple alerts were raised via Darktrace’s Managed Threat Detection to warn customers of active ransomware incidents. By emphasizing anomaly-based detection and response, Darktrace can effectively identify devices affected by ransomware and take action against emerging activity, minimizing disruption and impact on customer networks.
Credit to Kwa Qing Hong (Senior Cyber Analyst and Deputy Analyst Team Lead, Singapore) and Signe Zahark (Principal Cyber Analyst, Japan)
