다크트레이스의 사이버 AI 분석가의 소디노키비(REvil) 랜섬웨어 조사
Sodinokibi is one of the most lucrative ransomware strains of 2020, with its creators, cyber-criminal gang REvil, recently claiming over $100 million in profits this year alone. The prevalent threat is known to wipe backup files, encrypt files on local shares and exfiltrate data.
Exfiltration before encryption is a technique being increasingly adopted by profit-seeking cyber-criminals, who can threaten to leak the stolen data should a target organization not comply with their demands. Sodinobiki also makes heavy use of code obfuscation and encryption techniques to evade detection by signature-based, anti-virus solutions.
Darktrace’s AI recently detected Sodinokibi targeting a retail organization in the US. Prior to this year, the company operated primarily face-to-face in physical stores, but have conducted the majority of their business in the digital realm since the onset of the pandemic.
Cyber AI Analyst automatically launched a full investigation into this incident in real time, as the attack was unfolding. The technology provided summary reports of the entire incident which the security team could immediately action for incident response. This blog explores its findings.
Darktrace automatically investigated on the full scope of the Sodinokibi attack, with Cyber AI Analyst clearly identifying and summarising every stage of the attack lifecycle, which played out over the course of three weeks as below:
Darktrace produced a large number of security-relevant anomalies associated with just three credentials, and displayed these along a common timeline shown below:
While a human analyst might have been able to identify these unusual patterns and investigate what caused the clusters of anomalous activity, this process would have taken precious hours during a crisis. Cyber AI Analyst automatically performed the same analysis using supervised machine learning trained on Darktrace’s world-leading analysts, generating meaningful summaries of each stage of the event in real time, as the incident unfolded.
REvil ransomware attack
The following events occurred during a free trial period, and Darktrace was not being actively monitored. Its Autonomous Response technology, Darktrace Antigena, was installed in passive mode, and in the absence of automatic interference at an early stage, this compromise was allowed to unfold without interruption. However, with Darktrace’s AI learning normal ‘patterns of life’ for every device in the background, identifying anomalies, and launching an automated investigation into the attack, we are able to go back into the Threat Visualizer and see how the incident unfolded.
The attack began when the credentials of a highly privileged member of the retail organization’s IT team were compromised. REvil is known to make use of phishing emails, exploit kits, server vulnerabilities, and compromised MSP networks for initial intrusion.
In this case, the attacker used the IT credential to compromise a domain controller and exfiltrate data directly after initial reconnaissance. Darktrace’s AI detected the attacker logging into the domain controller via SMB, writing suspicious files and then deleting batch scripts and log files in the root directory to clear their tracks.
The domain controller then made connections to several rare external endpoints, and Darktrace witnessed a 28MB upload that was likely exfiltration of initial reconnaissance data. Four days later, the attacker connected to the same endpoint (sadstat[.]com) – likely a stager download for C2, which was then initiated via connections on port 443 later that same day.
A week on from the intial C2 connection, a SQL server was detected engaging in network scanning as the attacker sought to move laterally in search of sensitive and valuable data. Over the course of two weeks, Darktrace witnessed unusual internal RDP connections using administrative credentials, before data was uploaded to multiple cloud storage endpoints as well as an SSH server. PsExec was used to deploy the ransomware, resulting in file encryption.
The evasive nature of modern ransomware
REvil started with an inherent advantage in that they were armed with the credentials of a highly privileged IT admin. Nevertheless, they still made several attempts to evade traditional, signature-based tools, such as ‘Living off the Land’ – using common tools such PsExec, WMI, RDP to blend into to legitimate activity.
They leveraged frequently-used cloud storage solutions like Dropbox and pCloud for data transfer, and they conducted SSH on port 443, blending in with SSL connections on the same port. They used a newly-registered domain for C2 communication, meaning Open Source Intelligence Tools (OSINT) were blind to the threat.
Finally, the malware itself was evasive in that it made use of code obfuscation and encryption, and had no need for a system library or API imports. This is the basis for most modern ransomware attacks, and the reality is signature-based tools cannot keep up. Darktrace’s AI not only detected the anomalous activity associated with every stage of the attack, but generated fleshed-out summaries of each stage of the attack with Cyber AI Analyst.
Cyber AI Analyst: Real-time incident reporting
Between September 21 and October 12, Cyber AI Analyst created 15 incidents, investigating dozens of point detections and creating a coherent attack narrative.
Figure 3: Cyber AI Incident log of the first compromised DC. This incident tab details the connections to sadstat[.]com
Figure 4: The DC establishes C2 to the first GHOSTnet GmbH IP
Figure 5: This incident tab highlights the file encryption of files on network shares
Figure 6: Darktrace surfaces the IT admin account takeover
Figure 7: Example of a client type device involved in extensive administrative RDP and SMB activity, as well as data uploads to Dropbox (this upload to Dropbox occurs few seconds before file encryption begins)
REvil vs AI
This Sodinokibi ransomware attack slipped under the radar of a range of traditional tools deployed by the retail organization. However, despite the threat dwelling in the retail organization’s digital environment for over a month, and REvil using local tools to blend in to regular traffic, from Darktrace’s perspective these actions were noisy in comparison to the organization’s normal ‘pattern of life’, setting off a series of alerts and investigations.
Darktrace’s Cyber AI Analyst was able to autonomously investigate nearly every attack phase of the ransomware. The technology works around the clock, without requiring training or time off, and can often reduce hours or days of incident response into just minutes, reducing time to triage by up to 92% and augmenting the capabilities of the human security team.
Thanks to Darktrace analyst Joel Lee for his insights on the above threat find.
Learn more about Cyber AI Analyst
Darktrace model detections:
- Anomalous Connection / Active Remote Desktop Tunnel
- Anomalous Connection / Data Sent To New External Device
- Anomalous Connection / Data Sent to Rare Domain
- Anomalous Connection / High Volume of New or Uncommon Service Control
- Anomalous Connection / SMB Enumeration
- Anomalous Connection / Uncommon 1 GiB Outbound
- Anomalous Connection / Unusual Admin RDP Session
- Anomalous Connection / Unusual Admin SMB Session
- Anomalous File / Internal / Additional Extension Appended to SMB File
- Anomalous Server Activity / Anomalous External Activity from Critical Network Device
- Compliance / SMB Drive Write
- Compliance / Possible Tor Usage
- Compromise / Ransomware / Ransom or Offensive Words Written to SMB
- Compromise / Ransomware / Suspicious SMB Activity
- Device / ICMP Address Scan
- Device / Multiple Lateral Movement Model Breaches
- Device / Network Scan
- Device / New or Uncommon WMI Activity
- Device / New or Unusual Remote Command Execution
- Device / RDP Scan
- Device / Suspicious Network Scan Activity
- Unusual Activity / Enhanced Unusual External Data Transfer
- Unusual Activity / Unusual Internal Connections
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Inside the SOC
How Abuse of ‘PerfectData Software’ May Create a Perfect Storm: An Emerging Trend in Account Takeovers
Amidst the ever-changing threat landscape, new tactics, techniques, and procedures (TTPs) seem to emerge daily, creating extreme challenges for security teams. The broad range of attack methods utilized by attackers seems to present an insurmountable problem: how do you defend against a playbook that does not yet exist?
Faced with the growing number of novel and uncommon attack methods, it is essential for organizations to adopt a security solution able to detect threats based on their anomalies, rather than relying on threat intelligence alone.
In March 2023, Darktrace observed an emerging trend in the use of an application known as ‘PerfectData Software’ for probable malicious purposes in several Microsoft 365 account takeovers.
Using its anomaly-based detection, Darktrace DETECT™ was able to identify the activity chain surrounding the use of this application, potentially uncovering a novel piece of threat actor tradecraft in the process.
Microsoft 365 Intrusions
In recent years, Microsoft’s Software-as-a-Service (SaaS) suite, Microsoft 365, along with its built-in identity and access management (IAM) service, Azure Active Directory (Azure AD), have been heavily targeted by threat actors due to their near-ubiquitous usage across industries. Four out of every five Fortune 500 companies, for example, use Microsoft 365 services .
Malicious actors typically gain entry to organizations’ Microsoft 365 environments by abusing either stolen account credentials or stolen session cookies . Once inside, actors can access sensitive data within mailboxes or SharePoint repositories, and send out emails or Teams messages. This activity can often result in serious financial harm, especially in cases where the malicious actor’s end-goal is to elicit fraudulent transactions.
Darktrace regularly observes malicious actors behaving in predictable ways once they gain access to customer Microsoft 365 environment. One typical example is the creation of new inbox rules and sending deceitful emails intended to convince recipients to carry out subsequent actions, such as following a malicious link or providing sensitive information. It is also common for actors to register new applications in Azure AD so that they can be used to conduct follow-up activities, like mass-mailing or data theft. The registration of applications in Azure AD therefore seems to be a relatively predictable threat actor behavior . Darktrace DETECT understands that unusual application registrations in Azure AD may constitute a deviation in expected behavior, and therefore a possible indicator of account compromise.
These registrations of applications in Azure AD are evidenced by creations of, as well as assignments of permissions to, Service Principals in Azure AD. Darktrace has detected a growing trend in actors creating and assigning permissions to a Service Principal named ‘PerfectData Software’. Further investigation of this Azure AD activity revealed it to be part of an ongoing account takeover.
‘PerfectData Software’ Activity
Darktrace observed variations of the following pattern of activity relating to an application named ‘PerfectData Software’ within its customer base:
- Actor signs in to a Microsoft 365 account from an endpoint associated with a Virtual Private Server (VPS) or Virtual Private Network (VPN) service
- Actor registers an application called 'PerfectData Software' with Azure AD, and then grants permissions to the application
- Actor accesses mailbox data and creates inbox rule
In two separate incidents, malicious actors were observed conducting their activities from endpoints associated with VPN services (HideMyAss (HMA) VPN and Surfshark VPN, respectively) and from endpoints within the Autonomous System AS396073 MAJESTIC-HOSTING-01.
In March 2023, Darktrace observed a malicious actor signing in to a Microsoft 365 account from a Kuwait-based IP address within the Autonomous System, AS198605 AVAST Software s.r.o. This IP address is associated with the VPN service, HMA VPN. Over the next couple of days, an actor (likely the same malicious actor) signed in to the account several more times from two different Nigeria-based endpoints, as well as a VPS-related endpoint and a HMA VPN endpoint.
During their login sessions, the actor performed a variety of actions. First, they created and assigned permissions to a Service Principal named ‘PerfectData Software’. This Service Principal creation represents the registration of an application called ‘PerfectData Software’ in Azure AD. Although the reason for registering this application is unclear, within a few days the actor registered and granted permission to another application, ‘Newsletter Software Supermailer’, and created a new inbox rule names ‘s’ on the mailbox of the hijacked account. This inbox rule moved emails meeting certain conditions to a folder named ‘RSS Subscription. The ‘Newsletter Software Supermailer’ application was likely registered by the actor to facilitate mass-mailing activity.
Immediately after these actions, Darktrace detected the actor sending out thousands of malicious emails from the account. The emails included an attachment named ‘Credit Transfer Copy.html’, which contained a suspicious link. Further investigation revealed that the customer’s network had received several fake invoice emails prior to this initial intrusion activity. Additionally, there was an unusually high volume of failed logins to the compromised account around the time of the initial access.
In a separate case also observed by Darktrace in March 2023, a malicious actor was observed signing in to a Microsoft 365 account from an endpoint within the Autonomous System, AS397086 LAYER-HOST-HOUSTON. The endpoint appears to be related to the VPN service, Surfshark VPN. This login was followed by several failed and successful logins from a VPS-related within the Autonomous System, AS396073 MAJESTIC-HOSTING-01. The actor was then seen registering and assigning permissions to an application called ‘PerfectData Software’. As with the previous example, the motives for this registration are unclear. The actor proceeded to log in several more times from a Surfshark VPN endpoint, however, they were not observed carrying out any further suspicious activity.
It was not clear in either of these examples, nor in fact any of cases observed by Darktrace, why actors had registered and assigned permissions to an application called ‘PerfectData Software’, and there do not appear to be any open-source intelligence (OSINT) resources or online literature related to the malicious usage of an application by that name. That said, there are several websites which appear to provide email migration and data recovery/backup tools under the moniker ‘PerfectData Software’.
It is unclear whether the use of ‘PerfectData Software’ by malicious actors observed on the networks of Darktrace customers was one of these tools. However, given the nature of the tools, it is possible that the actors intended to use them to facilitate the exfiltration of email data from compromises mailboxes.
If the legitimate software ‘PerfectData’ is the application in question in these incidents, it is likely being purchased and misused by attackers for malicious purposes. It is also possible the application referenced in the incidents is a spoof of the legitimate ‘PerfectData’ software designed to masquerade a malicious application as legitimate.
Cases of ‘PerfectData Software’ activity chains detected by Darktrace typically began with an actor signing into an internal user’s Microsoft 365 account from a VPN or VPS-related endpoint. These login events, along with the suspicious email and/or brute-force activity which preceded them, caused the following DETECT models to breach:
- SaaS / Access / Unusual External Source for SaaS Credential Use
- SaaS / Access / Suspicious Login Attempt
- SaaS / Compromise / Login From Rare Following Suspicious Login Attempt(s)
- SaaS / Email Nexus / Unusual Location for SaaS and Email Activity
Subsequent activities, including inbox rule creations, registration of applications in Azure AD, and mass-mailing activity, resulted in breaches of the following DETECT models.
- SaaS / Admin / OAuth Permission Grant
- SaaS / Compromise / Unusual Logic Following OAuth Grant
- SaaS / Admin / New Application Service Principal
- IaaS / Admin / Azure Application Administration Activities
- SaaS / Compliance / New Email Rule
- SaaS / Compromise / Unusual Login and New Email Rule
- SaaS / Email Nexus / Suspicious Internal Exchange Activity
- SaaS / Email Nexus / Possible Outbound Email Spam
- SaaS / Compromise / Unusual Login and Outbound Email Spam
- SaaS / Compromise / Suspicious Login and Suspicious Outbound Email(s)
In cases where Darktrace RESPOND™ was enabled in autonomous response mode, ‘PerfectData Software’ activity chains resulted in breaches of the following RESPOND models:
• Antigena / SaaS / Antigena Suspicious SaaS Activity Block
• Antigena / SaaS / Antigena Significant Compliance Activity Block
In response to these model breaches, Darktrace RESPOND took immediate action, performing aggressive, inhibitive actions, such as forcing the actor to log out of the SaaS platform, and disabling the user entirely. When applied autonomously, these RESPOND actions would seriously impede an attacker’s progress and minimize network disruption.
In addition, Darktrace Cyber AI Analyst was able to autonomously investigate registrations of the ‘PerfectData Software’ application and summarized its findings into digestible reports.
Due to the widespread adoption of Microsoft 365 services in the workplace and continued emphasis on a remote workforce, account hijackings now pose a more serious threat to organizations around the world than ever before. The cases discussed here illustrate the tendency of malicious actors to conduct their activities from endpoints associated with VPN services, while also registering new applications, like PerfectData Software, with malicious intent.
While it was unclear exactly why the malicious actors were using ‘PerfectData Software’ as part of their account hijacking, it is clear that either the legitimate or spoofed version of the application is becoming an very likely emergent piece of threat actor tradecraft.
Darktrace DETECT’s anomaly-based approach to threat detection allowed it to recognize that the use of ‘PerfectData Software’ represented a deviation in the SaaS user’s expected behavior. While Darktrace RESPOND, when enabled in autonomous response mode, was able to quickly take preventative action against threat actors, blocking the potential use of the application for data exfiltration or other nefarious purposes.
MITRE ATT&CK Mapping
• T1598 – Phishing for Information
• T1110 – Brute Force
• T1078.004 – Valid Accounts: Cloud Accounts
Command and Control:
• T1105 – Ingress Tool Transfer
• T1098.003 – Account Manipulation: Additional Cloud Roles
• T1114 – Email Collection
• T1564.008 – Hide Artifacts: Email Hiding Rules
• T1534 – Internal Spearphishing
Unusual Source IPs
• 5.62.60[.]202 (AS198605 AVAST Software s.r.o.)
• 160.152.10[.]215 (AS37637 Smile-Nigeria-AS)
• 197.244.250[.]155 (AS37705 TOPNET)
• 169.159.92[.]36 (AS37122 SMILE)
• 45.62.170[.]237 (AS396073 MAJESTIC-HOSTING-01)
• 92.38.180[.]49 (AS202422 G-Core Labs S.A)
• 129.56.36[.]26 (AS327952 AS-NATCOM)
• 92.38.180[.]47 (AS202422 G-Core Labs S.A.)
• 107.179.20[.]214 (AS397086 LAYER-HOST-HOUSTON)
• 45.62.170[.]31 (AS396073 MAJESTIC-HOSTING-01)
Darktrace Integrates Self-Learning AI with Amazon Security Lake to Support Security Investigations
Darktrace has deepened its relationship with AWS by integrating its detection and response capabilities with Amazon Security Lake.
This development will allow mutual customers to seamlessly combine Darktrace AI’s bespoke understanding of their organization with the Threat Intelligence offered by other security tools, and investigate all of their alerts in one central location.
This integration will improve the value security teams get from both products, streamlining analyst workflows and improving their ability to detect and respond to the full spectrum of known and unknown cyber-threats.
How Darktrace and Amazon Security Lake augment security teams
Amazon Security Lake is a newly-released service that automatically centralizes an organization’s security data from cloud, on-premises, and custom sources into a customer owned purpose-built data lake. Both Darktrace and Amazon Security Lake support the Open Cybersecurity Schema Framework (OCSF), an open standard to simplify, combine, and analyze security logs.
Customers can store security logs, events, alerts, and other relevant data generated by various AWS services and security tools. By consolidating security data in a central lake, organizations can gain a holistic view of their security posture, perform advanced analytics, detect anomalies and open investigations to improve their security practices.
With Darktrace DETECT and RESPOND AI engines covering all assets across IT, OT, network, endpoint, IoT, email and cloud, organizations can augment the value of their security data lakes by feeding Darktrace’s rich and context-aware datapoints to Amazon Security Lake.
Amazon Security Lake empowers security teams to improve the protection of your digital estate:
- Quick and painless data normalization
- Fast-tracks ability to investigate, triage and respond to security events
- Broader visibility aids more effective decision-making
- Surfaces and prioritizes anomalies for further investigation
- Single interface for seamless data management
How will Darktrace customers benefit?
Across the Cyber AI Loop, all Darktrace solutions have been architected with AWS best practices in mind. With this integration, Darktrace is bringing together its understanding of ‘self’ for every organization with the centralized data visibility of the Amazon Security Lake. Darktrace’s unique approach to cyber security, powered by groundbreaking AI research, delivers a superior dataset based on a deep and interconnected understanding of the enterprise.
Where other cyber security solutions are trained to identify threats based on historical attack data and techniques, Darktrace DETECT gains a bespoke understanding of every digital environment, continuously analyzing users, assets, devices and the complex relationships between them. Our AI analyzes thousands of metrics to reveal subtle deviations that may signal an evolving issue – even unknown techniques and novel malware. It distinguishes between malicious and benign behavior, identifying harmful activity that typically goes unnoticed. This rich dataset is fed into RESPOND, which takes precise action to neutralize threats against any and every asset, no matter where data resides.
Both DETECT and RESPOND are supported by Darktrace Self-Learning AI, which provides full, real-time visibility into an organization’s systems and data. This always-on threat analysis already makes humans better at cyber security, improving decisions and outcomes based on total visibility of the digital ecosystem, supporting human performance with AI coverage and empowering security teams to proactively protect critical assets.
Converting Darktrace alerts to the Amazon Security Lake Open Cybersecurity Schema Framework (OCSF) supplies the Security Operations Center (SOC) and incident response team with contextualized data, empowering them to accelerate their investigation, triage and response to potential cyber threats.
Darktrace is available for purchase on the AWS Marketplace.
Learn more about how Darktrace provides full-coverage, AI-powered cloud security for AWS, or see how our customers use Darktrace in their AWS cloud environments.