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Inside the SOC
Ransomware
Detecting the unknown: revealing uncategorized ransomware using Darktrace
Uncategorized attacks happen frequently, with new threat groups and malware continually coming to light. Novel and known threat groups alike are changing their C2 domains, file hashes and other threat infrastructure, allowing them to avoid detection through traditional signature and rule-based techniques. Zero-day exploitation has also become increasingly apparent – a recent Mandiant report revealed that the number of identified zero-days in 2021 had dramatically increased from 2020 (80 vs 32). More specifically, the number of zero-days exploited by ransomware groups was, and continues to be, on an upward trend [1]. This trend appears to have continued into 2022. Given the unknown nature of these attacks, it is challenging to defend against them using traditional signature and rule-based approaches. Only those anomaly-based solutions functioning via deviations from normal behavior in a network, will effectively detect these threats.
It is particularly important that businesses can quickly identify threats like ransomware before the end-goal of encryption is reached. As the variety of ransomware strains increases, so do the number which are uncategorized. Whilst zero-days have recently been explored in another Darktrace blog, this blog looks at an example of a sophisticated novel ransomware attack that took place during Summer 2021 which Darktrace DETECT/Network detected ahead of it being categorized or found on popular OSINT. This occurred within the network of an East African financial organization.
On the 6th of July 2021, multiple user accounts were brute-forced on an external-facing VPN server via NTLM. Notably this included attempted logins with the generic account ‘Administrator’. Darktrace alerted to this initial bruteforcing activity, however as similar attempts had been made against the server before, it was not treated as a high-priority threat.
Following successful bruteforcing on the VPN, the malicious actor created a new user account which was then added to an administrative group on an Active Directory server. This new user account was subsequently used in an RDP session to an internal Domain Controller. Cyber AI Analyst picked up on the unusual nature of these administrative connections in comparison to normal activity for these devices and alerted on it (Figure 2).
Less than 20 minutes later, significant reconnaissance began on the domain controller with the new credential. This involved SMB enumeration with various file shares accessed including sensitive files such as the Security Account Manager (samr). This was followed by a two-day period of downtime where the threat actor laid low.
On the 8th of July, suspicious network behavior resumed – the default Administrator credential seen previously was also used on a second internal domain controller. Connections to a rare external IP were made by this device a few hours later. OSINT at the time suggested these connections may have been related to the use of penetration testing tools, in particular the tool Process Hacker [2].
Over the next two days reconnaissance and lateral movement activities occurred on a wider scale, originating from multiple network devices. A wide variety of techniques were used during this period:
· Exploitation of legitimate administrative services such as PsExec for remote command execution.
· Taking advantage of legacy protocols still in use on the network like SMB version 1.
· Bruteforcing login attempts via Kerberos.
· The use of other penetration testing tools including Metasploit and Nmap. These were intended to probe for vulnerabilities.
On the 10th of July, ransomware was deployed. File encryption occurred, with the extension ‘.blackbyte’ being appended to multiple files. At the time there were no OSINT references to this file extension or ransomware type, therefore any signature-based solution would have struggled to detect it. It is now apparent that BlackByte ransomware had only appeared a few weeks earlier and, since then, the Ransomware-as-a-Service group has been attacking businesses and critical infrastructure worldwide [3]. A year later they still pose an active threat.
The use of living-off-the-land techniques, popular penetration testing tools, and a novel strain of ransomware meant the attackers were able to move through the environment without giving away their presence through known malware-signatures. Although a traditional security solution would identify some of these actions, it would struggle to link these separate activities. The lack of attribution, however, had no bearing on Darktrace’s ability to detect the unusual behavior with its anomaly-based methods.
While this customer had RESPOND enabled at the time of this attack, its manual configuration meant that it was unable to act on the devices engaging in encryption. Nevertheless, a wide range of high-scoring Darktrace DETECT/Network models breached which were easily visible within the customer’s threat tray. This included multiple Enhanced Monitoring models that would have led to Proactive Threat Notifications (PTN) being alerted had the customer subscribed to the service. Whilst the attack was not prevented in this case, Darktrace analysts were able to give support to the customer via Ask the Expert (ATE), providing in-depth analysis of the compromise including a list of likely compromised devices and credentials. This helped the customer to work on post-compromise recovery effectively and ensured the ransomware had reduced impact within their environment.
Conclusion
While traditional security solutions may be able to deal well with ransomware that uses known signatures, AI is needed to spot new or unknown types of attack – a reliance on signatures will lead to these types of attack being missed.
Remediation can also be far more difficult if a victim doesn’t know how to identify the compromised devices or credentials because there are no known IOCs. Darktrace model breaches will highlight suspicious activity in each part of the cyber kill chain, whether involving a known IOC or not, helping the customer to efficiently identify areas of compromise and effectively remediate (Figure 3).
As long as threat actors continue to develop new methods of attack, the ability to detect uncategorized threats is required. As demonstrated above, Darktrace’s anomaly-based approach lends itself perfectly to detecting these novel or uncategorized threats.
Thanks to Max Heinemeyer for his contributions to this blog.
Appendices
Model Breaches
· Anomalous Connection / SMB Enumeration
· Anomalous Connection / Suspicious Activity On High Risk Device
· Anomalous Server Activity / Anomalous External Activity from Critical Network Device
· Compliance / Default Credential Usage
· Device / SMB Session Bruteforce
· Anomalous Connection / Sustained MIME Type Conversion
· Anomalous Connection / Unusual SMB Version 1 Connectivity
· Anomalous File / Internal / Additional Extension Appended to SMB File
· Compliance / Possible Unencrypted Password File on Server
· Compliance / SMB Drive Write
· Compliance / Weak Active Directory Ticket Encryption
· Compromise / Ransomware / Possible Ransom Note Write
· Compromise / Ransomware / Ransom or Offensive Words Written to SMB
· Compromise / Ransomware / SMB Reads then Writes with Additional Extensions
· Compromise / Ransomware / Suspicious SMB Activity
· Device / Attack and Recon Tools in SMB
· Device / Multiple Lateral Movement Model Breaches
· Device / New or Unusual Remote Command Execution
· Device / SMB Lateral Movement
· Device / Suspicious File Writes to Multiple Hidden SMB Shares
· Device / Suspicious Network Scan Activity
· Unusual Activity / Anomalous SMB Read & Write
· Unusual Activity / Anomalous SMB to Server
· User / Kerberos Password Bruteforce
References
[1] https://www.mandiant.com/resources/zero-days-exploited-2021
[2] https://www.virustotal.com/gui/ip-address/162.243.25.33/relations
[3] https://www.zscaler.com/blogs/security-research/analysis-blackbyte-ransomwares-go-based-variants
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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 [1].
Malicious actors typically gain entry to organizations’ Microsoft 365 environments by abusing either stolen account credentials or stolen session cookies [2]. 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 [3][4]. 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.
Darktrace Coverage
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.
Conclusion
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.
Appendices
MITRE ATT&CK Mapping
Reconnaissance:
• T1598 – Phishing for Information
Credential Access:
• T1110 – Brute Force
Initial Access:
• T1078.004 – Valid Accounts: Cloud Accounts
Command and Control:
• T1105 – Ingress Tool Transfer
Persistence:
• T1098.003 – Account Manipulation: Additional Cloud Roles
Collection:
• T1114 – Email Collection
Defense Evasion:
• T1564.008 – Hide Artifacts: Email Hiding Rules
Lateral Movement:
• 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)
References
[1] https://www.investing.com/academy/statistics/microsoft-facts/
[2] https://intel471.com/blog/countering-the-problem-of-credential-theft
[3] https://darktrace.com/blog/business-email-compromise-to-mass-phishing-campaign-attack-analysis
[4] https://darktrace.com/blog/breakdown-of-a-multi-account-compromise-within-office-365
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클라우드
Darktrace Integrates Self-Learning AI with Amazon Security Lake to Support Security Investigations
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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.
