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Black Basta: Old Dogs with New Tricks

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21
Sep 2023
21
Sep 2023
This blog discusses the emergence of Black Basta, a relatively new ransomware group that was first observed in early 2022. In April 2023, Darktrace detected a case of Black Basta on the customer network and was able to track the ransomware at every stage of the cyber kill chain.

What is Black Basta?

Over the past year, security researchers have been tracking a new ransomware group, known as Black Basta, that has been observed targeted organizations worldwide to deploy double extortion ransomware attacks since early 2022. While the strain and group are purportedly new, evidence seen suggests they are an offshoot of the Conti ransomware group [1].

The group behind Black Basta run a Ransomware as a Service (RaaS) model. They work with initial access brokers who will typically already have a foothold in company infrastructure to begin their attacks. Once inside a network, they then pivot internally using numerous tools to further their attack.

Black Basta Ransomware

Like many other ransomware actors, Black Basta uses double extortion as part of its modus operandi, exfiltrating sensitive company data and using the publication of this as a second threat to affected companies. This is also advertised on a dark web site, setup by the group to apply further pressure for affected companies to make ransom payments and avoid reputational damage.

The group also seems to regularly take advantage of existing tools to undertake the earlier stages of their attacks. Notably, the Qakbot banking trojan, seems to be the malware often used to gain an initial foothold within compromised environments.

Analysis of the tools, procedures and infrastructure used by Black Basta belies a maturity to the actors behind the ransomware. Their models and practices suggest those involved are experienced individuals, and security researchers have drawn possible links to the Conti ransomware group.

As such, Black Basta is a particular concern for security teams as attacks will likely be more sophisticated, with attackers more patient and able to lie low on digital estates for longer, waiting for the opportune moment to strike.

Cyber security is an infinite game where defender and attacker are stuck as cat and mouse; as new attacks evolve, security vendors and teams respond to the new indicators of compromise (IoCs), and update their existing rulesets and lists. As a result, attackers are forced to change their stripes to evade detection or sometimes even readjust their targets and end goals.

Anomaly Based Detection

By using the power of Darktrace’s Self-Learning AI, security teams are able to detect deviations in behavior. Threat actors need to move through the kill chain to achieve their aims, and in doing so will cause affected devices within networks to deviate from their expected pattern of life. Darktrace’s anomaly-based approach to threat detection allows it recognize these subtle deviations that indicate the presence of an attacker, and stop them in their tracks.

Additionally, the ecosystem of cyber criminals has matured in the last few decades. It is well documented how many groups now operate akin to legitimate companies, with structure, departments and governance. As such, while new attack methods and tactics do appear in the wild, the maturity in their business models belie the experience of those behind the attack.

As attackers grow their business models and develop their arsenal of attack vectors, it becomes even more critical for security teams to remain vigilant to anomalies within networks, and remain agnostic to underlying IoCs and instead adopt anomaly detection tools able to identify tactics, techniques, and procedures (TTPs) that indicate attackers may be moving through a network, ahead of deployment of ransomware and data encryption.

Darktrace’s Coverage of Black Basta

In April 2023, the Darktrace Security Operations Center (SOC) assisted a customer in triaging and responding to an ongoing ransomware infection on their network. On a Saturday, the customer reached out directly to the Darktrace analyst team via the Ask the Expert service for support after they observed encrypted files and locked administrative accounts on their network. The analyst team were able to investigate and clarify the attack path, identifying affected devices and assisting the customer with their remediation. Darktrace DETECT™ observed varying IoCs and TTPs throughout the course of this attack’s kill chain; subsequent analysis into these indicators revealed this had likely been a case of Black Basta seen in the wild.

Initial Intrusion

The methods used by the  group to gain an initial foothold in environments varies – sometimes using phishing, sometimes gaining access through a common vulnerability exposed to the internet. Black Basta actors appear to target specific organizations, as opposed to some groups who aim to hit multiple at once in a more opportunistic fashion.

In the case of the Darktrace customer likely affected by Black Basta, it is probable that the initial intrusion was out of scope. It may be that the path was via a phishing email containing an Microsoft Excel spreadsheet that launches malicious powershell commands; a noted technique for Black Basta. [3][4]  Alternatively, the group may have worked with access brokers who already had a foothold within the customer’s network.

One particular device on the network was observed acting anomalously and was possibly the first to be infected. The device attempted to connect to multiple internal devices over SMB, and connected to a server that was later found to be compromised and is described throughout the course of this blog. During this connection, it wrote a file over SMB, “syncro.exe”, which is possibly a legitimate Remote Management software but could in theory be used to spread an infection laterally. Use of this tool otherwise appears sporadic for the network, and was notably unusual for the environment.

Given these timings, it is possible this activity is related to the likely Black Basta compromise. However, there is some evidence online that use of Syncro has been seen installed as part of the execution of loaders such as Batloader, potentially indicating a separate or concurrent attack [5].

Internal Reconnaissance + Lateral Movement

However the attackers gained access in this instance, the first suspicious activity observed by Darktrace originated from an infected server. The attacker used their foothold in the device to perform internal reconnaissance, enumerating large portions of the network. Darktrace DETECT’s anomaly detection noted a distinct rise in connections to a large number of subnets, particularly to closed ports associated with native Windows services, including:

  • 135 (RPC)
  • 139 (NetBIOS)
  • 445 (SMB)
  • 3389 (RDP)

During the enumeration, SMB connections were observed during which suspiciously named executable files were written:

  • delete.me
  • covet.me

Data Staging and Exfiltration

Around 4 hours after the scanning activity, the attackers used their knowledge gained during enumeration about the environment to begin gathering and staging data for their double extortion attempts. Darktrace observed the same infected server connecting to a file storage server, and downloading over 300 GiB of data. Darktrace DETECT identified that the connections had been made via SMB and was able to present a list of filenames to the customer, allowing their security team to determine the data that had likely been exposed to the attackers.

The SMB paths detected by Darktrace showed a range of departments’ file areas being accessed by threat actors. This suggests they were interested in getting as much varied data as possible, presumably in an attempt to ensure a large amount of valuable information was at their disposal to make any threats of releasing them more credible, and more damaging to the company.

Shortly after the download, the device made an external connection over SSH to a rare domain, dataspt[.]com, hosted in the United States. The connection itself was made over an unusual port, 2022, and Darktrace recognized that the domain was new for the network.

During this upload, the threat actors uploaded a similar volume of data to the 300GiB that had been downloaded internally earlier. Darktrace flagged the usual elements of this external upload, making the identification and triage of this exfiltration attempt easier for the customer.

On top of this, Darktrace’s autonomous investigation tool Cyber AI Analyst™ launched an investigation into this on-going activity and was able to link the external upload events to the internal download, identifying them as one exfiltration incident rather than two isolated events. AI Analyst then provided a detailed summary of the activity detected, further speeding up the identification of affected files.

Preparing for Exploitation

All the activity documented so far had occurred on a Wednesday evening. It was at this point that the burst of activity calmed, and the ransomware lay in wait within the environment. Other devices around the network, particularly those connected to by the original infected server and a domain controller, were observed performing some elements of anomalous activity, but the attack seemed to largely take a pause.

However, on the Saturday morning, 3 days later, the compromised server began to change the way it communicated with attackers by reaching out to a new command and control (C2) endpoint. It seemed that attackers were gearing up for their attack, taking advantage of the weekend to strike while security teams often run with a reduced staffing.

Darktrace identified connections to a new endpoint within 4 minutes of it first being seen on the customer’s environment. The server had begun making repeated SSL connections to the new external endpoint, faceappinc[.]com, which has been flagged as malicious by various open-source intelligence (OSINT) sources.

The observed JA3 hash (d0ec4b50a944b182fc10ff51f883ccf7) suggests that the command-line tool BITS Admin was being used to launch these connections, another suggestion of the use of mature tooling.

In addition to this, Darktrace also detected the server using an administrative credential it had never previously been associated with. Darktrace recognized that the use of this credential represented a deviation from the device’s usual activity and thus could be indicative of compromise.

The server then proceeded to use the new credential to authenticate over Keberos before writing a malicious file (“management.exe”) to the Temp directory on a number of internal devices.

Encryption

At this point, the number of anomalous activities detected from the server increased massively as the attacker seems to connect networkwide in an attempt to cause as quick and destructive an encryption effort as possible. Darktrace observed numerous files that had been encrypted by a local process. The compromised server began to write ransom notes, named “instructions_read_me.txt” to other file servers, which presumably also had successfully deployed payloads. While Black Basta actors had initially been observed dropping ransom notes named “readme.txt”, security researchers have since observed and reported an updated variant of the ransomware that drops “instructions_read_me_.txt”, the name of the file detected by Darktrace, instead [6].

Another server was also observed making repeated SSL connections to the same rare external endpoint, faceappinc[.]com. Shortly after beginning these connections, the device made an HTTP connection to a rare IP address with no hostname, 212.118.55[.]211. During this connection, the device also downloaded a suspicious executable file, cal[.]linux. OSINT research linked the hash of this file to a Black Basta Executable and Linkable File (ELF) variant, indicating that the group was highly likely behind this ransomware attack.

Of particular interest again, is how the attacker lives off the land, utilizing pre-installed Windows services. Darktrace flagged that the server was observed using PsExec, a remote management executable, on multiple devices.

Darktrace Assistance

Darktrace DETECT was able to clearly detect and provide visibility over all stages of the ransomware attack, alerting the customer with multiple model breaches and AI Analyst investigation(s) and highlighting suspicious activity throughout the course of the attack.

For example, the exfiltration of sensitive data was flagged for a number of anomalous features of the meta-data: volume; rarity of the endpoint; port and protocol used.

In total, the portion of the attack observed by Darktrace lasted about 4 days from the first model breach until the ransomware was deployed. In particular, the encryption itself was initiated on a Saturday.

The encryption event itself was initiated on a Saturday, which is not uncommon as threat actors tend to launch their destructive attacks when they expect security teams will be at their lowest capacity. The Darktrace SOC team regularly observes and assists in customer’s in the face of ransomware actors who patiently lie in wait. Attackers often choose to strike as security teams run on reduced hours of manpower, sometimes even choosing to deploy ahead of longer breaks for national or public holidays, for example.

In this case, the customer contacted Darktrace directly through the Ask the Expert (ATE) service. ATE offers customers around the clock access to Darktrace’s team of expert analysts. Customers who subscribe to ATE are able to send queries directly to the analyst team if they are in need of assistance in the face of suspicious network activity or emerging attacks.

In this example, Darktrace’s team of expert analysts worked in tandem with Cyber AI Analyst to investigate the ongoing compromise, ensuring that the investigation and response process were completed as quickly and efficiently as possible.

Thanks to Darktrace’s Self-Learning AI, the analyst team were able to quickly produce a detailed report enumerating the timeline of events. By combining the human expertise of the analyst team and the machine learning capabilities of AI Analyst, Darktrace was able to quickly identify anomalous activity being performed and the affected devices. AI Analyst was then able to collate and present this information into a comprehensive and digestible report for the customer to consult.

Conclusion

It is likely that this ransomware attack was undertaken by the Black Basta group, or at least using tools related to their method. Although Black Basta itself is a relatively novel ransomware strain, there is a maturity and sophistication to its tactics. This indicates that this new group are actually experienced threat actors, with evidence pointing towards it being an offshoot of Conti.

The Pyramid of Pain is a well trodden model in cyber security, but it can help us understand the various features of an attack. Indicators like static C2 destinations or file hashes can easily be changed, but it’s the underlying TTPs that remain the same between attacks.

In this case, the attackers used living off the land techniques, making use of tools such as BITSAdmin, as well as using tried and tested malware such as Qakbot. While the domains and IPs involved will change, the way these malware interact and move about systems remains the same. Their fingerprint therefore causes very similar anomalies in network traffic, and this is where the strength of Darktrace lies.

Darktrace’s anomaly-based approach to threat detection means that these new attack types are quickly drawn out of the noise of everyday traffic within an environment. Once attackers have gained a foothold in a network, they will have to cause deviation from the usual pattern of a life on a network to proceed; Darktrace is uniquely placed to detect even the most subtle changes in a device’s behavior that could be indicative of an emerging threat.

Machine learning can act as a force multiplier for security teams. Working hand in hand with the Darktrace SOC, the customer was able to generate cohesive and comprehensive reporting on the attack path within days. This would be a feat for humans alone, requiring significant resources and time, but with the power of Darktrace’s Self-Learning AI, these deep and complex analyses become as easy as the click of a button.

Credit to: Matthew John, Director of Operations, SOC, Paul Jennings, Principal Analyst Consultant

Appendices

Darktrace DETECT Model Breaches

Internal Reconnaissance

Device / Multiple Lateral Movement Model Breaches

Device / Large Number of Model Breaches

Device / Network Scan

Device / Anomalous RDP Followed by Multiple Model Breaches

Device / Possible SMB/NTLM Reconnaissance

Device / SMB Lateral Movement

Anomalous Connection / SMB Enumeration

Anomalous Connection / Possible Share Enumeration Activity

Device / Suspicious SMB Scanning Activity

Device / RDP Scan

Anomalous Connection / Active Remote Desktop Tunnel

Device / Increase in New RPC Services

Device / ICMP Address Scan

Download and Upload

Unusual Activity / Enhanced Unusual External Data Transfer

Unusual Activity / Unusual External Data Transfer

Anomalous Connection / Uncommon 1 GiB Outbound

Anomalous Connection / Data Sent to Rare Domain

Anomalous Connection / Download and Upload

Compliance / SSH to Rare External Destination

Anomalous Server Activity / Rare External from Server

Anomalous Server Activity / Outgoing from Server

Anomalous Connection / Application Protocol on Uncommon Port

Anomalous Connection / Multiple Connections to New External TCP Port

Device / Anomalous SMB Followed By Multiple Model Breaches

Unusual Activity / SMB Access Failures

Lateral Movement and Encryption

User / New Admin Credentials on Server

Compliance / SMB Drive Write

Device / Anomalous RDP Followed By Multiple Model Breaches

Anomalous Connection / High Volume of New or Uncommon Service Control

Anomalous Connection / New or Uncommon Service Control

Device / New or Unusual Remote Command Execution

Anomalous Connection / SMB Enumeration

Additional Beaconing and Tooling

Device / Initial Breach Chain Compromise

Device / Multiple C2 Model Breaches

Compromise / Large Number of Suspicious Failed Connections

Compromise / Sustained SSL or HTTP Increase

Compromise / SSL or HTTP Beacon

Compromise / Suspicious Beaconing Behavior

Compromise / Large Number of Suspicious Successful Connections

Compromise / High Volume of Connections with Beacon Score

Compromise / Slow Beaconing Activity To External Rare

Compromise / SSL Beaconing to Rare Destination

Compromise / Beaconing Activity To External Rare

Compromise / Beacon to Young Endpoint

Compromise / Agent Beacon to New Endpoint

Anomalous Server Activity / Rare External from Server

Anomalous Connection / Multiple Failed Connections to Rare Endpoint

Anomalous File / EXE from Rare External Location

IoC - Type - Description + Confidence

dataspt[.]com - Hostname - Highly Likely Exfiltration Server

46.22.211[.]151:2022 - IP Address and Unusual Port - Highly Likely Exfiltration Server

faceappinc[.]com - Hostname - Likely C2 Infrastructure

Instructions_read_me.txt - Filename - Almost Certain Ransom Note

212.118.55[.]211 - IP Address - Likely C2 Infrastructure

delete[.]me - Filename - Potential lateral movement script

covet[.]me - Filename - Potential lateral movement script

d0ec4b50a944b182fc10ff51f883ccf7 - JA3 Client Fingerprint - Potential Windows BITS C2 Process

/download/cal.linux - URI - Likely BlackBasta executable file

1f4dcfa562f218fcd793c1c384c3006e460213a8 - Sha1 File Hash - Likely BlackBasta executable file

References

[1] https://blogs.blackberry.com/en/2022/05/black-basta-rebrand-of-conti-or-something-new

[2] https://www.cybereason.com/blog/threat-alert-aggressive-qakbot-campaign-and-the-black-basta-ransomware-group-targeting-u.s.-companies

[3] https://www.trendmicro.com/en_us/research/22/e/examining-the-black-basta-ransomwares-infection-routine.html

[4] https://unit42.paloaltonetworks.com/atoms/blackbasta-ransomware/

[5] https://www.trendmicro.com/en_gb/research/23/a/batloader-malware-abuses-legitimate-tools-uses-obfuscated-javasc.html

[6] https://www.pcrisk.com/removal-guides/23666-black-basta-ransomware

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.
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Matthew John
Director of Operations, SOC
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Inside the SOC

The Price of Admission: Countering Stolen Credentials with Darktrace

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03
Jun 2024

Using leaked credentials to gain unauthorized access

Dark web marketplaces selling sensitive data have increased accessibility for malicious actors, similar to Ransomware-as-a-Service (RaaS), lowering the barrier to entry usually associated with malicious activity. By utilizing leaked credentials, malicious actors can easily gain unauthorized access to accounts and systems which they can leverage to carry out malicious activities like data exfiltration or malware deployment.

Usage of leaked credentials by malicious actors is a persistent concern for both organizations and security providers. Google Cloud’s ‘H1 2024 Threat Horizons Report’ details that initial access seen in 2.9% of cloud compromises observed on Google Cloud resulted from leaked credential usage [1], with the ‘IBM X-Force Threat Intelligence Index 2024’ reporting 71% year-on-year increase in cyber-attacks which utilize stolen or compromised credentials [2].

Darktrace coverage of leaked credentials

In early 2024, one Darktrace customer was compromised by a malicious actor after their internal credentials had been leaked on the dark web. Subsequent attack phases were detected by Darktrace/Network and the customer was alerted to the suspicious activity via the Proactive Threat Notification (PTN) service, following an investigation by Darktrace’s Security Operation Center (SOC).

Darktrace detected a device on the network of a customer in the US carrying out a string of anomalous activity indicative of network compromise. The device was observed using a new service account to authenticate to a Virtual Private Network (VPN) server, before proceeding to perform a range of suspicious activity including internal reconnaissance and lateral movement.

Malicious actors seemingly gained access to a previously unused service account for which they were able to set up multi-factor authentication (MFA) to access the VPN. As this MFA setup was made possible by the configuration of the customer’s managed service provider (MSP), the initial access phase of the attack fell outside of Darktrace’s purview.

Unfortunately for the customer in this case, Darktrace RESPOND™ was not enabled on the network at the time of the attack. Had RESPOND been active, it would have been able to autonomously act against the malicious activity by disabling users, strategically blocking suspicious connections and limiting devices to their expected patterns of activity.

Attack timeline of leaked credentials spotted by darktrace

Network Scanning Activity

On February 22, 2024, Darktrace detected the affected device performing activity indicative of network scanning, namely initiating connections on multiple ports, including ports 80, 161 389 and 445, to other internal devices. While many of these internal connection attempts were unsuccessful, some successful connections were observed.

Devices on a network can gather information about other internal devices by performing network scanning activity. Defensive scanning can be used to support network security, allowing internal security teams to discover vulnerabilities and potential entry points that require their attention, however attackers are also able to take advantage of such information, such as open ports and services available on internal devices, with offensive scanning.

Brute Force Login Attempts

Darktrace proceeded to identify the malicious actor attempting to access a previously unused service account for which they were able to successfully establish MFA to access the organization’s VPN. As the customer’s third-party MSP had been configured to allow all users to login to the organization’s VPN using MFA, this login was successful. Moreover, the service account had never previously been used and MFA and never been established, allowing the attacker to leverage it for their own nefarious means.

Darktrace/Network identified the attacker attempting to authenticate over the Kerberos protocol using a total of 30 different usernames, of which two were observed successfully authenticating. There was a total of 6 successful Kerberos logins identified from two different credentials.  Darktrace also observed over 100 successful NTLM attempts from the same device for multiple usernames including “Administrator” and “mail”. These credentials were later confirmed by the customer to have been stolen and leaked on the dark web.

Advanced Search query results showing the usernames that successfully authenticated via NTLM.
Figure 1: Advanced Search query results showing the usernames that successfully authenticated via NTLM.

Even though MFA requirements had been satisfied when the threat actor accessed the organization’s VPN, Darktrace recognized that this activity represented a deviation from its previously learned behavior.

Malicious actors frequently attempt to gain unauthorized access to accounts and internal systems by performing login attempts using multiple possible usernames and passwords. This type of brute-force activity is typically accomplished using computational power via the use of software or scripts to attempt different username/password combinations until one is successful.

By purchasing stolen credentials from dark web marketplaces, attackers are able to significantly increase the success rate of brute-force attacks and, if they do gain access, they can easily act on their objectives, be that exfiltrating sensitive data or moving through their target networks to further the compromise.

Share Enumeration

Around 30 minutes after the initial network scanning activity, the compromised device was observed performing SMB enumeration using one of the aforementioned accounts. Darktrace understood that this activity was suspicious as the device had never previously been used to perform SMB activity and had not been tagged as a security device.

Darktrace/Network identifying the suspicious SMB enumeration performed by the compromised device.
Figure 2: Darktrace/Network identifying the suspicious SMB enumeration performed by the compromised device.

Such enumeration can be used by malicious actors to gain insights into the structures and configurations of a target device, view permissions associated with shared resources, and also view general identifying information about the system.

Darktrace further identified that the device connected to the named pipe “srvsvc”. By enumerating over srvsvc, a threat actor is able to request a list of all available SMB shares on a destination device, enabling further data gathering as part of network reconnaissance. Srvsvc also provides access to remote procedure call (RPC) for various services on a destination device.

At this stage, a Darktrace/Network Enhanced Monitoring model was triggered for lateral movement activity taking place on the customer’s network. As this particular customer was subscribed to the PTN service, the Enhanced Monitoring model alert was promptly triaged and investigated by the Darktrace SOC. The customer was alerted to the emerging activity and given full details of the incident and the SOC team’s investigation.

Attack and Reconnaissance Tool Usage

A few minutes later, Darktrace observed the device making a connection with a user agent associated with the Nmap network scanning tool, “Mozilla/5.0 (compatible; Nmap Scripting Engine; https://nmap.org/book/nse[.]html)”. While these tools are often used legitimately by an organization’s security team, they can also be used maliciously by attackers to exploit vulnerabilities that attackers may have unearthed during earlier reconnaissance activity.

As such services are often seen as normal network traffic, attackers can often use them to bypass traditional security measures. Darktrace’s Self-Learning AI, however, was able to recognize that the affected device was not a security device and therefore not expected to carry out such activity, even if it was using a legitimate Nmap service.

Darktrace/Network identifying the compromised device using the Nmap scanning tool.
Figure 3: Darktrace/Network identifying the compromised device using the Nmap scanning tool.

Further Lateral Movement

Following this suspicious Nmap usage, Darktrace observed a range of additional anomalous SMB activity from the aforementioned compromised account. The affected device attempted to establish almost 900 SMB sessions, as well as performing 65 unusual file reads from 29 different internal devices and over 300 file deletes for the file “delete.me” from over 100 devices using multiple paths, including ADMIN$, C$, print$.

Darktrace also observed the device making several DCE-RPC connections associated with Active Directory Domain enumeration, including DRSCrackNames and DRSGetNCChanges; a total of more than 1000 successful DCE-RPC connection were observed to a domain controller.

As this customer did not have Darktrace/Network's autonomous response deployed on their network, the above detailed lateral movement and network reconnaissance activity was allowed to progress unfettered, until Darktrace’s SOC alerted the customer’s security team to take urgent action. The customer also received follow-up support through Darktrace’s Ask the Expert (ATE) service, allowing them to contact the analyst team directly for further details and support on the incident.

Thanks to this early detection, the customer was able to quickly identify and disable affected user accounts, effectively halting the attack and preventing further escalation.

Conclusions

Given the increasing trend of ransomware attackers exfiltrating sensitive data for double extortion and the rise of information stealers, stolen credentials are commonplace across dark web marketplaces. Malicious actors can exploit these leaked credentials to drastically lower the barrier to entry associated with brute-forcing access to their target networks.

While implementing well-configured MFA and enforcing regular password changes can help protect organizations, these measures alone may not be enough to fully negate the advantage attackers gain with stolen credentials.

In this instance, an attacker used leaked credentials to compromise an unused service account, allowing them to establish MFA and access the customer’s VPN. While this tactic may have allowed the attacker to evade human security teams and traditional security tools, Darktrace’s AI detected the unusual use of the account, indicating a potential compromise despite the organization’s MFA requirements being met. This underscores the importance of adopting an intelligent decision maker, like Darktrace, that is able to identify and respond to anomalies beyond standard protective measures.

Credit to Charlotte Thompson, Cyber Security Analyst, Ryan Traill, Threat Content Lead

Appendices

Darktrace DETECT Model Coverage

-       Device / Suspicious SMB Scanning Activity (Model Alert)

-       Device / ICMP Address Scan (Model Alert)

-       Device / Network Scan (Model Alert)

-       Device / Suspicious LDAP Search Operation (Model Alert)

-       User / Kerberos Username Brute Force (Model Alert)

-       Device / Large Number of Model Breaches (Model Alert)

-       Anomalous Connection / SMB Enumeration (Model Alert)

-       Device / Multiple Lateral Movement Model Breaches (Enhanced Monitoring Model Alert)

-       Device / Possible SMB/NTLM Reconnaissance (Model Alert)

-       Anomalous Connection / Possible Share Enumeration Activity (Model Alert)

-       Device / Attack and Recon Tools (Model Alert)

MITRE ATT&CK Mapping

Tactic – Technique - Code

INITIAL ACCESS - Hardware Additions     -T1200

DISCOVERY - Network Service Scanning -T1046

DISCOVERY - Remote System Discovery - T1018

DISCOVERY - Domain Trust Discovery      - T1482

DISCOVERY - File and Directory Discovery - T1083

DISCOVERY - Network Share Discovery - T1135

RECONNAISSANCE - Scanning IP Blocks - T1595.001

RECONNAISSANCE - Vulnerability Scanning - T1595.002

RECONNAISSANCE - Client Configurations - T1592.004

RECONNAISSANCE - IP Addresses - T1590.005

CREDENTIAL ACCESS - Brute Force - T1110

LATERAL MOVEMENT - Exploitation of Remote Services -T1210

References

  1. 2024 Google Cloud Threat Horizons Report
    https://services.google.com/fh/files/misc/threat_horizons_report_h12024.pdf
  2. IBM X-Force Threat Intelligence Index 2024
    https://www.ibm.com/reports/threat-intelligence
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Charlotte Thompson
Cyber Analyst

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Exploring the Benefits and Risks of Third-Party Data Solutions

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03
Jun 2024

Why do companies allow third parties to handle their data?

Companies seek out third parties to handle their data for operational efficiency.

The scale and cost of maintaining in-house infrastructure can be outsourced to third parties who specialize in data management or in certain business functions.

Third parties who handle an organization’s data can range from large public cloud providers such as Azure or AWS, to boutique companies who handle specific business functions such as telemarketing, payment systems, or webpage hosting.

The operational efficiencies gained through third-party data management can be summarized by three key benefits:

  • Global accessibility: Third-party data storage enables data access across the globe, allowing businesses to access data from anywhere.
  • Enhanced collaboration: Third-party data storage allows for file sharing, real-time editing, and integration with other applications and services enhancing a business’s collaboration efforts.
  • Reliability and uptime: Reputable third-party storage providers offer high reliability and uptime guarantees, ensuring that data is available whenever needed. They typically have robust disaster recovery and backup systems in place to prevent data loss.

Given these benefits, it is no surprise that businesses are using these services to expand their operations and scale efforts with the need of a growing business. This strategic move not only optimizes resource allocation but also enhances operational agility, enabling businesses to adapt swiftly to evolving data demands and maintain a competitive edge in a dynamic market.

Security risks of entrusted data to third-party vendors

Entrusting data to third parties can expose businesses to supply chain risks and increase the risk of data breaches and unauthorized access. A business has less control over its data and becomes dependent on the third party's policies, practices, and uptime. Many third-party vendors are the target of hackers who specialize in monetizing sensitive data and exploiting gray areas around who is responsible for securing the data.

Thus, businesses are vulnerable when they entrust sensitive data to third-party platforms, which often lack transparency about data usage and security. The platforms, chosen mainly for cost, efficiency, and user experience, are frequent targets for cyber criminals, hacktivists, and opportunistic lone hackers looking for sensitive data accidentally exposed due to misconfigurations or poor data management policies.

Consumers are putting pressure on businesses to improve cybersecurity when handling their personal data. Businesses who suffer a data breach face a high level of scrutiny from customers, investors, the media, and governments, even when the data breach is the result of a third party’s being hacked. For example, Uber made headlines in 2022 for a data breach which was the result of a compromised vendor who had access to data regarding Uber’s employees.

Similarly, the UK’s Ministry of Defence was the victim of a data breach earlier this year when hackers targeted a third party payroll system used by the government department.

Why do cyber-criminals target third parties?

Cyber-criminals can potentially gain access to multiple networks when targeting a third-party storage provider. A successful attack could give attackers access to the networks and systems of all its clients, amplifying the impact of a single breach.

For example, when Illuminate Education was the target of a cyber-attack, the data of 23 US School Districts was stolen via its student-tracking software. It included student data from the country's two largest school systems - New York City Public Schools and Los Angeles Unified School District.

Common third-party security risks

When collaborating with third parties, organizations should be aware of the most common types of security risks posed to their cybersecurity.

  • Software supply chain attacks: Software supply chain attacks occur when cyber criminals infiltrate and compromise software products or updates at any point in the development or distribution process. This allows attackers to insert malicious code into legitimate software, which then gets distributed to users through trusted channels.
  • Human error: Human error in cybersecurity refers to mistakes made by individuals that lead to security breaches or vulnerabilities. These errors can result from lack of awareness, insufficient training, negligence, or simple mistakes.
  • Privileged access misuse: Privileged access misuse involves the inappropriate or unauthorized use of elevated access rights by individuals within an organization. This can include intentionally malicious actions or unintentional misuse of administrative privileges.

What to look for in a security solution when using third parties to store or manage data

Understanding the security posture of a third party is important when partnering with it and entrusting it with your organization’s data. Understanding how basic cyber hygiene policies are implemented is a good place to start, such as data retention policies, use of encryption for data in storage, and how identity and access are managed.

In some circumstances, it is important to understand who is responsible for the data’s security. For example, when using public cloud infrastructure, it is generally the responsibility of the data owner to manage how the data is accessed and stored.

In that situation, an organization needs to ensure it has solutions in place which gives it full visibility of that third-party environment, and which can proactively identify misconfigurations and detect and respond to suspicious activity in real time.

Benefits of using AI tools to aid in managing sensitive data

According to research performed by IBM, organizations with extensive use of security AI and automation identified and contained a data breach 108 days faster in 2023 than organizations that did not use AI for cybersecurity. (1) This figure is only likely to improve as companies mature in their adoption of AI for cyber security and can be a key indicator in the security posture of a third-party vendor.

Example of third-party security incidents

Sumo data breach

Sumo, an Australian energy and internet provider, suffered a data breach which they became aware of on May 13th, 2024. Further investigation into the cyber incident has found that “the personal details of approximately 40,000 customers were compromised, including approximately 3,000 Australian passport numbers.” (2)

While none of Sumo’s systems were allegedly accessed or affected and the third-party application also worked as designed (3), the incident was blamed on an unnamed third party. The breach may have been the result of a misconfiguration or human error.

This incident underscores the importance of not only selecting third-party providers with robust security measures but also continuously monitoring and assessing their security practices.

How Darktrace helps monitor third-party data usage

Darktrace/Cloud uses Self-Learning AI to provide complete cyber resilience for multi-cloud environments.

Benefits of Darktrace/Cloud:

Architectural awareness: Gives users an understanding of their cloud footprint, including real-time visibility into cloud assets, architectures, users and permissions. Combines asset enumeration, modeled architectures, and flow log analysis. Cost insights give a better understanding of resource allocation, helping teams contextualize resources.

Cloud-native detection and response: AI understands ‘normal’ for your unique business and stops cyber-threats with autonomous response. Near-real-time response goes beyond simple email alerts or opening a ticket; and includes cloud-native actions like detaching EC2 instances and applying security groups to contain risky assets.

Cloud protection and compliance: Identify compliance issues and potential misconfigurations with attack path modeling and prioritized remediation steps. Darktrace’s attack surface management (ASM) adds a critical external view of your organization, highlighting vulnerabilities most impactful to your specific situation and revealing shadow IT.

Learn more about securing cloud environments by reading: The CISO’s Guide to Cloud Security here.

References

1.    https://www.ibm.com/reports/data-breach

2.    https://www.passports.gov.au/news/sumo-data-breach

3.    https://www.smh.com.au/technology/sumo-slammed-by-data-breach-as-energy-and-internet-customers-have-details-leaked-20240515-p5jdwp.html

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About the author
Oakley Cox
Analyst Technical Director, APAC
Our ai. Your data.

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