Blog
Inside the SOC
PREVENT
Exploring the Cyber AI Loop as an Analyst: PREVENT/ASM & DETECT
On countless occasions, Darktrace has observed cyber-attacks disrupting business operations by using a vulnerable internet-facing asset as a starting point for infection. Finding that one entry point could be all a threat actor needs to compromise an entire organization. With the objective to prevent such vulnerabilities from being exploited, Darktrace’s latest product family includes Attack Surface Management (ASM) to continuously monitor customer attack surfaces for risks, high-impact vulnerabilities and potential external threats.
An attack surface is the sum of exposed and internet-facing assets and the associated risks a hacker can exploit to carry out a cyber-attack. PREVENT/ASM uses AI to understand what external assets belong to an organization by searching beyond known servers, networks, and IPs across public data sources.
This blog discusses how Darktrace PREVENT/ASM could combine with DETECT to find potential vulnerabilities and subsequent exploitation within network traffic. In particular, this blog will investigate the assets of a large Australian company which operates in the environmental sciences industry.
Introducing ASM
In order to understand the link between PREVENT and DETECT, the core features of ASM should first be showcased.
When facing the landing page, the UI highlights the number of registered assets identified (with zero prior deployment). The tool then organizes the information gathered online in an easily assessable manner. Analysts can see vulnerable assets according to groupings like ‘Misconfiguration’, ‘Social Media Threat’ and ‘Information Leak’ which shows the type of risk posed to said assets.
The Network tab helps analysts to filter further to take more rapid action on the most vulnerable assets and interact with them to gather more information. The image below has been filtered by assets with the ‘highest scoring’ risk.
Interacting with the showcased asset selected above allows pivoting to the following page, this provides more granular information around risk metrics and the asset itself. This includes a more detailed description of what the vulnerabilities are, as well as general information about the endpoint including its location, URL, web status and technologies used.
Filtering does not end here. Within the Insights tab, analysts can use the search bar to craft personalized queries and narrow their focus to specific types of risk such as vulnerable software, open ports, or potential cybersquatting attempts from malicious actors impersonating company brands. Likewise, filters can be made for assets that may be running software at risk from a new CVE.
For each of the entries that can be read on the left-hand side, a query that could resemble the one on the top right exists. This allows users to locate specific findings beyond those risks that are categorized as critical. These broader searches can range from viewing the inventory as a whole, to seeing exposed APIs, expiring certificates, or potential shadow IT. Queries will return a list with all the assets matching the given criteria, and users can then explore them further by viewing the asset page as seen in Figure 4.
Compromise Scenario
Now that a basic explanation of PREVENT/ASM has been given, this scenario will continue to look at the Australian customer but show how Darktrace can follow a potential compromise of an at-risk ASM asset into the network.
Having certain ports open could make it particularly easy for an attacker to access an internet-facing asset, particularly those sensitive ones such as 3389 (RDP), 445 (SMB), 135 (RPC Epmapper). Alternatively, a vulnerable program with a well-known exploitation could also aid the task for threat actors.
In this specific case, PREVENT/ASM identified multiple external assets that belonged to the customer with port 3389 open. One of these assets can be labelled as ‘Server A'. Whilst RDP connections can be protected with a password for a given user, if those were weak to bruteforce, it could be an easy task for an attacker to establish an admin session remotely to the victim machine.
N or zero-day vulnerabilities associated with the protocol could also be exploited; for example, CVE-2019-0708 exploits an RCE vulnerability in Remote Desktop where an unauthenticated attacker connects to the target system using RDP and sends specially crafted requests. This vulnerability is pre-authentication and requires no user interaction.
Certain protocols are known to be sensitive according to the control they provide on a destination machine. These are developed for administrative purposes but have the potential to ease an attacker’s job if accessible. Thanks to PREVENT/ASM, security teams can anticipate such activity by having visibility over those assets that could be vulnerable. If this RDP were successfully exploited, DETECT/Network would then highlight the unusual activity performed by the compromised device as the attacker moved through the kill chain.
There are several models within DETECT/Network which monitor for risks against internet facing assets. For example, ‘Server A’ which had an open 3389 port on ASM registered the following model breach in the network:
A model like this could highlight a misconfiguration that has caused an internal device to become unexpectedly open to the internet. It could also suggest a compromised device that has now been opened to the internet to allow further exploitation. If the result of a sudden change, such an asset would also be detected by ASM and highlighted within the ‘New Assets’ part of the Insights page. Ultimately this connection was not malicious, however it shows the ability for security teams to track between PREVENT to DETECT and verify an initial compromise.
A mock scenario can take this further. Using the continued example of an open port 3389 intrusion, new RDP cookies may be registered (perhaps even administrative). This could enable further lateral movement and eventual privilege escalation. Various DETECT models would highlight actions of this nature, two examples are below:
Alongside efforts to move laterally, Darktrace may find attempts at reconnaissance or C2 communication from compromised internet facing devices by looking at Darktrace DETECT model breaches including ‘Network Scan’, ‘SMB Scanning’ and ‘Active Directory Reconnaissance’. In this case the network also saw repeated failed internal connections followed by the ‘LDAP Brute-Force Activity model’ around the same time as the RDP activity. Had this been malicious, DETECT would then continue to provide visibility into the C2 and eventual malware deployment stages.
With the combined visibility of both tools, Darktrace users have support for greater triage across the whole kill chain. For customers also using RESPOND, actions will be taken from the DETECT alerting to subsequently block malicious activity. In doing so, inputs will have fed across the whole Cyber AI Loop by having learnt from PREVENT, DETECT and RESPOND.
This feed from the Cyber AI Loop works both ways. In Figure 9, below, a DETECT model breach shows a customer alert from an internet facing device:
This breach took place because an established server suddenly started serving HTTP sessions on a port commonly used for HTTPS (secure) connections. This could be an indicator that a criminal may have gained control of the device and set it to listen on the given port and enable direct connection to the attacker’s machine or command and control server. This device can be viewed by an analyst in its Darktrace PREVENT version, where new metrics can be observed from a perspective outside of the network.
This page reports the associated risks that could be leveraged by malicious actors. In this case, the events are not correlated, but in the event of an attack, this backwards pivoting could help to pinpoint a weak link in the chain and show what allowed the attacker into the network. In doing so this supports the remediation and recovery process. More importantly though, it allows organizations to be proactive and take appropriate security measures required before it could ever be exploited.
Concluding Thoughts
The combination of PREVENT/ASM with DETECT/Network provides wide and in-depth visibility over a company’s infrastructure. Through the Cyber AI Loop, this coverage is continually learning and updating based on inputs from both. PREVENT/ASM can show companies the potential weaknesses that a cybercriminal could take advantage of. In turn this allows them to prioritize patching, updating, and management of their internet facing assets. At the same time, Darktrace DETECT will show the anomalous behavior of any of these internet facing devices, enabling security teams or RESPOND to stop an attack. Use of these tools by an analyst together is effective in gaining informed security data which can be fed back to IT management. Leveraging this allows normal company operations to be performed without the worry of cyber disruption.
Credit to: Emma Foulger, Senior Cyber Analyst at Darktrace
Like this and want more?
More in this series
Blog
Inside the SOC
PurpleFox in a Henhouse: How Darktrace Hunted Down a Persistent and Dynamic Rootkit
Versatile Malware: PurpleFox
As organizations and security teams across the world move to bolster their digital defenses against cyber threats, threats actors, in turn, are forced to adopt more sophisticated tactics, techniques and procedures (TTPs) to circumvent them. Rather than being static and predictable, malware strains are becoming increasingly versatile and therefore elusive to traditional security tools.
One such example is PurpleFox. First observed in 2018, PurpleFox is a combined fileless rootkit and backdoor trojan known to target Windows machines. PurpleFox is known for consistently adapting its functionalities over time, utilizing different infection vectors including known vulnerabilities (CVEs), fake Telegram installers, and phishing. It is also leveraged by other campaigns to deliver ransomware tools, spyware, and cryptocurrency mining malware. It is also widely known for using Microsoft Software Installer (MSI) files masquerading as other file types.
The Evolution of PurpleFox
The Original Strain
First reported in March 2018, PurpleFox was identified to be a trojan that drops itself onto Windows machines using an MSI installation package that alters registry values to replace a legitimate Windows system file [1]. The initial stage of infection relied on the third-party toolkit RIG Exploit Kit (EK). RIG EK is hosted on compromised or malicious websites and is dropped onto the unsuspecting system when they visit browse that site. The built-in Windows installer (MSIEXEC) is leveraged to run the installation package retrieved from the website. This, in turn, drops two files into the Windows directory – namely a malicious dynamic-link library (DLL) that acts as a loader, and the payload of the malware. After infection, PurpleFox is often used to retrieve and deploy other types of malware.
Subsequent Variants
Since its initial discovery, PurpleFox has also been observed leveraging PowerShell to enable fileless infection and additional privilege escalation vulnerabilities to increase the likelihood of successful infection [2]. The PowerShell script had also been reported to be masquerading as a .jpg image file. PowerSploit modules are utilized to gain elevated privileges if the current user lacks administrator privileges. Once obtained, the script proceeds to retrieve and execute a malicious MSI package, also masquerading as an image file. As of 2020, PurpleFox no longer relied on the RIG EK for its delivery phase, instead spreading via the exploitation of the SMB protocol [3]. The malware would leverage the compromised systems as hosts for the PurpleFox payloads to facilitate its spread to other systems. This mode of infection can occur without any user action, akin to a worm.
The current iteration of PurpleFox reportedly uses brute-forcing of vulnerable services, such as SMB, to facilitate its spread over the network and escalate privileges. By scanning internet-facing Windows computers, PurpleFox exploits weak passwords for Windows user accounts through SMB, including administrative credentials to facilitate further privilege escalation.
Darktrace detection of PurpleFox
In July 2023, Darktrace observed an example of a PurpleFox infection on the network of a customer in the healthcare sector. This observation was a slightly different method of downloading the PurpleFox payload. An affected device was observed initiating a series of service control requests using DCE-RPC, instructing the device to make connections to a host of servers to download a malicious .PNG file, later confirmed to be the PurpleFox rootkit. The device was then observed carrying out worm-like activity to other external internet-facing servers, as well as scanning related subnets.
Darktrace DETECT™ was able to successfully identify and track this compromise across the cyber kill chain and ensure the customer was able to take swift remedial action to prevent the attack from escalating further.
While the customer in question did have Darktrace RESPOND™, it was configured in human confirmation mode, meaning any mitigative actions had to be manually applied by the customer’s security team. If RESPOND had been enabled in autonomous response mode at the time of the attack, it would have been able to take swift action against the compromise to contain it at the earliest instance.
Attack Overview
Initial Scanning over SMB
On July 14, 2023, Darktrace detected the affected device scanning other internal devices on the customer’s network via port 445. The numerous connections were consistent with the aforementioned worm-like activity that has been reported from PurpleFox behavior as it appears to be targeting SMB services looking for open or vulnerable channels to exploit.
This initial scanning activity was detected by Darktrace DETECT, specifically through the model breach ‘Device / Suspicious SMB Scanning Activity’. Darktrace’s Cyber AI Analyst™ then launched an autonomous investigation into these internal connections and tied them into one larger-scale network reconnaissance incident, rather than a series of isolated connections.
As Darktrace RESPOND was configured in human confirmation mode, it was unable to autonomously block these internal connections. However, it did suggest blocking connections on port 445, which could have been manually applied by the customer’s security team.
Privilege Escalation
The device successfully logged in via NTLM with the credential, ‘administrator’. Darktrace recognized that the endpoint was external to the customer’s environment, indicating that the affected device was now being used to propagate the malware to other networks. Considering the lack of observed brute-force activity up to this point, the credentials for ‘administrator’ had likely been compromised prior to Darktrace’s deployment on the network, or outside of Darktrace’s purview via a phishing attack.
Exploitation
Darktrace then detected a series of service control requests over DCE-RPC using the credential ‘admin’ to make SVCCTL Create Service W Requests. A script was then observed where the controlled device is instructed to launch mshta.exe, a Windows-native binary designed to execute Microsoft HTML Application (HTA) files. This enables the execution of arbitrary script code, VBScript in this case.
There are a few MSIEXEC flags to note:
- /i : installs or configures a product
- /Q : sets the user interface level. In this case, it is set to ‘No UI’, which is used for “quiet” execution, so no user interaction is required
Evidently, this was an attempt to evade detection by endpoint users as it is surreptitiously installed onto the system. This corresponds to the download of the rootkit that has previously been associated with PurpleFox. At this stage, the infected device continues to be leveraged as an attack device and scans SMB services over external endpoints. The device also appeared to attempt brute-forcing over NTLM using the same ‘administrator’ credential to these endpoints. This activity was identified by Darktrace DETECT which, if enabled in autonomous response mode would have instantly blocked similar outbound connections, thus preventing the spread of PurpleFox.
Installation
On August 9, Darktrace observed the device making initial attempts to download a malicious .PNG file. This was a notable change in tactics from previously reported PurpleFox campaigns which had been observed utilizing .MOE files for their payloads [3]. The .MOE payloads are binary files that are more easily detected and blocked by traditional signatured-based security measures as they are not associated with known software. The ubiquity of .PNG files, especially on the web, make identifying and blacklisting the files significantly more difficult.
The first connection was made with the URI ‘/test.png’. It was noted that the HTTP method here was HEAD, a method similar to GET requests except the server must not return a message-body in the response.
The metainformation contained in the HTTP headers in response to a HEAD request should be identical to the information sent in response to a GET request. This method is often used to test hypertext links for validity and recent modification. This is likely a way of checking if the server hosting the payload is still active. Avoiding connections that could possibly be detected by antivirus solutions can help keep this activity under-the-radar.
The server responds with a status code of 200 before the download begins. The HEAD request could be part of the attacker’s verification that the server is still running, and that the payload is available for download. The ‘/test.png’ HEAD request was sent twice, likely for double confirmation to begin the file transfer.
Subsequent analysis using a Packet Capture (PCAP) tool revealed that this connection used the Windows Installer user agent that has previously been associated with PurpleFox. The device then began to download a payload that was masquerading as a Microsoft Word document. The device was thus able to download the payload twice, from two separate endpoints.
By masquerading as a Microsoft Word file, the threat actor was likely attempting to evade the detection of the endpoint user and traditional security tools by passing off as an innocuous text document. Likewise, using a Windows Installer user agent would enable threat actors to bypass antivirus measures and disguise the malicious installation as legitimate download activity.
Darktrace DETECT identified that these were masqueraded file downloads by correctly identifying the mismatch between the file extension and the true file type. Subsequently, AI Analyst was able to correctly identify the file type and deduced that this download was indicative of the device having been compromised.
In this case, the device attempted to download the payload from several different endpoints, many of which had low antivirus detection rates or open-source intelligence (OSINT) flags, highlighting the need to move beyond traditional signature-base detections.
If Darktrace RESPOND was enabled in autonomous response mode at the time of the attack it would have acted by blocking connections to these suspicious endpoints, thus preventing the download of malicious files. However, as RESPOND was in human confirmation mode, RESPOND actions required manual application by the customer’s security team which unfortunately did not happen, as such the device was able to download the payloads.
Conclusion
The PurpleFox malware is a particularly dynamic strain known to continually evolve over time, utilizing a blend of old and new approaches to achieve its goals which is likely to muddy expectations on its behavior. By frequently employing new methods of attack, malicious actors are able to bypass traditional security tools that rely on signature-based detections and static lists of indictors of compromise (IoCs), necessitating a more sophisticated approach to threat detection.
Darktrace DETECT’s Self-Learning AI enables it to confront adaptable and elusive threats like PurpleFox. By learning and understanding customer networks, it is able to discern normal network behavior and patterns of life, distinguishing expected activity from potential deviations. This anomaly-based approach to threat detection allows Darktrace to detect cyber threats as soon as they emerge.
By combining DETECT with the autonomous response capabilities of RESPOND, Darktrace customers are able to effectively safeguard their digital environments and ensure that emerging threats can be identified and shut down at the earliest stage of the kill chain, regardless of the tactics employed by would-be attackers.
Credit to Piramol Krishnan, Cyber Analyst, Qing Hong Kwa, Senior Cyber Analyst & Deputy Team Lead, Singapore
Appendices
Darktrace Model Detections
- Device / Increased External Connectivity
- Device / Large Number of Connections to New Endpoints
- Device / SMB Session Brute Force (Admin)
- Compliance / External Windows Communications
- Anomalous Connection / New or Uncommon Service Control
- Compromise / Unusual SVCCTL Activity
- Compromise / Rare Domain Pointing to Internal IP
- Anomalous File / Masqueraded File Transfer
RESPOND Models
- Antigena / Network / Significant Anomaly / Antigena Breaches Over Time Block
- Antigena / Network / External Threat / Antigena Suspicious Activity Block
- Antigena / Network / Significant Anomaly / Antigena Significant Anomaly from Client Block
- Antigena / Network / Significant Anomaly / Antigena Enhanced Monitoring from Client Block
- Antigena / Network / External Threat / Antigena Suspicious File Block
- Antigena / Network / External Threat / Antigena File then New Outbound Block
List of IoCs
IoC - Type - Description
/C558B828.Png - URI - URI for Purple Fox Rootkit [4]
5b1de649f2bc4eb08f1d83f7ea052de5b8fe141f - File Hash - SHA1 hash of C558B828.Png file (Malware payload)
190.4.210[.]242 - IP - Purple Fox C2 Servers
218.4.170[.]236 - IP - IP for download of .PNG file (Malware payload)
180.169.1[.]220 - IP - IP for download of .PNG file (Malware payload)
103.94.108[.]114:10837 - IP - IP from Service Control MSIEXEC script to download PNG file (Malware payload)
221.199.171[.]174:16543 - IP - IP from Service Control MSIEXEC script to download PNG file (Malware payload)
61.222.155[.]49:14098 - IP - IP from Service Control MSIEXEC script to download PNG file (Malware payload)
178.128.103[.]246:17880 - IP - IP from Service Control MSIEXEC script to download PNG file (Malware payload)
222.134.99[.]132:12539 - IP - IP from Service Control MSIEXEC script to download PNG file (Malware payload)
164.90.152[.]252:18075 - IP - IP from Service Control MSIEXEC script to download PNG file (Malware payload)
198.199.80[.]121:11490 - IP - IP from Service Control MSIEXEC script to download PNG file (Malware payload)
MITRE ATT&CK Mapping
Tactic - Technique
Reconnaissance - Active Scanning T1595, Active Scanning: Scanning IP Blocks T1595.001, Active Scanning: Vulnerability Scanning T1595.002
Resource Development - Obtain Capabilities: Malware T1588.001
Initial Access, Defense Evasion, Persistence, Privilege Escalation - Valid Accounts: Default Accounts T1078.001
Initial Access - Drive-by Compromise T1189
Defense Evasion - Masquerading T1036
Credential Access - Brute Force T1110
Discovery - Network Service Discovery T1046
Command and Control - Proxy: External Proxy T1090.002
References
- https://blog.360totalsecurity.com/en/purple-fox-trojan-burst-out-globally-and-infected-more-than-30000-users/
- https://www.trendmicro.com/en_us/research/19/i/purple-fox-fileless-malware-with-rookit-component-delivered-by-rig-exploit-kit-now-abuses-powershell.html
- https://www.akamai.com/blog/security/purple-fox-rootkit-now-propagates-as-a-worm
- https://www.foregenix.com/blog/an-overview-on-purple-fox
- https://www.trendmicro.com/en_sg/research/21/j/purplefox-adds-new-backdoor-that-uses-websockets.html
Blog
OT
$70 Million in Cyber Security Funding for Electric Cooperatives & Utilities
What is the Bipartisan Infrastructure Deal?
The Bipartisan Infrastructure Law passed by congress in 2021 aimed to upgrade power and infrastructure to deliver clean, reliable energy across the US to achieve zero-emissions. To date, the largest investment in clean energy, the deal will fund new programs to support the development and deployment of clean energy technology.
Why is it relevant to electric municipalities?
Section 40124 of the Bipartisan Infrastructure Law allocates $250 million over a 5-year period to create the Rural and Municipal Utility Cybersecurity (RMUC) Program to help electric cooperative, municipal, and small investor-owned utilities protect against, detect, respond to, and recover from cybersecurity threats.1 This act illuminates the value behind a full life-cycle approach to cyber security. Thus, finding a cyber security solution that can provide all aspects of security in one integrated platform would enhance the overall security posture and ease many of the challenges that arise with adopting multiple point solutions.
On November 16, 2023 the Office of Cybersecurity, Energy Security, and Emergency Response (CESER) released the Advanced Cybersecurity Technology (ACT) for electric utilities offering a $70 million funding opportunity that aims to enhance the cybersecurity posture of electric cooperative, municipal, and small investor-owned utilities.
Funding Details
10 projects will be funded with application submissions due November 29, 2023, 5:00 pm ET with $200,000 each in cash prizes in the following areas:
- Direct support for eligible utilities to make investments in cybersecurity technologies, tools, training, and improvements in utility processes and procedures;
- Funding to strengthen the peer-to-peer and not-for-profit cybersecurity technical assistance ecosystem currently serving eligible electric utilities; and
- Increasing access to cybersecurity technical assistance and training for eligible utilities with limited cybersecurity resources. 2
To submit for this award visit: https://www.herox.com/ACT1Prize
How can electric municipalities utilize the funding?
While the adoption of hybrid working patterns increase cloud and SaaS usage, the number of industrial IoT devices also continues to rise. The result is decrease in visibility for security teams and new entry points for attackers. Particularly for energy and utility organizations.
Electric cooperatives seeking to enhance their cyber security posture can aim to invest in cyber security tools that provide the following:
Compliance support: Consider finding an OT security solution that maps out how its solutions and features help your organization comply with relevant compliance mandates such as NIST, ISA, FERC, TSA, HIPAA, CIS Controls, and more.
Anomaly based detection: Siloed security solutions also fail to detect attacks that span
the entire organization. Anomaly-based detection enhances an organization’s cyber security posture by proactively defending against potential attacks and maintaining a comprehensive view of their attack surface.
Integration capabilities: Implementation of several point solutions that complete individual tasks runs the risk of increasing workloads for operators and creates additional challenges with compliance, budgeting, and technical support. Look for cyber security tools that integrate with your existing technologies.
Passive and active asset tracking: Active Identification offers accurate enumeration, real time updates, vulnerability assessment, asset validation while Passive Identification eliminates the risk of operational disruption, minimizes risk, does not generate additional network traffic. It would be ideal to find a security solution that can do both.
Can secure both IT and OT in unison: Given that most OT cyber-attacks actually start in IT networks before pivoting into OT, a mature security posture for critical infrastructure would include a single solution for both IT and OT. Separate solutions for IT and OT present challenges when defending network boundaries and detecting incidents when an attacker pivots from IT to OT. These independent solutions also significantly increase operator workload and materially diminish risk mitigation efforts.
Darktrace/OT for Electric Cooperatives and Utilities
For smaller teams with just one or two dedicated employees, Darktrace’s Cyber AI Analyst and Investigation features allow end users to spend less time in the platform as it compiles critical incidents into comprehensive actionable event reports. AI Analyst brings all the information into a centralized view with incident reporting in natural language summaries and can be generated for compliance reports specific to regulatory requirements.
For larger teams, Darktrace alerts can be forwarded to 3rd party platforms such as a SIEM, where security team decision making is augmented. Additionally, executive reports and autonomous response reduce the alert fatigue generally associated with legacy tools. Most importantly, Darktrace’s unique understanding of normal allows security teams to detect zero-days and signatureless attacks regardless of the size of the organization and how alerts are consumed.
Key Benefits of Darktrace/OT
- Anomaly-based detection and real-time response
- Secures IT, OT, and IoT in unison
- Active and Passive Asset Identification
- Automated security reporting
- Attack surface management and vulnerability assessment
- Covers all levels of the Purdue Model
.png)
References
