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Using Self-Learning AI to defend against zero-day and N-day attacks
Key Terms:
Zero-day | A recently discovered security vulnerability in computer software that has no currently available fix or patch. Its name come from the reality that vendors have “zero days” to act and respond.
N-day | A vulnerability that emerges in computer software in which a vendor is aware and may have already issued (or are currently working on) a patch or fix. Active exploits often already exist and await abuse by nefarious actors.
Traditional security solutions often apply signature-based-detection when identifying cyber threats, helping to defend against legacy attacks but consequently missing novel ones. Therefore, security teams often lend a lot of focus to ensuring that the risk of zero-day vulnerabilities is reduced [1]. As explored in this blog, however, organizations can face just as much of a risk from n-day attacks, since they invite the most attention from malicious actors [2]. This is due in part to the reduced complexity, cost and time invested in researching and finding new exploits compared with that found when attackers exploit zero-days.
This blog will examine both a zero-day and n-day attack that two different Darktrace customers faced in the fall of 2021. This will include the activity Darktrace detected, along with the steps taken by Darktrace/Network to intervene. It will then compare the incidents, discuss the possible dangers of third-party integrations, and assess the deprecation of legacy security tools.
Revisiting zero-day attacks
Zero-days are among the greatest concerns security teams face in the era of modern technology and networking. Defending critical systems from zero-day compromises is a task most legacy security solutions are often unable to handle. Due to the complexity of uncovering new security flaws and developing elaborate code that can exploit them, these attacks are often carried out by funded or experienced groups such as nation-state actors and APTs. One of history’s most prolific zero-days, ‘Stuxnet’, sent security teams worldwide into a global panic in 2010. This involved a widespread attack on Iranian nuclear infrastructure and was widely accepted to be a result of nation-state actors [3]. The Stuxnet worm took advantage of four zero-day exploits, compromising over 200,000 devices and physically damaging around 10% of the 9,000 critical centrifuges at the Natanz nuclear site.
More recently, 2021 saw the emergence of several critical zero-day vulnerabilities within SonicWall’s product suite [4]. SonicWall is a security hardware manufacturer that provides hardware firewall devices, unified threat management, VPN gateways and network security solutions. Some of these vulnerabilities lie within their Secure Mobile Access (SMA) 100 series (for example, CVE-2019-7481, CVE-2021-20016 and CVE-2021-20038 to name a few). These directly affected VPN devices and often allowed attackers easy remote access to company devices. CVE-2021-20016 in particular incorporates an SQL-Injection vulnerability within SonicWall’s SSL VPN SMA 100 product line [5]. If exploited, this defect would allow an unauthenticated remote attacker to perform their own malicious SQL query in order to access usernames, passwords and other session related information.
The N-day underdog
The shadow cast by zero-day attacks often shrouds that of n-day attacks. N-days, however, often pose an equal - if not greater - risk to the majority of organizations, particularly those in industrial sectors. Since these vulnerabilities have fixes available, all of the hard work around research is already done; malicious actors only need to view proof of concepts (POCs) or, if proficient in coding, reverse-engineer software to reveal code-changes (binary diffing) in order to exploit these security flaws in the wild. These vulnerabilities are typically attributed to opportunistic hackers and script-kiddies, where little research or heavy lifting is required.
August 2021 gave rise to a critical vulnerability in Atlassian Confluence servers, namely CVE-2021-26084 [6]. Confluence is a widely used collaboration wiki tool and knowledge-sharing platform. As introduced and discussed a few months ago in a previous Darktrace blog, this vulnerability allows attackers to remotely execute code on internet-facing servers after exploiting injection vulnerabilities in Object-Graph Navigation Language (OGNL). Whilst Confluence had patches and fixes available to users, attackers still jumped on this opportunity and began scanning the internet for signs of critical devices serving this outdated software [7]. Once identified, they would exploit the vulnerability, often installing crypto mining software onto the device. More recently, Darktrace explored a new vulnerability (CVE-2022-26134), disclosed midway through 2022, that affected Confluence servers and data centers using similar techniques to that found in CVE-2021-26084 [8].
SonicWall in the wild – 1. Zero-day attack
At the beginning of August 2021, Darktrace prevented an attack from taking place within a European automotive customer’s environment (Figure 1). The attack targeted a vulnerable internet-facing SonicWall VPN server, and while the attacker’s motive remains unclear, similar historic events suggest that they intended to perform ransomware encryption or data exfiltration.
Darktrace was unable to confirm the definite tactics, techniques and procedures (TTPs) used by the attacker to compromise the customer’s environment, as the device was compromised before Darktrace installation and coverage. However, from looking at recently disclosed SonicWall VPN vulnerabilities and patterns of behaviour, it is likely CVE-2021-20016 played a part. At some point after this initial infection, it is also believed the device was able to move laterally to a domain controller (DC) using administrative credentials; it was this server that then initiated the anomalous activity that Darktrace detected and alerted on.
On August 5th 2021 , Darktrace observed this compromised domain controller engaging in unusual ICMP scanning - a protocol used to discover active devices within an environment and create a map of an organization’s network topology. Shortly after, the infected server began scanning devices for open RDP ports and enumerating SMB shares using unorthodox methods. SMB delete and HTTP requests (over port 445 and 80 respectively) were made for files named delete.me in the root directory of numerous network shares using the user agent Microsoft WebDAV. However, no such files appeared to exist within the environment. This may have been the result of an attacker probing devices in the network in an effort to see their responses and gather information on properties and vulnerabilities they could later exploit.
Soon the infected DC began establishing RDP tunnels back to the VPN server and making requests to an internal DNS server for multiple endpoints relating to exploit kits, likely in an effort to strengthen the attacker’s foothold within the environment. Some of the endpoints requested relate to:
- EternalBlue vulnerability
- Petit Potam NTLM hash attack tool
- Unusual GitHub repositories
- Unusual Python repositories
The DC made outgoing NTLM requests to other internal devices, implying the successful installation of Petit Potam exploitation tools. The server then began performing NTLM reconnaissance, making over 1,000 successful logins under ‘Administrator’ to several other internal devices. Around the same time, the device was also seen making anonymous SMBv1 logins to numerous internal devices, (possibly symptomatic of the attacker probing machines for EternalBlue vulnerabilities).
Interestingly, the device also made numerous failed authentication attempts using a spoofed credential for one of the organization’s security managers. This was likely in an attempt to hide themselves using ‘Living off the Land’ (LotL) techniques. However, whilst the attacker clearly did their research on the company, they failed to acknowledge the typical naming convention used for credentials within the environment. This ultimately backfired and made the compromise more obvious and unusual.
In the morning of the following day, the initially compromised VPN server began conducting further reconnaissance, engaging in similar activity to that observed by the domain controller. Until now, the customer had set Darktrace RESPOND to run in human confirmation mode, meaning interventions were not made autonomously but required confirmation by a member of the internal security team. However, thanks to Proactive Threat Notifications (PTNs) delivered by Darktrace’s dedicated SOC team, the customer was made immediately aware of this unusual behaviour, allowing them to apply manual Darktrace RESPOND blocks to all outgoing connections (Figure 2). This gave the security team enough time to respond and remediate before serious damage could be done.
Confluence in the wild – 2. N-day attack
Towards the end of 2021, Darktrace saw a European broadcasting customer leave an Atlassian Confluence internet-facing server unpatched and vulnerable to crypto-mining malware using CVE-2021-26084. Thanks to Darktrace, this attack was entirely immobilized within only a few hours of the initial infection, protecting the organization from damage (Figure 3).
On midday on September 1st 2021, an unpatched Confluence server was seen receiving SSL connections over port 443 from a suspicious new endpoint, 178.238.226[.]127. The connections were encrypted, meaning Darktrace was unable to view the contents and ascertain what requests were being made. However, with the disclosure of CVE-2021-26084 just 7 days prior to this activity, it is likely that the TTPs used involved injecting OGNL expressions to Confluence server memory; allowing the attacker to remotely execute code on the vulnerable server.
Immediately after successful exploitation of the Confluence server, the infected device was observed making outgoing HTTP GET requests to several external endpoints using a new user agent (curl/7.61.1). Curl was used to silently download and configure multiple suspicious files relating to XMRig cryptocurrency miner, including ld.sh, XMRig and config.json. Subsequent outgoing connections were then made to europe.randomx-hub.miningpoolhub[.]com · 172.105.210[.]117 using the JSON-RPC protocol, seen alongside the mining credential maillocal.confluence (Figure 4). Only 3 seconds after initial compromise, the infected device began attempting to mine cryptocurrency using the Minergate protocol but was instantly and autonomously blocked by Darktrace RESPOND. This prevented the server from abusing system resources and generating profits for the attacker.
In the afternoon, the malware persisted with its infection. The compromised server began making successive HTTP GET requests to a new rare endpoint 195.19.192[.]28 using the same curl user agent (Figures 5 & 6). These requests were for executable and dynamic library files associated with Kinsing malware (but fortunately were also blocked by Darktrace RESPOND). Kinsing is a malware strain found in numerous attack campaigns which is often associated with crypto-jacking, and has appeared in previous Darktrace blogs [9].
The attacker then began making HTTP POST requests to an IP 185.154.53[.]140, using the same curl user agent; likely a method for the attacker to maintain persistence within the network and establish a foothold using its C2 infrastructure. The Confluence server was then again seen attempting to mine cryptocurrency using the Minergate protocol. It made outgoing JSON-RPC connections to a different new endpoint, 45.129.2[.]107, using the following mining credential: ‘42J8CF9sQoP9pMbvtcLgTxdA2KN4ZMUVWJk6HJDWzixDLmU2Ar47PUNS5XHv4Kmfdh8aA9fbZmKHwfmFo8Wup8YtS5Kdqh2’. This was once again blocked by Darktrace RESPOND (Figure 7).
The final activity seen from this device involved the download of additional shell scripts over HTTP associated with Kinsing, namely spre.sh and unk.sh, from 194.38.20[.]199 and 195.3.146[.]118 respectively (Figure 8). A new user agent (Wget/1.19.5 (linux-gnu)) was used when connecting to the latter endpoint, which also began concurrently initiating repeated connections indicative of C2 beaconing. These scripts help to spread the Kinsing malware laterally within the environment and may have been the attacker's last ditch efforts at furthering their compromise before Darktrace RESPOND blocked all connections from the infected Confluence server [11]. With Darktrace RESPOND's successful actions, the customer’s security team were then able to perform their own response and remediation.
Darktrace Coverage: N- vs Zero-days
In the SonicWall case the attacker was unable to achieve their actions on objectives (thanks to Darktrace's intervention). However, this incident displayed tactics of a more stealthy and sophisticated attacker - they had an exploited machine but waited for the right moment to execute their malicious code and initiate a full compromise. Due to the lack of visibility over attacker motive, it is difficult to deduce what type of actor led to this intrusion. However, with the disclosure of a zero-day vulnerability (CVE-2021-20016) not long before this attack, along with a seemingly dormant initially compromised device, it is highly possible that it was carried out by a sophisticated cyber criminal or gang.
On the other hand, the Confluence case engaged in a slightly more noisy approach; it dropped crypto mining malware on vulnerable devices in the hope that the target’s security team did not maintain visibility over their network or would merely turn a blind eye. The files downloaded and credentials observed alongside the mining activity heavily imply the use of Kinsing malware [11]. Since this vulnerability (CVE-2021-26084) emerged as an n-day attack with likely easily accessible POCs, as well as there being a lack of LotL techniques and the motive being long term monetary gain, it is possible this attack was conducted by a less sophisticated or amateur actor (script-kiddie); one that opportunistically exploits known vulnerabilities in internet-facing devices in order to make a quick profit [12].
Whilst Darktrace RESPOND was enabled in human confirmation mode only during the start of the SonicWall attack, Darktrace’s Cyber AI Analyst still offered invaluable insight into the unusual activity associated with the infected machines during both the Confluence and SonicWall compromises. SOC analysts were able to see these uncharacteristic behaviours and escalate the incident through Darktrace’s PTN and ATE services. Analysts then worked through these tickets with the customers, providing support and guidance and, in the SonicWall case, quickly helping to configure Darktrace RESPOND. In both scenarios, Darktrace RESPOND was able to block abnormal connections and enforce a device’s pattern of life, affording the security team enough time to isolate the infected machines and prevent further threats such as ransomware detonation or data exfiltration.
Concluding thoughts and dangers of third-party integrations
Organizations with internet-facing devices will inevitably suffer opportunistic zero-day and n-day attacks. While little can be done to remove the risk of zero-days entirely, ensuring that organizations keep their systems up to date will at the very least help prevent opportunistic and script-kiddies from exploiting n-day vulnerabilities.
However, it is often not always possible for organizations to keep their systems up to date, especially for those who require continuous availability. This may also pose issues for organizations that rely on, and put their trust in, third party integrations such as those explored in this blog (Confluence and SonicWall), as enforcing secure software is almost entirely out of their hands. Moreover, with the rising prevalence of remote working, it is essential now more than ever that organizations ensure their VPN devices are shielded from external threats, guidance on which has been released by the NSA/CISA [13].
These two case studies have shown that whilst organizations can configure their networks and firewalls to help identify known indicators of compromise (IoC), this ‘rearview mirror’ approach will not account for, or protect against, any new and undisclosed IoCs. With the aid of Self-Learning AI and anomaly detection, Darktrace can detect the slightest deviation from a device’s normal pattern of life and respond autonomously without the need for rules and signatures. This allows for the disruption and prevention of known and novel attacks before irreparable damage is caused- reassuring security teams that their digital estates are secure.
Thanks to Paul Jennings for his contributions to this blog.
Appendices: SonicWall (Zero-day)
Abweichungen von Darktrace Modellen
· AIA / Suspicious Chain of Administrative Credentials
· Anomalous Connection / Active Remote Desktop Tunnel
· Anomalous Connection / SMB Enumeration
· Anomalous Connection / Unusual Internal Remote Desktop
· Compliance / High Priority Compliance Model Breach
· Compliance / Outgoing NTLM Request from DC
· Device / Anomalous RDP Followed By Multiple Model Breaches
· Device / Anomalous SMB Followed By Multiple Model Breaches
· Device / ICMP Address Scan
· Device / Large Number of Model Breaches
· Device / Large Number of Model Breaches from Critical Network Device
· Device / Multiple Lateral Movement Model Breaches (PTN/Enhanced Monitoring model)
· Device / Network Scan
· Device / Possible SMB/NTLM Reconnaissance
· Device / RDP Scan
· Device / Reverse DNS Sweep
· Device / SMB Session Bruteforce
· Device / Suspicious Network Scan Activity (PTN/Enhanced Monitoring model)
· Unusual Activity / Possible RPC Recon Activity
Darktrace RESPOND (Antigena) actions (as displayed in example)
· Antigena / Network / Manual / Quarantine Device
MITRE ATT&CK Techniques Observed
IoCs
Appendices: Confluence (N-day)
Abweichungen von Darktrace Modellen
· Anomalous Connection / New User Agent to IP Without Hostname
· Anomalous Connection / Posting HTTP to IP Without Hostname
· Anomalous File / EXE from Rare External Location
· Anomalous File / Script from Rare Location
· Compliance / Crypto Currency Mining Activity
· Compromise / High Priority Crypto Currency Mining (PTN/Enhanced Monitoring model)
· Device / Initial Breach Chain Compromise (PTN/Enhanced Monitoring model)
· Device / Internet Facing Device with High Priority Alert
· Device / New User Agent
Darktrace RESPOND (Antigena) actions (displayed in example)
· Antigena / Network / Compliance / Antigena Crypto Currency Mining Block
· Antigena / Network / External Threat / Antigena File then New Outbound Block
· Antigena / Network / External Threat / Antigena Suspicious Activity Block
· Antigena / Network / External Threat / Antigena Suspicious File Block
· Antigena / Network / Significant Anomaly / Antigena Block Enhanced Monitoring
MITRE ATT&CK Techniques Observed
IOCs
References:
[1] https://securitybrief.asia/story/why-preventing-zero-day-attacks-is-crucial-for-businesses
[3] https://www.wired.com/2014/11/countdown-to-zero-day-stuxnet/
[4] https://cve.mitre.org/cgi-bin/cvekey.cgi?keyword=SonicWall+2021
[5] https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2021-20016
[6] https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2021-26084
[8] https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-26134
[9] https://attack.mitre.org/software/S0599/
[10] https://www.virustotal.com/gui/ip-address/195.19.192.28/detection
[11] https://sysdig.com/blog/zoom-into-kinsing-kdevtmpfsi/
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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.
Schlussfolgerung
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 indicators 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
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$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
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