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Comment sécuriser les systèmes de contrôle industriel dans le cloud

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13
Oct 2020
13
Oct 2020
With a major water utilities firm in the UK recently moving their SCADA systems to the cloud, this blog explores what ‘ICSaaS’ would look like in practice, and the security implications of such a transformation.

Transitions of OT to managed cloud services

Last month, a major water utilities firm in the UK revealed plans to move a significant part of their SCADA system to the cloud. This is one of the most high-profile transitions of OT to managed cloud services to date.

Though moving Industrial Control Systems (ICS) to the cloud has been theoretically possible for at least 10 years, the associated risks have meant that uptake has been slow. Operational technology is often bespoke and has traditionally been isolated from the Internet, and so moving OT systems to the cloud can impact reliability, performance, and security. Industrial Control Systems are high-stake environments: the slightest period of downtime can have significant ramifications for the safety of workers and the business as a whole.

These considerations have traditionally led most organizations to conclude that the benefits of moving ICS to the cloud — namely, making it cheaper and easier to manage, and improving its availability — are outweighed by the risks. Even though workers may be able to remotely control equipment on the factory floor, for example, the threat of those with malicious intent gaining access to the same protocols is a strong deterrent for organizations to hold back on digital transformation in this area.

However, the conditions brought about by the pandemic this year have brought unique challenges to the management of SCADA systems on site, causing organizations to consider secure ways to slowly transition these environments to the cloud.

But as OT converges with IT in the cloud, so too do their respective risks. Only complete and unified visibility across both IT and OT will allow companies to accelerate their digital transformation whilst at the same time managing the associated risks of digitization and of their increasingly dynamic workforces.

Figure 1: Darktrace provides a unified view of IT/OT.

ICSaaS

What will this ICS cloud infrastructure look like in practice? ICS applications, services and databases, such as the Historian, would be hosted in the cloud, with PLCs feeding data directly to the cloud. With this underway, workstations can access the ICS data remotely. The attack surface of SaaS for ICS — or ‘ICSaaS’ — would end up looking more similar to common SaaS networks than to a traditional SCADA/ICS network.

Simply put, moving industrial systems to the cloud renders traditional security concepts obsolete. The network segmentation and hierarchy recommended by the Purdue model, for instance, will become less relevant as more high-stake environments embrace digital transformation.

Figure 2: A schematic of ICSaaS cloud infrastructure

Security concerns with ICS & Cloud

The usual security concerns associated with SaaS carry over to ICS environments as they converge with the cloud. With ICSaaS, the data involved in industrial processes can be accessed from anywhere, raising questions about data security, as well as compliance and regulation.

Further, with ICSaaS, there is a loss of visibility and control over network. Not only does the workforce become increasingly dynamic, no longer bound to the HQ, but organizations also depend on a wider range of technologies on a daily basis – which means more work for security teams trying to keep up with these variables. These factors increase risk from insider threat, as well of a host of other attack vectors that emerge when industrial operations are being handled by workers who are not physically present in the on-prem workspaces.

As industrial workers begin to carry out operations in the cloud, siloed and static security controls will succumb to the same pitfalls as they have in today’s dynamic workforce: their hard-coded, pre-defined rules and signatures are not designed to adapt with sudden transformation, and so they will be forced into either default ‘inclusion listing’, or will produce unworkable numbers of ‘false positives’, impacting operations.

ICS security teams require a fundamentally different approach. Hundreds of organizations in the industrial space are turning to self-learning, AI-powered technology that continuously adapts and learns patterns of behavior across the digital ecosystem – from ICS to the cloud and beyond – in order to distinguish ‘strange but benign’ behavior as well as ‘strange but threatening’ activity indicative of a cyber-threat.

Technology and protocol agnostic, Darktrace/OT is uniquely positioned to meet the challenge of securing ICS in the cloud. The AI technology learns on the job, understanding ‘normal’ for every user, device and controller. This enables it to detect anomalies that signal an intrusion. Darktrace’s Cyber AI Analyst will then automatically launch an investigation and produce a natural-language summary of the security incident ready for IT security teams or ICS engineers to action.

Figure 3: Possible threats to an ICSaaS cloud infrastructure

ICSaaS and artificial intelligence

As ICSaaS comes of age, attackers will exploit never-before-seen attack vectors. The combined challenges of cloud security and ICS security — loss of visibility, communication barriers, varying technical knowledge, differing capabilities, misaligned objectives — make securing ICSaaS cloud infrastructure a considerable challenge.

Attacks seen in the wild recently, such as the EKANS ransomware, have managed to breach the IT and OT divide. These blind spots, however, can be illuminated by a unified platform approach to securing industrial and IT systems. Monitoring activity across the entire digital estate allows a single system to recognize when malicious activity in one area might become a precursor to compromise in another, more critical, area.

By moving away from rules and signatures of pre-defined threats and learning digital ‘patterns of life’ across the organization, Darktrace’s AI represents a step-change in cyber security. Introducing self-learning AI systems into the security infrastructure allows for real-time detection and investigation into threats across the entire digital estate. This capability will enable more archaic OT systems to go through digital transformation whilst managing the risks brought about by ICSaaS.

Credit to: Darktrace analyst Oakley Cox for his insights on the above investigation.

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The Implications of NIS2 on Cyber Security and AI

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05
Dec 2023

The NIS2 Directive requires member states to adopt laws that will improve the cyber resilience of organizations within the EU. It impacts organizations that are “operators of essential services”. Under NIS 1, EU member states could choose what this meant. In an effort to ensure more consistent application, NIS2 has set out its own definition. It eliminates the distinction between operators of essential services and digital service providers from NIS1, instead defining a new list of sectors:

  • Energy (electricity, district heating and cooling, gas, oil, hydrogen)
  • Transport (air, rail, water, road)
  • Banking (credit institutions)
  • Financial market infrastructures
  • Health (healthcare providers and pharma companies)
  • Drinking water (suppliers and distributors)
  • Digital infrastructure (DNS, TLD registries, telcos, data center providers, etc.)
  • ICT service providers (B2B): MSSPs and managed service providers
  • Public administration (central and regional government institutions, as defined per member state)
  • Space
  • Postal and courier services
  • Waste management
  • Chemicals
  • Food
  • Manufacturing of medical devices
  • Computers and electronics
  • Machinery and equipment
  • Motor vehicles, trailers and semi-trailers and other transport equipment
  • Digital providers (online market places, online search engines, and social networking service platforms) and research organizations.

With these updates, it becomes harder to try and find industry segments not included within the scope. NIS2 represents legally binding cyber security requirements for a significant region and economy. Standout features that have garnered the most attention include the tight timelines associated with notification requirements. Under NIS 2, in-scope entities must submit an initial report or “early warning” to the competent national authority or computer security incident response team (CSIRT) within 24 hours from when the entity became aware of a significant incident. This is a new development from the first iteration of the Directive, which used more vague language of the need to notify authorities “without undue delay”.

Another aspect gaining attention is oversight and regulation – regulators are going to be empowered with significant investigation and supervision powers including on-site inspections. We cover more on this in our white paper.

The stakes are now higher, with the prospect of fines that are capped at €10 million or 2% of an offending organization’s annual worldwide turnover – whichever is greater. Added to that, the NIS2 Directive includes an explicit obligation to hold members of management bodies personally responsible for breaches of their duties to ensure compliance with NIS2 obligations – and members can be held personally liable.  

The risk management measures introduced in the Directive are not altogether surprising – they reflect common best practices. Many organizations (especially those that are newly in scope for NIS2) may have to expand their cyber security capabilities, but there’s nothing controversial or alarming in the required measures.  For organizations in this situation, there are various tools, best practices, and frameworks they can leverage.  Darktrace in particular provides capabilities in the areas of visibility, incident handling, and reporting that can help.

NIS2 and Cyber AI

The use of AI is not an outright requirement within NIS2 – which may be down to lack of knowledge and expertise in the area, and/or the immaturity of the sector. The clue to this might be in the timing: the provisional agreement on the NIS2 text was reached in May 2022 – six months before ChatGPT and other open-source Generative AI tools propelled broader AI technology into the forefront of public consciousness. If the language were drafted today, it's not far-fetched to imagine AI being mentioned much more prominently and perhaps even becoming a requirement.

NIS2 does, however, very clearly recommend that “member states should encourage the use of any innovative technology, including artificial intelligence”[1].  Another section speaks directly to essential and important entities, saying that they should “evaluate their own cyber security capabilities, and where appropriate, pursue the integration of cyber security enhancing technologies, such as artificial intelligence or machine learning systems…”[2]

One of the recitals states that “member states should adopt policies on the promotion of active cyber protection”.  Where active cyber protection is defined as “the prevention, detection, monitoring, analysis and mitigation of network security breaches in an active manner.”[3]  

From a Darktrace perspective, our self-learning Cyber AI technology is precisely what enables our technology to deliver active cyber protection – protecting organizations and uplifting security teams at every stage of an incident lifecycle – from proactively hardening defenses before an attack is launched, to real-time threat detection and response, through to recovering quickly back to a state of good health.  

The visibility provided by Darktrace is vital to understanding the effectiveness of policies and ensuring policy compliance. NIS2 also covers incident handling and business continuity, which Darktrace HEAL addresses through AI-enabled incident response, readiness reports, simulations, and secure collaborations.

Reporting is integral to NIS2 and organizations can leverage Darktrace’s incident reporting features to present the necessary technical details of an incident and provide a jump start to compiling a full report with business context and impact.  

What’s Next for NIS2

We don’t yet know the details for how EU member states will transpose NIS2 into national law – they have until 17th October 2024 to work this out. The Commission also commits to reviewing the functioning of the Directive every three years. Given how much our overall understanding and appreciation for not only the dangers of AI but also its power (perhaps even necessity in the realm of cyber security) is changing, we may see many member states will leverage the recitals’ references to AI in order to make a strong push if not a requirement that essential and important organizations within their jurisdiction leverage AI.

Organizations are starting to prepare now to meet the forthcoming legislation related to NIS2. To see how Darktrace can help, talk to your representative or contact us.


[1] (51) on page 11
[2]
(89) on page 17
[3]
(57) on page 12

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About the author
John Allen
VP, Cyber Risk & Compliance

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PurpleFox in a Henhouse: How Darktrace Hunted Down a Persistent and Dynamic Rootkit

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27
Nov 2023

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

Figure 1: Timeline of PurpleFox malware kill chain.

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.

Figure 2: Cyber AI Analyst technical details summarizing the initial scanning activity seen with the internal network scan over port 445.

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.

Figure 3: The affected device’s Model Breach Event Log showing the initial scanning activity observed by Darktrace DETECT and the corresponding suggested RESPOND action.

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.

Figure 4: PurpleFox remote service control activity captured by a Darktrace DETECT model breach.
Figure 5: The infected device’s Model Breach Event Log showing the anomalous service control activity being picked up by DETECT.

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.

Figure 6: The infected device’s Model Breach Event Log showing the outbound activity corresponding to PurpleFox’s wormlike spread. This was caught by DETECT and the corresponding suggested RESPOND action.

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.

Figure 7: Packet Capture from an affected customer device showing the initial HTTP requests to the payload server.
Figure 8: Packet Capture showing the HTTP requests to download the payloads.

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.

Figure 9: PCAP from the affected customer device showing the Windows Installer user-agent associated with the .PNG file download.

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.

Figure 10: Cyber AI Analyst technical details summarizing the downloads of the PurpleFox payload.
Figure 11 (a): The Model Breach generated by the masqueraded file transfer associated with the PurpleFox payload.
Figure 11 (b): The Model Breach generated by the masqueraded file transfer associated with the PurpleFox payload.

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 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

  1. https://blog.360totalsecurity.com/en/purple-fox-trojan-burst-out-globally-and-infected-more-than-30000-users/
  2. 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
  3. https://www.akamai.com/blog/security/purple-fox-rootkit-now-propagates-as-a-worm
  4. https://www.foregenix.com/blog/an-overview-on-purple-fox
  5. https://www.trendmicro.com/en_sg/research/21/j/purplefox-adds-new-backdoor-that-uses-websockets.html
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About the author
Piramol Krishnan
Cyber Security Analyst

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