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Ransomware

Ransomware Groups Aim for Maximum Disruption

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06
Feb 2022
06
Feb 2022
Discover key ransomware trends and effective strategies to safeguard your organization. Marcus Fowler provides insights on combating cyber threats!

In parallel to the global COVID-19 pandemic, there has been a growing ransomware pandemic. Darktrace researchers discovered that ransomware attacks on US organizations tripled in 2021 compared to 2020, and attacks on UK organizations doubled.

This crisis brought 30 nations together to discuss a counter-ransomware initiative focused on cryptocurrency regulation, security resilience, attack disruption, and international cyber diplomacy. Despite these landmark policies and law enforcement efforts, it’s safe to say that ransomware will remain as a top priority threat and is not going anywhere.

As ransomware permeates, cyber-attackers will continue evolving techniques in 2022

Ransomware gangs are becoming more sophisticated in how they select targets and how they carry out attacks. Many organizations think that ransomware shouldn’t be a serious concern if they have backups in place because they can quickly bring business operations back online. But modern attacks are about more than encryption or data exfiltration; they focus on maximizing disruption to business operations, including targeting backups for encryption and deletion. In 2022, we could see ransomware gangs target cloud service providers as well as backup and archiving providers.

Critical infrastructure organizations and businesses will continue to assess how quickly they can restore operations in the aftermath of an attack and how extensively they will be able to rely on, and the costs required for cyber insurers to cover entire ransom payments and costly systems repairs.

In early January, Microsoft researchers found evidence of malware targeting multiple Ukrainian organizations deploying what appeared to be ransomware but was actually a wiper. The malware displays a ransom note then executes the wiper when the target device is powered down. If adopted by other non-state actors, this evolution goes beyond ransomware, and some organizations won’t be able to survive these types of attacks.

Sophisticated ransomware gangs will expand their detailed targeting efforts from only ‘big game hunting,’ where they target large and well-known targets, to use more resources directly targeting midsize and smaller organizations. With increased scalability through automation and leveraging supply chain attacks, ransomware gangs will have the resources to expand their operations. Large organizations have more substantial budgets and more people, and they can prioritize resources to deal with ransomware’s effects — it will be far more difficult for small businesses.

Not only are ransomware operators expanding whom they can target, but the group of cyber-attackers able to execute attacks is expanding. The rise of Ransomware-as-a-Service (RaaS) gives low-skilled threat actors access to sophisticated malware strains, lowering the barrier to entry for attackers. RaaS has expanded the criminal ecosystem to include lower-level threat actors who find and attack the targets before installing the malicious software. Threat actors are increasingly using bots to automate the initial attack that gets them a foothold in the system.

There is also a varying degree of professionalism amongst cyber-criminals, from seasoned veterans (with current or previous nation-state experience) to ‘script kiddies’ with little expertise. This array translates to greater potential for untested or reckless use of sophisticated tools by unsophisticated actors.

Ransomware groups will bounce back

Ransomware groups are resilient. Even if government pressures force ransomware groups to disband or criminally charge them, they will continue to rebrand and crop back up. For example, DarkSide, confirmed by the FBI to be behind the attack on Colonial Pipeline, shut down a week after the attack. Shortly after, BlackMatter emerged, widely believed to be a rebranded version of the same cyber-crime group.

Figure 1: Darktrace breaks down the stages of a BlackMatter ransomware attack targeting a marketing firm in the US

Earlier this year, Russia’s security agency announced that it had arrested several members belonging to the notorious REvil ransomware gang and neutralized its operations. While this is a significant step against a major group, it is unlikely to reflect a long-term change in Russian policy towards cyber-criminal gangs. These arrests almost certainly do not mark the end of REvil.

Five ransomware groups have formed a cartel to exchange data and ‘best’ practices. These groups include Wizard Spider (linked to the Ryuk and Conti ransomware strains), Twisted Spider (which developed Maze and uses Egregor), Viking Spider (the group behind Ragnar), and LockBit.

Even if government pressures force ransomware groups to disband or criminally charge ransomware gangs, these groups will continue to rebrand and crop back up with even more sophisticated techniques and capabilities.

A static ‘hardened’ perimeter defense isn’t the answer – a dynamic self-defending one is

For organizations to build systems to withstand cyber-attacks, security leaders need to think and, more importantly, defend beyond the initial breach to maximize continuity of business operations. Security defenses like firewalls centered on defending the cyber perimeter are not enough to protect against evolving threats.

A truly dynamic defense is achievable. Organizations need to actively enforce ‘normal’ for businesses and disrupt attacks at the earliest indicators of malicious anomalous behavior, such as file encryption or data exfiltration. Security technology needs to learn, make micro-decisions, and take proportional responses to detect and stop attacks early enough before data exfiltration or encryption occurs.

Attackers are acutely aware of Threat Intelligence-reliant defensive tools they need to evade and know the limitations of the legacy, siloed approach many organizations employ. Attackers are finding valuable information, exfiltrating the files, and encrypting the data in a short period. The race condition and response window for defenders to detect and stop attacks is getting smaller; security teams and solution responses must get faster.

Cyber security is no longer a human-scale problem. Organizations need to adopt AI-based protections that can defend against increasingly automated ransomware attacks. In an era of fast-moving cyber-attacks, and with threat actors deliberately striking when security teams are out of the office, AI technologies have become essential in taking targeted action to contain attacks without interrupting normal business.

INSIDE THE SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
AUTHOR
ABOUT ThE AUTHOR
Marcus Fowler
SVP, Strategic Engagements and Threats

As SVP of Strategic Engagements and Threats, Marcus works closely with senior security leaders across industries on cyber security strategy and business resilience, including across Darktrace’s Federal Division. Marcus focuses his research and analysis around emerging and next generation cyber threats, trends, and conflicts. Prior to joining Darktrace in 2019, Marcus spent 15 years at the Central Intelligence Agency developing global cyber operations and technical strategies. He has led cyber efforts with various US Intelligence Community elements and global partners. Prior to serving at the CIA, Marcus was an officer in the United States Marine Corps. Marcus has an engineering degree from the United States Naval Academy and a Masters’ Degree in International Security Studies from The Fletcher School. He also completed Harvard Business School’s Executive Education Advanced Management Program.

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Lost in Translation: Darktrace Blocks Non-English Phishing Campaign Concealing Hidden Payloads

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15
May 2024

Email – the vector of choice for threat actors

In times of unprecedented globalization and internationalization, the enormous number of emails sent and received by organizations every day has opened the door for threat actors looking to gain unauthorized access to target networks.

Now, increasingly global organizations not only need to safeguard their email environments against phishing campaigns targeting their employees in their own language, but they also need to be able to detect malicious emails sent in foreign languages too [1].

Why are non-English language phishing emails more popular?

Many traditional email security vendors rely on pre-trained English language models which, while function adequately against malicious emails composed in English, would struggle in the face of emails composed in other languages. It should, therefore, come as no surprise that this limitation is becoming increasingly taken advantage of by attackers.  

Darktrace/Email™, on the other hand, focuses on behavioral analysis and its Self-Learning AI understands what is considered ‘normal’ for every user within an organization’s email environment, bypassing any limitations that would come from relying on language-trained models [1].

In March 2024, Darktrace observed anomalous emails on a customer’s network that were sent from email addresses belonging to an international fast-food chain. Despite this seeming legitimacy, Darktrace promptly identified them as phishing emails that contained malicious payloads, preventing a potentially disruptive network compromise.

Attack Overview and Darktrace Coverage

On March 3, 2024, Darktrace observed one of the customer’s employees receiving an email which would turn out to be the first of more than 50 malicious emails sent by attackers over the course of three days.

The Sender

Darktrace/Email immediately understood that the sender never had any previous correspondence with the organization or its employees, and therefore treated the emails with caution from the onset. Not only was Darktrace able to detect this new sender, but it also identified that the emails had been sent from a domain located in China and contained an attachment with a Chinese file name.

The phishing emails detected by Darktrace sent from a domain in China and containing an attachment with a Chinese file name.
Figure 1: The phishing emails detected by Darktrace sent from a domain in China and containing an attachment with a Chinese file name.

Darktrace further detected that the phishing emails had been sent in a synchronized fashion between March 3 and March 5. Eight unique senders were observed sending a total of 55 emails to 55 separate recipients within the customer’s email environment. The format of the addresses used to send these suspicious emails was “12345@fastflavor-shack[.]cn”*. The domain “fastflavor-shack[.]cn” is the legitimate domain of the Chinese division of an international fast-food company, and the numerical username contained five numbers, with the final three digits changing which likely represented different stores.

*(To maintain anonymity, the pseudonym “Fast Flavor Shack” and its fictitious domain, “fastflavor-shack[.]cn”, have been used in this blog to represent the actual fast-food company and the domains identified by Darktrace throughout this incident.)

The use of legitimate domains for malicious activities become commonplace in recent years, with attackers attempting to leverage the trust endpoint users have for reputable organizations or services, in order to achieve their nefarious goals. One similar example was observed when Darktrace detected an attacker attempting to carry out a phishing attack using the cloud storage service Dropbox.

As these emails were sent from a legitimate domain associated with a trusted organization and seemed to be coming from the correct connection source, they were verified by Sender Policy Framework (SPF) and were able to evade the customer’s native email security measures. Darktrace/Email; however, recognized that these emails were actually sent from a user located in Singapore, not China.

Darktrace/Email identified that the email had been sent by a user who had logged in from Singapore, despite the connection source being in China.
Figure 2: Darktrace/Email identified that the email had been sent by a user who had logged in from Singapore, despite the connection source being in China.

The Emails

Darktrace/Email autonomously analyzed the suspicious emails and identified that they were likely phishing emails containing a malicious multistage payload.

Darktrace/Email identifying the presence of a malicious phishing link and a multistage payload.
Figure 3: Darktrace/Email identifying the presence of a malicious phishing link and a multistage payload.

There has been a significant increase in multistage payload attacks in recent years, whereby a malicious email attempts to elicit recipients to follow a series of steps, such as clicking a link or scanning a QR code, before delivering a malicious payload or attempting to harvest credentials [2].

In this case, the malicious actor had embedded a suspicious link into a QR code inside a Microsoft Word document which was then attached to the email in order to direct targets to a malicious domain. While this attempt to utilize a malicious QR code may have bypassed traditional email security tools that do not scan for QR codes, Darktrace was able to identify the presence of the QR code and scan its destination, revealing it to be a suspicious domain that had never previously been seen on the network, “sssafjeuihiolsw[.]bond”.

Suspicious link embedded in QR Code, which was detected and extracted by Darktrace.
Figure 4: Suspicious link embedded in QR Code, which was detected and extracted by Darktrace.

At the time of the attack, there was no open-source intelligence (OSINT) on the domain in question as it had only been registered earlier the same day. This is significant as newly registered domains are typically much more likely to bypass gateways until traditional security tools have enough intelligence to determine that these domains are malicious, by which point a malicious actor may likely have already gained access to internal systems [4]. Despite this, Darktrace’s Self-Learning AI enabled it to recognize the activity surrounding these unusual emails as suspicious and indicative of a malicious phishing campaign, without needing to rely on existing threat intelligence.

The most commonly used sender name line for the observed phishing emails was “财务部”, meaning “finance department”, and Darktrace observed subject lines including “The document has been delivered”, “Income Tax Return Notice” and “The file has been released”, all written in Chinese.  The emails also contained an attachment named “通知文件.docx” (“Notification document”), further indicating that they had been crafted to pass for emails related to financial transaction documents.

 Darktrace/Email took autonomous mitigative action against the suspicious emails by holding the message from recipient inboxes.
Figure 5: Darktrace/Email took autonomous mitigative action against the suspicious emails by holding the message from recipient inboxes.

Conclusion

Although this phishing attack was ultimately thwarted by Darktrace/Email, it serves to demonstrate the potential risks of relying on solely language-trained models to detect suspicious email activity. Darktrace’s behavioral and contextual learning-based detection ensures that any deviations in expected email activity, be that a new sender, unusual locations or unexpected attachments or link, are promptly identified and actioned to disrupt the attacks at the earliest opportunity.

In this example, attackers attempted to use non-English language phishing emails containing a multistage payload hidden behind a QR code. As traditional email security measures typically rely on pre-trained language models or the signature-based detection of blacklisted senders or known malicious endpoints, this multistage approach would likely bypass native protection.  

Darktrace/Email, meanwhile, is able to autonomously scan attachments and detect QR codes within them, whilst also identifying the embedded links. This ensured that the customer’s email environment was protected against this phishing threat, preventing potential financial and reputation damage.

Credit to: Rajendra Rushanth, Cyber Analyst, Steven Haworth, Head of Threat Modelling, Email

Appendices  

List of Indicators of Compromise (IoCs)  

IoC – Type – Description

sssafjeuihiolsw[.]bond – Domain Name – Suspicious Link Domain

通知文件.docx – File - Payload  

References

[1] https://darktrace.com/blog/stopping-phishing-attacks-in-enter-language  

[2] https://darktrace.com/blog/attacks-are-getting-personal

[3] https://darktrace.com/blog/phishing-with-qr-codes-how-darktrace-detected-and-blocked-the-bait

[4] https://darktrace.com/blog/the-domain-game-how-email-attackers-are-buying-their-way-into-inboxes

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Rajendra Rushanth
Cyber Analyst

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The State of AI in Cybersecurity: The Impact of AI on Cybersecurity Solutions

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13
May 2024

About the AI Cybersecurity Report

Darktrace surveyed 1,800 CISOs, security leaders, administrators, and practitioners from industries around the globe. Our research was conducted to understand how the adoption of new AI-powered offensive and defensive cybersecurity technologies are being managed by organizations.

This blog continues the conversation from “The State of AI in Cybersecurity: Unveiling Global Insights from 1,800 Security Practitioners” which was an overview of the entire report. This blog will focus on one aspect of the overarching report, the impact of AI on cybersecurity solutions.

To access the full report, click here.

The effects of AI on cybersecurity solutions

Overwhelming alert volumes, high false positive rates, and endlessly innovative threat actors keep security teams scrambling. Defenders have been forced to take a reactive approach, struggling to keep pace with an ever-evolving threat landscape. It is hard to find time to address long-term objectives or revamp operational processes when you are always engaged in hand-to-hand combat.                  

The impact of AI on the threat landscape will soon make yesterday’s approaches untenable. Cybersecurity vendors are racing to capitalize on buyer interest in AI by supplying solutions that promise to meet the need. But not all AI is created equal, and not all these solutions live up to the widespread hype.  

Do security professionals believe AI will impact their security operations?

Yes! 95% of cybersecurity professionals agree that AI-powered solutions will level up their organization’s defenses.                                                                

Not only is there strong agreement about the ability of AI-powered cybersecurity solutions to improve the speed and efficiency of prevention, detection, response, and recovery, but that agreement is nearly universal, with more than 95% alignment.

This AI-powered future is about much more than generative AI. While generative AI can help accelerate the data retrieval process within threat detection, create quick incident summaries, automate low-level tasks in security operations, and simulate phishing emails and other attack tactics, most of these use cases were ranked lower in their impact to security operations by survey participants.

There are many other types of AI, which can be applied to many other use cases:

Supervised machine learning: Applied more often than any other type of AI in cybersecurity. Trained on attack patterns and historical threat intelligence to recognize known attacks.

Natural language processing (NLP): Applies computational techniques to process and understand human language. It can be used in threat intelligence, incident investigation, and summarization.

Large language models (LLMs): Used in generative AI tools, this type of AI applies deep learning models trained on massively large data sets to understand, summarize, and generate new content. The integrity of the output depends upon the quality of the data on which the AI was trained.

Unsupervised machine learning: Continuously learns from raw, unstructured data to identify deviations that represent true anomalies. With the correct models, this AI can use anomaly-based detections to identify all kinds of cyber-attacks, including entirely unknown and novel ones.

What are the areas of cybersecurity AI will impact the most?

Improving threat detection is the #1 area within cybersecurity where AI is expected to have an impact.                                                                                  

The most frequent response to this question, improving threat detection capabilities in general, was top ranked by slightly more than half (57%) of respondents. This suggests security professionals hope that AI will rapidly analyze enormous numbers of validated threats within huge volumes of fast-flowing events and signals. And that it will ultimately prove a boon to front-line security analysts. They are not wrong.

Identifying exploitable vulnerabilities (mentioned by 50% of respondents) is also important. Strengthening vulnerability management by applying AI to continuously monitor the exposed attack surface for risks and high-impact vulnerabilities can give defenders an edge. If it prevents threats from ever reaching the network, AI will have a major downstream impact on incident prevalence and breach risk.

Where will defensive AI have the greatest impact on cybersecurity?

Cloud security (61%), data security (50%), and network security (46%) are the domains where defensive AI is expected to have the greatest impact.        

Respondents selected broader domains over specific technologies. In particular, they chose the areas experiencing a renaissance. Cloud is the future for most organizations,
and the effects of cloud adoption on data and networks are intertwined. All three domains are increasingly central to business operations, impacting everything everywhere.

Responses were remarkably consistent across demographics, geographies, and organization sizes, suggesting that nearly all survey participants are thinking about this similarly—that AI will likely have far-reaching applications across the broadest fields, as well as fewer, more specific applications within narrower categories.

Going forward, it will be paramount for organizations to augment their cloud and SaaS security with AI-powered anomaly detection, as threat actors sharpen their focus on these targets.

How will security teams stop AI-powered threats?            

Most security stakeholders (71%) are confident that AI-powered security solutions are better able to block AI-powered threats than traditional tools.

There is strong agreement that AI-powered solutions will be better at stopping AI-powered threats (71% of respondents are confident in this), and there’s also agreement (66%) that AI-powered solutions will be able to do so automatically. This implies significant faith in the ability of AI to detect threats both precisely and accurately, and also orchestrate the correct response actions.

There is also a high degree of confidence in the ability of security teams to implement and operate AI-powered solutions, with only 30% of respondents expressing doubt. This bodes well for the acceptance of AI-powered solutions, with stakeholders saying they’re prepared for the shift.

On the one hand, it is positive that cybersecurity stakeholders are beginning to understand the terms of this contest—that is, that only AI can be used to fight AI. On the other hand, there are persistent misunderstandings about what AI is, what it can do, and why choosing the right type of AI is so important. Only when those popular misconceptions have become far less widespread can our industry advance its effectiveness.  

To access the full report, click here.

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