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The Cyber Security Shortages Holding Back Numerous Countries

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04
Sep 2022
04
Sep 2022
Many emerging markets in the Global South suffer from ineffective cyber legislation and crippling skill shortages. Learn how these markets need protection.

As a flurry of tech startup investment driven by the pandemic tailed off in the second quarter of 2022, funding for startups fell globally by 23%, the largest drop in over a decade. In Africa, however, that funding doubled over the same period. The continent has seen a wave of venture capital from within and without, and increasing numbers of ‘unicorns’ – startups valued at over $1 billion. 

For investors, the continent is steadily becoming a safer bet, but certain concerns remain, not least of which is the cyber-reliance of many African nations and businesses. A 2021 report by Interpol suggests that the continent’s GDP is reduced by up to 10% (equivalent to $4.12 billion in 2021) by cybercrime alone. If emerging markets like Nigeria, South Africa, and Kenya are to continue drawing investment, they’ll need to match business innovation with more effective security measures.

The Cost of a Continental Skill Shortage

Cyber skill shortages remain an issue in many Global South markets, meaning the impact of common threats is effectively magnified when they hit organizations in these nations. Having the expertise on hand to reduce time-to-response and take decisive, effective remediation action can be the difference between a bullet point on a threat report and a fully-fledged attack.

Many cyber professionals will think of WannaCry, a ransomware attack which affected over 200,000 devices in 2017, as a threat of the past, its relevance consigned to the months after its first appearance. For countries in Latin America and the Caribbean, however, it remains a prevalent and punishing tool, and continues to target thousands of systems: the highest number of WannaCry attacks are consistently seen in Brazil, Ecuador, and Chile. Why is so much damage still being wrought by a ransomware strain which was largely thrown into obsolescence in the Global North years ago? Think tanks like the RUSI attribute it to a lack of IT professionals and the slow uptake of new security standards in regions which are otherwise enjoying rapid digitalization. 

The discordance between internet penetration rates and cyber security capabilities is even more pronounced in Africa. An estimate made in 2018 suggested that there were only 7,000 certified security professionals in the continent, one for every 177,000 people. In the US, comparatively, the figure was one for every 330 people. Even adjusting for Africa’s reduced internet penetration rate, the figure remains one professional for every 45,140 internet users. 

The result of this is that 9 in every 10 African businesses are said to operate without necessary cyber security protocols in place. If the continent continues to draw investment without making big strides in its cyber security measures, its rapidly growing base of potential victims (Africa’s internet using population numbers over 650 million, massively outstripping North America’s 350 million) will draw increasing numbers of cyber-attacks.

Attackers Destabilize the Market

There is already evidence that attackers are beginning to take notice. Interpol cites a report claiming that in the first months of 2021, African organizations saw the highest increase in ransomware attacks of any region. But it is the efficacy, rather than frequency, of attacks on Global South nations which will be most concerning to investors seeking stability. 

Last year in South Africa, several major trade ports were brought to a halt by a ransomware attack on Transnet and, just a few months later, the country’s justice department was brought down in a similar attack. In Costa Rica earlier this year, the ransomware group Conti successfully locked down several government systems and threatened to overthrow the presiding government if ransom payments were not made, leading President Chaves to declare a national state of emergency. Organizations operating critical national infrastructure are particularly attractive to attackers, as the disruption caused by their downtime makes it easier to extort a generous ransom. These attacks are also high-profile, often internationally so. 

High-profile attacks can greatly affect the confidence of investors and potential business partners. A KPMG report on cyber risks in emerging markets explains: “Those suppliers handling confidential third-party data in emerging markets that are able to demonstrate strong security posture around that data are likely to be more attractive and potentially able to win more business.” Organizations in countries with generally weaker cyber security practices should be looking at tools to put the concerns of potential partners and investors at ease. Ideally these should be AI-driven tools which not only stop old, known threats, but also those headline-grabbing novel attacks and zero days.

Protecting Progress

Many Global South governments are now taking steps to address cybercrime concerns, and bring legislation up to global standards. Last year, South Africa’s President Cyril Ramaphosa signed the Cybercrimes and Cybersecurity Act, placing new breach reporting responsibilities on organizations. Similar acts were passed in nations such as Zambia and Ecuador the same year.

International cooperation on the issue of cyber security is also more common: the Convention on Cyber-security and Personal Data Protection adopted by the African Union's 55 member states in 2014 has now been ratified by thirteen nations, while in July of this year, delegates from Bangladesh, Bhutan, India, Myanmar, Nepal, Sri Lanka, and Thailand gathered for the inaugural BIMSTEC (Bay of Bengal Initiative for Multi-Sectoral Technical and Economic Cooperation) meeting on cyber security cooperation

These are important steps, but legislation and discussion will do little if organizations do not take action in their wake. As we stressed in our recent blog on modern cyber warfare, the involvement of the private sector in government directives is crucial to tackling widespread cyber threats. Togo’s Minister of Digital Economy stressed this fact when he announced the new African Centre for Coordination and Research in Cybersecurity last month: “Our partnership model with the private sector is an innovative approach that we want to showcase to inspire other countries for safer cyberspace on the continent.”

For emerging markets to thrive globally, the organizations within them need to recognize the growing target on their backs, and protect themselves and their data from increasing numbers of sophisticated cyber-attacks. Addressing crippling skill shortages may seem like a long-term – even generational – plan, but with the right tools it can be done almost immediately. AI solutions like Darktrace can autonomously prevent, detect, and respond to attacks, buying back hours for security professionals, and augmenting the ability of small teams to tackle numerous complex threats simultaneously. Darktrace PREVENT preempts attackers and continuously hardens defenses, ensuring that organizations are prepared for novel threats, rather than falling victim to old ransomware strains.

The economic significance of cyber resilience has become undeniable. With proper security investment, emerging markets and Global South nations can hold onto the billions being lost to cyber-attack costs, and continue to focus on business growth and innovation.

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
David Masson
Director of Enterprise Security

David Masson is Darktrace’s Director of Enterprise Security, and has over two decades of experience working in fast moving security and intelligence environments in the UK, Canada and worldwide. With skills developed in the civilian, military and diplomatic worlds, he has been influential in the efficient and effective resolution of various unique national security issues. David is an operational solutions expert and has a solid reputation across the UK and Canada for delivery tailored to customer needs. At Darktrace, David advises strategic customers across North America and is also a regular contributor to major international and national media outlets in Canada where he is based. He holds a master’s degree from Edinburgh University.

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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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