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Integrating Email Security to Build a Posture Greater Than the Sum of Its Parts

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17
Apr 2023
17
Apr 2023
While 94% of all cyber-attacks come through the inbox, their destination is almost never email. Attacks often traverse to other areas, like cloud apps and infrastructure, endpoints, or networks. As a result, although security teams must establish a strong cornerstone of email security, they should also consider how those solutions fit into the wider security posture.

On its own, Darktrace/Email™ stops attacks before they reach an employee’s inbox and considers both security teams and the employees themselves. But its value extends beyond email security, increased by its ability to integrate with the wider security ecosystem, including both Darktrace products and external tools. 

Darktrace’s understanding of you and your organization can be applied anywhere your company has data. This unifying approach to cyber security feeds AI outputs into each other, from threat prevention to detection and response, in order to harden the entire security posture autonomously and continuously. The AI also enriches other security solutions an organization has in place by both ingesting and sharing data. This degree of integration transforms a security stack so that it is greater than the sum of its parts. 

Integrating Beyond Email to Enhance Detection and Response 

Integrating email security with other areas of the digital estate bolsters defenses, while reducing required resources. With more data, security teams gain a better understanding of the security stack and how attacks move through the system.

Traditional security solutions do this by either manually aggregating inputs from various tools or using a SIEM without native integrations to collate data. In contrast, Darktrace’s integration provides real-time intelligence communications between products to inform security teams. 

For example, context of network activity can provide more holistic email security. There’s a strong correlation between the websites users visit and the people that they email, which means information like web traffic provides insight into email threats, and vice versa. 

If an organization receives an email from a strange new sender, that happens to be have been sent from a domain nobody has ever visited, that added context could influence the aggression levels of actions taken. Integrations with endpoint security extends this type of informed decision-making to remote environments. These examples highlight the patented power of Darktrace/Network™ and Darktrace/Endpoint™ when paired with email coverage. 

Diagram depicting the flow of email activity generated by Darktrace Email Security tool.
Figure 2. Darktrace/Email works with Darktrace/Network and Darktrace/Endpoint to generate email insights from web traffic and vice versa. 

Email activity is tied to cloud/SaaS application account activity in an even more direct way. In the case of an account takeover, a suspicious Microsoft 365 login becomes even more suspicious if it is followed by highly unusual email activity, like new inbox rules being created. Too many email security solutions focus on the inbox alone, but viewing these areas in a single scope is critical for security teams wanting to understand the full timeline of an incident. 

To this end, Darktrace creates a 360-degree view of each user and their behavior. This comprehensive view goes beyond native security monitoring tools, allowing security teams to identify instances of data exfiltration, human error, misdirected emails, inappropriate link sharing, unusual log activity, and more. 

In one real-life example, the security team saw an attack from both an email and a SaaS perspective to quickly understand the whole picture, thanks to Darktrace/Email and Darktrace/Apps™. 

Darktrace customers are getting significant value from this integrated security stack. “The whole suite of products has given us 100% visibility across our whole ecosystem, which is fantastic. A lot of times we need to use many products to do that, and with the Darktrace products, I have that all in one,” commented a vice president of enterprise security and fraud management at a major credit union. 

Siloed solutions are a massive pain point in the cyber industry. Most companies have several, layered tools in their security stacks. When there is little to no communication between them, the security team must contend with an inflated workload and misses out on value. They must learn how to navigate several different dashboards, translate between languages and terms, and manually correlate data, in addition to monitoring all the solutions daily. This process makes maintaining security more difficult for the team, especially in a threat landscape with increasingly complex and fast-paced attacks. 

By sending and collecting information to and from other tools that the security team already uses, whether they are a part of Darktrace’s product stack or not, Darktrace/Email optimizes workflows so security teams can reallocate resources to larger, more strategic projects.  

Collaborating Across Email Security and Cyber Risk Management Tools

Syncing email protections with cyber risk management tools even further reduces risk and hardens security.

When emails are received from domain names associated with the brand of the client, an attack surface management tool can automatically analyze if those domains should be included as part of the attack surface scope or trigger malicious domain responses. 

In the other direction, when the attack surface management tool identifies malicious assets, like suspicious domains, spoofing sites, and typo squatters, it can inform email security decisions. With integrations between tools, these malicious assets automatically become watched domains with heightened sensitivity for inbound email. 

This integrated risk reduction can occur internally as well. When security teams look at cyber risk from an internal perspective, they may identify attack paths and high value targets within the company’s digital estate. By leveraging this understanding, Darktrace can determine which employees are critical components of potential attack paths. Once determined, the AI can test them by creating phishing simulations using details like real-life communication patterns and calendar data. These tests generate insights that feed back into Darktrace/Email to harden the environment, for example by heightening sensitivity. 

This demonstrates the benefits of combining Darktrace/Email and Darktrace PREVENT™. As part of the Cyber AI Loop, these connections between email security and cyber risk management are made easy for the security team to understand and act on. One customer noted how this integration had improved its security team’s workflow.  

“The more you use of Darktrace, the better it can correlate on your behalf,” said a Chief Information Officer at a construction company. “That’s why we’re all in with Darktrace now. We now have a holistic Darktrace footprint, which benefits us because we have more of the modules working on our behalf and not having to do the correlations separately or in isolation.” 

Supporting Compatibility with External Security Solutions

Darktrace/Email also works together with external tools. In addition to its mature integration with email providers like Microsoft 365 and Google Workspaces, Darktrace/Email has an open architecture that makes it immensely flexible. It is both API-driven and compatible with syslog, so it can integrate with any security tool and feed into any SIEM or SOAR. 

This unlimited capacity for integration allows Darktrace to detect and respond to threats more precisely with access to more data, as well as reduce the security team’s time-to-meaning by putting all relevant information in a single pane of glass. 

Darktrace/Email is also part of the Darktrace Mobile App, so security teams can view notifications, reports, and remediation actions at any time, even on the go. In this way, Darktrace not only fits into the greater security posture, but also with employees’ day-to-day workflow. 

Finally, Darktrace/Email supports data exports. These translate and share the data it collects within the email environment, allowing the security team to communicate key takeaways generated by Darktrace/Email to anyone within the organization. It can export directly to Microsoft Excel, or any other data analytics tool. This is especially useful for security teams as they work with other departments like IT, compliance, finance, and more. 

Integrations Add Value to the Darktrace Partnership

While Darktrace/Email is a powerful tool on its own, a major source of its value comes from its compatibility with the rest of Darktrace, other tools, people, and processes. 

Deploying multiple Darktrace products builds a robust security ecosystem that enhances detection while breaking down silos and improving workflows, therefore enabling the security team to take on higher-level and more strategic work. By integrating with external tools, Darktrace not only increases its own value but also maximizes the return on investment of other security solutions a team already has.  

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
Dan Fein
VP, Product

Based in New York, Dan joined Darktrace’s technical team in 2015, helping customers quickly achieve a complete and granular understanding of Darktrace’s product suite. Dan has a particular focus on Darktrace/Email, ensuring that it is effectively deployed in complex digital environments, and works closely with the development, marketing, sales, and technical teams. Dan holds a Bachelor’s degree in Computer Science from New York University.

Carlos Gray
Product Manager

Carlos Gonzalez Gray is a Product Marketing Manager at Darktrace. Based in the Madrid Office, Carlos engages with the global product team to ensure each product supports the company’s overall strategy and goals throughout their entire lifecycle. Previous to his position in the product team, Carlos worked as a Cyber Technology Specialist where he specialized in the OT sector protecting critical infrastructure.  His background as a consultant in Spain to IBEX 35 companies led him to become well versed in matters of compliance, auditing and data privacy as well. Carlos holds an Honors BA in Political Science and a Masters in Cybersecurity from IE 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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