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Finding the Right Cyber Security AI for You

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20
Dec 2022
20
Dec 2022
This blog explores the nuances of AI in cyber security, how to identify true AI, and considerations when integrating AI technology with people, processes, and other technology.

AI has long been a buzzword – we started seeing it utilized in consumer space; in social media, e-commerce, and even in our music preference! In the past few years it has started to make its way through the enterprise space, especially in cyber security.

Increasingly, we see threat actors utilizing AI in their attack techniques. This is inevitable with the advancements in AI technology, the lower barrier to entry to the cyber security industry, and the continued profitability of being a threat actor. Surveying security decision makers across different industries like financial services and manufacturing, 77% of the respondents expect weaponized AI to lead to an increase in the scale and speed of attacks. 

Defenders are also ramping up their use of AI in cyber security – with more than 80% of the respondents agreeing that organizations require advanced defenses to combat offensive AI – resulted in a ‘cyber arms race’ with adversaries and security teams in constant pursuit of the latest technological advancements.  

The rules and signature approach is no longer sufficient in this evolving threat landscape. Because of this collective need, we will continue to see the push of AI innovations in this space as well. By 2025, cyber security technologies will account for 25% of the AI software market.

Despite the intrigue surrounding AI, many people have a limited understanding of how it truly works. The mystery of AI technology is what piques the interest of many cyber security practitioners. As an industry we also know that AI is necessary for advancement, but there is so much noise around AI and machine learning that some teams struggle to understand it. The paradox of choice leaves security teams more frustrated and confused by all the options presented to them.

Identifying True AI

You first need to define what you want the AI technology to solve. This might seem trivial, but many security teams often forget to come back to the fundamentals: what problem are you addressing? What are you trying to improve? 

Not every process needs AI; some processes will simply need automation – these are the more straightforward parts of your business. More complex and bigger systems require AI. The crux is identifying these parts of your business, applying AI and being clear of what you are going to achieve with these AI technologies. 

For example, when it comes to factory floor operations or tracking leave days of employees, businesses employ automation technologies, but when it comes to business decisions like PR strategies or new business exploration, AI is used to predict trends and help business owners make these decisions. 

Similarly, in cyber security, when dealing with known threats such as known malicious malware and hosting sites, automation is great at keeping track of them; workflows and playbooks are also best assessed with automation tools. However, when it comes to unknown unknowns like zero-day attacks, insider threats, IoT threats and supply chain attacks, AI is needed to detect and respond these threats as they emerge.

Automation is often communicated as AI, and it becomes difficult for security teams to differentiate. Automation helps you to quickly make a decision you already know you will make, whereas true AI helps you make a better decision.

Key ways to differentiate true AI from automation:

  • The Data Set: In automation, what you are looking for is very well-scoped. You already know what you are looking for – you are just accelerating the process with rules and signatures. True AI is dynamic. You no longer need to define activities that deserve your attention, the AI highlights and prioritizes this for you.
  • Bias: When you define what you are looking for, as humans inherently we impose our biases on these decisions. We are also limited by our knowledge at that point in time – this leaves out the crucial unknown unknowns.
  • Real-time: Every organization is always changing and it is important that AI takes all that data into consideration. True AI that is real time and also changes with your organization’s growth is hard to find. 

Our AI Research Centre has produced numerous papers on the applications of true AI in cyber security. The Centre comprises of more than 150 members and has more than 100 patents and patents pending. Some of the featured white papers include research on Attack Path Modeling and using AI as a preventative approach in your organization. 

Integrating AI Outputs with People, Process, and Technology


Integrating AI with People

We are living in the time of trust deficit, and that applies to AI as well. As humans we can be skeptical with AI, so how do we build trust for AI such that it works for us? This applies not only to the users of the technology, but the wider organization as well. Since this is the People pillar, the key factors to achieving trust in AI is through education, culture, and exposure. In a culture where people are open to learn and try new AI technologies, we will naturally build trust towards AI over time.

Integrating AI with Process

Then we should consider the integration of AI and its outputs into your workflow and playbooks. To make decisions around that, security managers need to be clear what their security priorities are, or which security gaps a particular technology is meant to fill. Regardless of whether you have an outsourced MSSP/SOC team, 50-strong in-house SOC team, or even just a 2-man team, it is about understanding your priorities and assigning the proper resources to them.

Integrating AI with Technology 

Finally, there is the integration of AI with your existing technology stack. Most security teams deploy different tools and services to help them achieve different goals – whether it is a tool like SIEM, a firewall, an endpoint, or services like pentesting, or vulnerability assessment exercises. One of the biggest challenges is putting all of this information together and pulling actionable insights out of them. Integration on multiple levels is always challenging with complex technologies because they technologies can rate or interpret threats differently.

Security teams often find themselves spending the most time making sense of the output of different tools and services. For example, taking the outcomes from a pentesting report and trying to enhance SOAR configurations, or looking at SOC alerts to advise firewall configurations, or taking vulnerability assessment reports to scope third-party Incident Response teams.

These tools can have a strong mastery of large volumes of data, but eventually ownership of the knowledge should still lie with the human teams – and the way to do that is with continuous feedback and integration. It is no longer efficient to use human teams to carry out this at scale and at speed. 

The Cyber AI Loop is Darktrace’s approach to cyber security. The four product families make up a key aspect of an organization’s cyber security posture. Darktrace PREVENT, DETECT, RESPOND and HEAL each feed back into a continuous, virtuous cycle, constantly strengthening each other’s abilities. 

This cycle augments humans at every stage of an incident lifecycle. For example, PREVENT may alert you to a vulnerability which holds a particularly high risk potential for your organization. It provides clear mitigation advice, and while you are on this, PREVENT will feed into DETECT and RESPOND, which are immediately poised to kick in should an attack occur in the interim. Conversely, once an attack has been contained by RESPOND, it will feed information back into PREVENT which will anticipate an attacker’s likely next move. Cyber AI Loop helps you harden security a holistic way so that month on month, year on year, the organization continuously improves its defensive posture. 

Explainable AI

Despite its complexity, AI needs to produce outputs that are clear and easy to understand in order to be useful. In the heat of the moment during a cyber incident, human teams need to quickly comprehend: What happened here? When did it happen? What devices are affected? What does it mean for my business? What should I deal with first?

To this end, Darktrace applies another level of AI on top of its initial findings that autonomously investigates in the background, reducing a mass of individual security events to just a few overall cyber incidents worthy of human review. It generates natural-language incident reports with all the relevant information for your team to make judgements in an instant. 

Figure 1: An example of how Darktrace filters individual model breaches into incidents and then critical incidents for the human to review 

Cyber AI Analyst does not only take into consideration network detection but also in your endpoints, your cloud space, IoT devices and OT devices. Cyber AI Analyst also looks at your attack surface and the risks associated to triage and show you the most prioritized alerts that if unexpected would cause maximum damage to your organization. These insights are not only delivered in real time but also unique to your environment.

This also helps address another topic that frequently comes up in conversations around AI: false positives. This is of course a valid concern: what is the point of harvesting the value of AI if it means that a small team now must look at thousands of alerts? But we have to remember that while AI allows us to make more connections over the vastness of logs, its goal is not to create more work for security teams, but to augment them instead.

To ensure that your business can continue to own these AI outputs and more importantly the knowledge, Explainable AI such as that used in Darktrace’s Cyber AI Analyst is needed to interpret the findings of AI, to ensure human teams know what happened, what action (if any) the AI took, and why. 

Conclusion

Every organization is different, and its security should reflect that. However, some fundamental common challenges of AI in cyber security are shared amongst all security teams, regardless of size, resources, industry vertical, and culture. Their cyber strategy and maturity levels are what sets them apart. Maturity is not defined by how many professional certifications or how many years of experience the team has. A mature team works together to solve problems. They understand that while AI is not the silver bullet, it is a powerful bullet that if used right, will autonomously harden the security of the complete digital ecosystem, while augmenting the humans tasked with defending it. 

DENTRO DEL SOC
Darktrace son expertos de talla mundial en inteligencia de amenazas, caza de amenazas y respuesta a incidentes, y proporcionan apoyo al SOC las 24 horas del día a miles de clientes de Darktrace en todo el mundo. Inside the SOC está redactado exclusivamente por estos expertos y ofrece un análisis de los ciberincidentes y las tendencias de las amenazas, basado en la experiencia real sobre el terreno.
AUTOR
SOBRE EL AUTOR
Germaine Tan
VP of Cyber Risk Management

Germaine is the Director of Analysis, APAC at Darktrace. Based in Singapore, she works with CISOs, managers and security teams all over APAC on model optimization and operationalization of Darktrace in their digital environments. She also manages the team of 17 analysts in the APAC region that threat hunts and monitors networks from all over the world. Germaine holds a Bachelor of Science in Engineering and a Masters of Science in Technology Management from Nanyang Technological University. She is CISSP, CRISC and CEH certified.

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Email

How to Protect your Organization Against Microsoft Teams Phishing Attacks

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21
May 2024

The problem: Microsoft Teams phishing attacks are on the rise

Around 83% of Fortune 500 companies rely on Microsoft Office products and services1, with Microsoft Teams and Microsoft SharePoint in particular emerging as critical platforms to the business operations of the everyday workplace. Researchers across the threat landscape have begun to observe these legitimate services being leveraged more and more by malicious actors as an initial access method.

As Teams becomes a more prominent feature of the workplace many employees rely on it for daily internal and external communication, even surpassing email usage in some organizations. As Microsoft2 states, "Teams changes your relationship with email. When your whole group is working in Teams, it means you'll all get fewer emails. And you'll spend less time in your inbox, because you'll use Teams for more of your conversations."

However, Teams can be exploited to send targeted phishing messages to individuals either internally or externally, while appearing legitimate and safe. Users might receive an external message request from a Teams account claiming to be an IT support service or otherwise affiliated with the organization. Once a user has accepted, the threat actor can launch a social engineering campaign or deliver a malicious payload. As a primarily internal tool there is naturally less training and security awareness around Teams – due to the nature of the channel it is assumed to be a trusted source, meaning that social engineering is already one step ahead.

Screenshot of a Microsoft Teams message request from a Midnight Blizzard-controlled account (courtesy of Microsoft)
Figure 1: Screenshot of a Microsoft Teams message request from a Midnight Blizzard-controlled account (courtesy of Microsoft)

Microsoft Teams Phishing Examples

Microsoft has identified several major phishing attacks using Teams within the past year.

In July 2023, Microsoft announced that the threat actor known as Midnight Blizzard – identified by the United States as a Russian state-sponsored group – had launched a series of phishing campaigns via Teams with the aim of stealing user credentials. These attacks used previously compromised Microsoft 365 accounts and set up new domain names that impersonated legitimate IT support organizations. The threat actors then used social engineering tactics to trick targeted users into sharing their credentials via Teams, enabling them to access sensitive data.  

At a similar time, threat actor Storm-0324 was observed sending phishing lures via Teams containing links to malicious SharePoint-hosted files. The group targeted organizations that allow Teams users to interact and share files externally. Storm-0324’s goal is to gain initial access to hand over to other threat actors to pursue more dangerous follow-on attacks like ransomware.

For a more in depth look at how Darktrace stops Microsoft Teams phishing read our blog: Don’t Take the Bait: How Darktrace Keeps Microsoft Teams Phishing Attacks at Bay

The market: Existing Microsoft Teams security solutions are insufficient

Microsoft’s native Teams security focuses on payloads, namely links and attachments, as the principal malicious component of any phishing. These payloads are relatively straightforward to detect with their experience in anti-virus, sandboxing, and IOCs. However, this approach is unable to intervene before the stage at which payloads are delivered, before the user even gets the chance to accept or deny an external message request. At the same time, it risks missing more subtle threats that don’t include attachments or links – like early stage phishing, which is pure social engineering – or completely new payloads.

Equally, the market offering for Teams security is limited. Security solutions available on the market are always payload-focused, rather than taking into account the content and context in which a link or attachment is sent. Answering questions like:

  • Does it make sense for these two accounts to speak to each other?
  • Are there any linguistic indicators of inducement?

Furthermore, they do not correlate with email to track threats across multiple communication environments which could signal a wider campaign. Effectively, other market solutions aren’t adding extra value – they are protecting against the same types of threats that Microsoft is already covering by default.

The other aspect of Teams security that native and market solutions fail to address is the account itself. As well as focusing on Teams threats, it’s important to analyze messages to understand the normal mode of communication for a user, and spot when a user’s Teams activity might signal account takeover.

The solution: How Darktrace protects Microsoft Teams against sophisticated threats

With its biggest update to Darktrace/Email ever, Darktrace now offers support for Microsoft Teams. With that, we are bringing the same AI philosophy that protects your email and accounts to your messaging environment.  

Our Self-Learning AI looks at content and context for every communication, whether that’s sent in an email or Teams message. It looks at actual user behavior, including language patterns, relationship history of sender and recipient, tone and payloads, to understand if a message poses a threat. This approach allows Darktrace to detect threats such as social engineering and payloadless attacks using visibility and forensic capabilities that Microsoft security doesn’t currently offer, as well as early symptoms of account compromise.  

Unlike market solutions, Darktrace doesn’t offer a siloed approach to Teams security. Data and signals from Teams are shared across email to inform detection, and also with the wider Darktrace ActiveAI security platform. By correlating information from email and Teams with network and apps security, Darktrace is able to better identify suspicious Teams activity and vice versa.  

Interested in the other ways Darktrace/Email augments threat detection? Read our latest blog on how improving the quality of end-user reporting can decrease the burden on the SOC. To find our more about Darktrace's enduring partnership with Microsoft, click here.

References

[1] Essential Microsoft Office Statistics in 2024

[2] Microsoft blog, Microsoft Teams and email, living in harmony, 2024

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About the author
Carlos Gray
Product Manager

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Dentro del SOC

Don’t Take the Bait: How Darktrace Keeps Microsoft Teams Phishing Attacks at Bay

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20
May 2024

Social Engineering in Phishing Attacks

Faced with increasingly cyber-aware endpoint users and vigilant security teams, more and more threat actors are forced to think psychologically about the individuals they are targeting with their phishing attacks. Social engineering methods like taking advantage of the human emotions of their would-be victims, pressuring them to open emails or follow links or face financial or legal repercussions, and impersonating known and trusted brands or services, have become common place in phishing campaigns in recent years.

Phishing with Microsoft Teams

The malicious use of the popular communications platform Microsoft Teams has become widely observed and discussed across the threat landscape, with many organizations adopting it as their primary means of business communication, and many threat actors using it as an attack vector. As Teams allows users to communicate with people outside of their organization by default [1], it becomes an easy entry point for potential attackers to use as a social engineering vector.

In early 2024, Darktrace/Apps™ identified two separate instances of malicious actors using Microsoft Teams to launch a phishing attack against Darktrace customers in the Europe, the Middle East and Africa (EMEA) region. Interestingly, in this case the attackers not only used a well-known legitimate service to carry out their phishing campaign, but they were also attempting to impersonate an international hotel chain.

Despite these attempts to evade endpoint users and traditional security measures, Darktrace’s anomaly detection enabled it to identify the suspicious phishing messages and bring them to the customer’s attention. Additionally, Darktrace’s autonomous response capability, was able to follow-up these detections with targeted actions to contain the suspicious activity in the first instance.

Darktrace Coverage of Microsoft Teams Phishing

Chats Sent by External User and Following Actions by Darktrace

On February 29, 2024, Darktrace detected the presence of a new external user on the Software-as-a-Service (SaaS) environment of an EMEA customer for the first time. The user, “REDACTED@InternationalHotelChain[.]onmicrosoft[.]com” was only observed on this date and no further activities were detected from this user after February 29.

Later the same day, the unusual external user created its first chat on Microsoft Teams named “New Employee Loyalty Program”. Over the course of around 5 minutes, the user sent 63 messages across 21 different chats to unique internal users on the customer’s SaaS platform. All these chats included the ‘foreign tenant user’ and one of the customer’s internal users, likely in an attempt to remain undetected. Foreign tenant user, in this case, refers to users without access to typical internal software and privileges, indicating the presence of an external user.

Darktrace’s detection of unusual messages being sent by a suspicious external user via Microsoft Teams.
Figure 1: Darktrace’s detection of unusual messages being sent by a suspicious external user via Microsoft Teams.
Advanced Search results showing the presence of a foreign tenant user on the customer’s SaaS environment.
Figure 2: Advanced Search results showing the presence of a foreign tenant user on the customer’s SaaS environment.

Darktrace identified that the external user had connected from an unusual IP address located in Poland, 195.242.125[.]186. Darktrace understood that this was unexpected behavior for this user who had only previously been observed connecting from the United Kingdom; it further recognized that no other users within the customer’s environment had connected from this external source, thereby deeming it suspicious. Further investigation by Darktrace’s analyst team revealed that the endpoint had been flagged as malicious by several open-source intelligence (OSINT) vendors.

External Summary highlighting the rarity of the rare external source from which the Teams messages were sent.
Figure 3: External Summary highlighting the rarity of the rare external source from which the Teams messages were sent.

Following Darktrace’s initial detection of these suspicious Microsoft Teams messages, Darktrace's autonomous response was able to further support the customer by providing suggested mitigative actions that could be applied to stop the external user from sending any additional phishing messages.

Unfortunately, at the time of this attack Darktrace's autonomous response capability was configured in human confirmation mode, meaning any autonomous response actions had to be manually actioned by the customer. Had it been enabled in autonomous response mode, it would have been able promptly disrupt the attack, disabling the external user to prevent them from continuing their phishing attempts and securing precious time for the customer’s security team to begin their own remediation procedures.

Darktrace autonomous response actions that were suggested following the ’Large Volume of Messages Sent from New External User’ detection model alert.
Figure 4: Darktrace autonomous response actions that were suggested following the ’Large Volume of Messages Sent from New External User’ detection model alert.

External URL Sent within Teams Chats

Within the 21 Teams chats created by the threat actor, Darktrace identified 21 different external URLs being sent, all of which included the domain "cloud-sharcpoint[.]com”. Many of these URLs had been recently established and had been flagged as malicious by OSINT providers [3]. This was likely an attempt to impersonate “cloud-sharepoint[.]com”, the legitimate domain of Microsoft SharePoint, with the threat actor attempting to ‘typo-squat’ the URL to convince endpoint users to trust the legitimacy of the link. Typo-squatted domains are commonly misspelled URLs registered by opportunistic attackers in the hope of gaining the trust of unsuspecting targets. They are often used for nefarious purposes like dropping malicious files on devices or harvesting credentials.

Upon clicking this malicious link, users were directed to a similarly typo-squatted domain, “InternatlonalHotelChain[.]sharcpoInte-docs[.]com”. This domain was likely made to appear like the SharePoint URL used by the international hotel chain being impersonated.

Redirected link to a fake SharePoint page attempting to impersonate an international hotel chain.
Figure 5: Redirected link to a fake SharePoint page attempting to impersonate an international hotel chain.

This fake SharePoint page used the branding of the international hotel chain and contained a document named “New Employee Loyalty Program”; the same name given to the phishing messages sent by the attacker on Microsoft Teams. Upon accessing this file, users would be directed to a credential harvester, masquerading as a Microsoft login page, and prompted to enter their credentials. If successful, this would allow the attacker to gain unauthorized access to a user’s SaaS account, thereby compromising the account and enabling further escalation in the customer’s environment.

Figure 6: A fake Microsoft login page that popped-up when attempting to open the ’New Employee Loyalty Program’ document.

This is a clear example of an attacker attempting to leverage social engineering tactics to gain the trust of their targets and convince them to inadvertently compromise their account. Many corporate organizations partner with other companies and well-known brands to offer their employees loyalty programs as part of their employment benefits and perks. As such, it would not necessarily be unexpected for employees to receive such an offer from an international hotel chain. By impersonating an international hotel chain, threat actors would increase the probability of convincing their targets to trust and click their malicious messages and links, and unintentionally compromising their accounts.

In spite of the attacker’s attempts to impersonate reputable brands, platforms, Darktrace/Apps was able to successfully recognize the malicious intent behind this phishing campaign and suggest steps to contain the attack. Darktrace recognized that the user in question had deviated from its ‘learned’ pattern of behavior by connecting to the customer’s SaaS environment from an unusual external location, before proceeding to send an unusually large volume of messages via Teams, indicating that the SaaS account had been compromised.

A Wider Campaign?

Around a month later, in March 2024, Darktrace observed a similar incident of a malicious actor impersonating the same international hotel chain in a phishing attacking using Microsoft Teams, suggesting that this was part of a wider phishing campaign. Like the previous example, this customer was also based in the EMEA region.  

The attack tactics identified in this instance were very similar to the previously example, with a new external user identified within the network proceeding to create a series of Teams messages named “New Employee Loyalty Program” containing a typo-squatted external links.

There were a few differences with this second incident, however, with the attacker using the domain “@InternationalHotelChainExpeditions[.]onmicrosoft[.]com” to send their malicious Teams messages and using differently typo-squatted URLs to imitate Microsoft SharePoint.

As both customers targeted by this phishing campaign were subscribed to Darktrace’s Proactive Threat Notification (PTN) service, this suspicious SaaS activity was promptly escalated to the Darktrace Security Operations Center (SOC) for immediate triage and investigation. Following their investigation, the SOC team sent an alert to the customers informing them of the compromise and advising urgent follow-up.

Conclusion

While there are clear similarities between these Microsoft Teams-based phishing attacks, the attackers here have seemingly sought ways to refine their tactics, techniques, and procedures (TTPs), leveraging new connection locations and creating new malicious URLs in an effort to outmaneuver human security teams and conventional security tools.

As cyber threats grow increasingly sophisticated and evasive, it is crucial for organizations to employ intelligent security solutions that can see through social engineering techniques and pinpoint suspicious activity early.

Darktrace’s Self-Learning AI understands customer environments and is able to recognize the subtle deviations in a device’s behavioral pattern, enabling it to effectively identify suspicious activity even when attackers adapt their strategies. In this instance, this allowed Darktrace to detect the phishing messages, and the malicious links contained within them, despite the seemingly trustworthy source and use of a reputable platform like Microsoft Teams.

Credit to Min Kim, Cyber Security Analyst, Raymond Norbert, Cyber Security Analyst and Ryan Traill, Threat Content Lead

Appendix

Darktrace Model Detections

SaaS Model

Large Volume of Messages Sent from New External User

SaaS / Unusual Activity / Large Volume of Messages Sent from New External User

Indicators of Compromise (IoCs)

IoC – Type - Description

https://cloud-sharcpoint[.]com/[a-zA-Z0-9]{15} - Example hostname - Malicious phishing redirection link

InternatlonalHotelChain[.]sharcpolnte-docs[.]com – Hostname – Redirected Link

195.242.125[.]186 - External Source IP Address – Malicious Endpoint

MITRE Tactics

Tactic – Technique

Phishing – Initial Access (T1566)

References

[1] https://learn.microsoft.com/en-us/microsoftteams/trusted-organizations-external-meetings-chat?tabs=organization-settings

[2] https://www.virustotal.com/gui/ip-address/195.242.125.186/detection

[3] https://www.virustotal.com/gui/domain/cloud-sharcpoint.com

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About the author
Min Kim
Cyber Security Analyst
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