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April 7, 2020
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Four Ways Cyber-Criminals Fly Under the Radar

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07
Apr 2020
Learn how cyber criminals evade detection. Darktrace analyses the four ways they operate under the radar. Read here to stay vigilant against cyber attacks.

The challenge of reliably attributing cyber-threats has amplified in recent years, as adversaries adopt a collection of techniques to ensure that even if their attacks are caught, they themselves escape detection and avoid punishment.

Detecting a threat is, of course, a very different technical challenge compared to tracing that activity back to a human operator. Nevertheless, at some point after the dust has settled, during the post-hoc incident analysis for example, someone somewhere may need to know who the suspects are. And in spite of all of our other advances, and also some recent successes in attributing offensive and cyber-criminal acts, only three out of every 100,000 cyber-crimes are prosecuted. Put simply, this is still an unsolved set of problems. Many of the successes we do have can be attributed more to operational security fails on the criminals’ end than any other active approaches. In fact, some recent trends have actually made reliable attribution even more challenging.

The four cyber-threat trends that make attribution difficult

There are four related trends in how threat-actors can procure and obtain attack capabilities that have resulted in an increase in complexity when attempting to reliably identify Tools, Techniques, and Procedures (TTPs) and attributing them to distinct threat-actors.

A Cybercrime-as-a-Service economy and supply chain allowing cyber-criminals to mix and match off the shelf offensive cyber capabilities.

Expansion of ‘Living off the Land’ (LoL) tool usage by threat-actors to evade traditional, signature-based security defenses, and to obfuscate their activity.

While Code Reuse has always existed in the hacker community, copying nation-state-grade attack code has recently become possible.

The barrier to entry for criminally motivated operators has been lowered, providing the means for less technical criminals, who are only limited by time and their imagination.

Figure 1: The four cyber-threat trends

Threat-actors can mix and match attack tools, creating attack stacks that can be tailored for a variety of campaigns.

Between a professional marketplace of cyber-crime tools and services, the increasing adoption of ‘Living off the Land’ techniques, and the reusing of code leaked from nation-state intelligence services, threat-actors with even the most limited technical ability can conduct highly sophisticated criminal campaigns. Prospective cyber-criminals now have four primary types of attack tools to choose from – with three of them brand new or greatly enhanced. Even more importantly, these threat-actors can mix and match attack tools, creating tactically flexible attack stacks that can be tailored for a variety of campaigns against a diverse set of victims.

Off the shelf attacks

The burgeoning and increasingly professional Cybercrime-as-a-Service market (estimated at $1.6B) provides a thriving marketplace of microservices, attack code, and attack platforms. Anyone with a motive and enough bitcoin and enthusiasm can become the next ‘cyber Don Corleone’. Many of these services offer dedicated account management and professional support 24 hours a day. The commercialization of the cyber-crime supply chain has raised the barrier to entry for Cybercrime-as-a-Service vendors, while at the same time lowering it for cyber-criminal operators.

Living off the Land

‘Living off the Land’ (LoL) and “malware-less” attacks have been on the rise for some time now. What makes these attack methods so dangerous is that they leverage standard operating system tools to conduct their nefarious business, making signature-based approaches that look for malware heuristics ineffective – including signature-based Intrusion Protection Systems.

These attacks in particular demonstrate the need for an approach to cyber security that goes beyond looking at what malware is being used. Rather than relying on static blacklists, security teams are instead turning to a more sophisticated approach that learns ‘normal’ for every user and device across an entire business. From that evolving baseline, this approach to defense can identify and contain anomalous activity indicative of a cyber-threat – all in real time.

Code reuse and repurpose

What is new, and unprecedented, is that cyber-criminals are gaining access to intelligence and nation-state grade attack code.

Hackers have always begged, borrowed, and stolen code from others, including attack code – just two notable examples include the Zeus trojan and RIG exploit kit code leaks that provided the code base for much of the current generation of threats. What is new and unprecedented is that, whether through malice or incompetence, cyber-criminals are gaining access to intelligence and nation-state grade attack code. The Shadowbroker leaks that resulted in Wannacry is one recent example of this trend, and one we expect to accelerate – especially with intelligence services actively outing each other’s methods.

Custom and bespoke techniques

The practice of hackers creating their own tools and researching their own exploits has a long and hallowed tradition, with headline-grabbing zero-days becoming more and more common. Nation-state actors in particular often make a distinction between attack operators and attack code developers, with the ability to request tailored and bespoke code and tools – not unlike the model that has been replicated in the Cybercrime-as-a-Service market. Even when developing custom tools, threat-actors frequently integrate code and exploits from other parties.

Figure 2: The four main attack tool types

When determining who is actually behind these attacks, though, what is most important is the ability to combine all four types of attack tools – this provides a further layer of obfuscation against methods that rely on pattern matching for detection whilst causing additional confusion for would-be investigators. An attacker can use any combination and variation of these tool types to create a different “Chimera” attack stack – making it that much more difficult to identify who is really the operator. Telling apart the operator from the Cybercrime-as-a-Service vendor, for example, is difficult when most of the TTPs that are evaluated are technical and derive from the tooling.

Figure 3: The TTP and Attribution Confusion Chain

Conclusion

As the challenge of attribution intensifies, our focus must turn to defending against cyber-attacks themselves.

The combination of the four threat trends outlined above has lowered the barrier to entry for criminally motivated operators. Less technical adversaries are now able to launch attacks at a speed and scale previously confined to the most organized and well-financed cyber-criminal rings. This change in circumstances has made attribution of offensive cyber activity drastically more complex, and it may be some time before the prosecution rate for cyber-crime gets good enough that it can act as a greater disincentive.

As the challenge of attribution intensifies, our focus must turn to defending against cyber-attacks themselves. You may not ever know who is attacking you, but if you can successfully thwart the full range of threats, new and old, your organization can continue to operate as normal.

Fortunately, defenders’ abilities to detect and respond to cyber-threats have significantly advanced in recent years, thanks to the latest developments in AI and machine learning. Over 3,500 organizations now rely on Cyber AI to detect and contain cyber-threats – whether attackers use pre-existing OS tools to masquerade their attacks or use bespoke and entirely new techniques to bypass rules and signatures. When a threat is identified, AI can respond autonomously by enforcing a user or device’s ‘pattern of life’, allowing ‘business as usual’ whilst ensuring the organization is protected from harm.

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.
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Oliver Rochford
Technical Director
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November 19, 2024

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Darktrace Leading the Future of Network Detection and Response with Recognition from KuppingerCole

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KuppingerCole has recognized Darktrace as an overall Leader, Product Leader, Market Leader and Innovation Leader in the KuppingerCole Leadership Compass: Network Detection and Response (2024).

With the perimeter all but dissolved, Network Detection and Response (NDR) tools are quickly becoming a critical component of the security stack, as the main tool to span the modern network. NDRs connect on-premises infrastructure to cloud, remote workers, identities, SaaS applications, and IoT/OT – something not available to EDR that requires agents and isolates visibility to individual devices.

KuppingerCole Analysts AG designated Darktrace an ‘Overall Leader’ position because of our continual innovation around user-led security. Self-Learning AI together with automated triage through Cyber AI Analyst and real-time autonomous response actions have been instrumental to security teams in stopping potential threats before they become a breach. With this time saved, Darktrace is leading beyond reactive security to truly harden a network, allowing the team to spend more time in preventive security measures.

Network Detection and Response protects where others fail to reach

NDR solutions operate at the network level, deploying inside or parallel to your network to ingest raw traffic via virtual or physical sensors. This gives them unprecedented potential to identify anomalies and possible breaches in any network - far beyond simple on-prem, into dynamic virtual environments, cloud or hybrid networks, cloud applications, and even remote devices accessing the corporate network via ZTNA or VPN.

Rather than looking at processes level data, NDR can detect the lateral movement of an adversary across multiple assets by analyzing network traffic patterns which endpoint solutions may not be able to identify [1]. In the face of a growing, complex environment, organizations large and small, will benefit from using NDRs either in conjunction, or as the foundation for, their Extended Detection and Response (XDR) for a unified view that improves their overall threat detection, ease of investigation and faster response times.

Today's NDR solutions are expected to include advanced ML and artificial intelligence (AI) algorithms [1]

Traditional IDS & IPS systems are labor intensive, requiring continuous rule creation, outdated signature maintenance, and manual monitoring for false positives or incorrect actions. This is no longer viable against a higher volume and changing landscape, making NDR the natural network tool to level against these evolutions. The role of AI in NDRs is designed to meet this challenge, “to reduce both the labor need for analysis and false positives, as well as add value by improving anomaly detection and overall security posture” .

Celebrating success in leadership and innovation

Darktrace is proud to have been recognized as an NDR “Overall Leader” in KuppingerCole Analyst AG’s Leadership Compass. The report gave further recognition to Darktrace as a ‘Product Leader”, “Innovation Leader” and “Market Leader”.

Maximum scores were received for core product categories, in addition to market presence and financial strength. Particular attention was directed to our innovation. This year has seen several NDR updates via Darktrace’s ActiveAI Security Platform version 6.2 which has enhanced investigation workflows and provided new AI transparency within the toolset.

Positive scores were also received for Darktrace’s deployment ecosystem and surrounding support, minimizing the need for extraneous integrations through a unique platform architecture that connects with over 90 other vendors.

High Scores received in Darktrace’s KuppingerCole Spider Chart across Core NDR capability areas
Figure 1: High Scores received in Darktrace’s KuppingerCole Spider Chart across Core NDR capability areas

Darktrace’s pioneering AI approach sets it apart

Darktrace / NETWORK’s approach is fundamentally different to other NDRs. Continual anomaly-based detection (our Self-Learning AI), understands what is normal across each of your network entities, and then examines deviations from these behaviors rather than needing to apply static rules or ML to adversary techniques. As a result, Darktrace / NETWORK can focus on surfacing the novel threats that cannot be anticipated, whilst our proactive solutions expose gaps that can be exploited and reduce the risk of known threats.    

Across the millions of possible network events that may occur, Darktrace’s Cyber AI Analyst reduces that manual workload for SOC teams by presenting only what is most important in complete collated incidents. This accelerates SOC Level 2 analyses of incidents by 10x2, giving time back, first for any necessary response and then for preventive workflows.

Finally, when incidents begin to escalate, Darktrace can natively (or via third-party) autonomously respond and take precise actions based on a contextual understanding of both the affected assets and incident in question so that threats can be disarmed without impacting wider operations.

Within the KuppingerCole report, several standout strengths were listed:

  • Cyber AI Analyst was celebrated as a core differentiator, enhancing both visibility and investigation into critical network issues and allowing a faster response.
  • Darktrace / NETWORK was singled for its user benefits. Both a clear interface for analysts with advanced filtering and analytical tools, and efficient role-based access control (RBAC) and configuration options for administrators.
  • At the product level, Darktrace was recognized for complete network traffic analysis (NTA) capabilities allowing extensive analysis into components like application use/type, fingerprinting, source/destination communication, in addition to comprehensive protocol support across a range of network device types from IT, OT, IoT and mobiles and detailed MITRE ATT&CK mapping.
  • Finally, at the heart of it, Darktrace’s innovation was highlighted in relation to its intrinsic Self Learning AI, utilizing multiple layers of deep learning, neural networks, LLMs, NLP, Generative AI and more to understand network activity and filter it for what’s critical on an individual customer level.

Going beyond reactive security

Darktrace’s visibility and AI-enabled detection, investigation and response enable security teams to focus on hardening gaps in their network through contextual relevance & priority. Darktrace / NETWORK explicitly gives time back to security teams allowing them to focus on the bigger strategic and governance workflows that sometimes get overlooked. This is enabled through proactive solutions intrinsically connected to our NDR:

  • Darktrace / Proactive Exposure Management, which looks beyond just CVE risks to instead discover, prioritize and validate risks by business impact and how to mobilize against them early, to reduce the number of real threats security teams face.
  • Darktrace / Incident Readiness & Recovery, a solution rather than service-based approach to incident response (IR) that lets teams respond in the best way to each incident and proactively test their familiarity and effectiveness of IR workflows with sophisticated incident simulations involving their own analysts and assets.

Together, these solutions allow Darktrace / NETWORK to go beyond the traditional NDR and shift teams to a more hardened and proactive state.

Putting customers first

Customers continue to sit at the forefront of Darktrace R&D, with their emerging needs and pain points being the direct inspiration for our continued innovation.

This year Darktrace / NETWORK has protected thousands of customers against the latest attacks, from data exfil and destruction, to unapproved privilege escalation and ransomware including strains like Medusa, Qilin and AlphV BlackCat.

In each instance, Darktrace / NETWORK was able to provide a holistic lens of the anomalies present in their traffic, collated those that were important, and either responded or gave teams the ability to take targeted actions against their threats – even when adversaries pivoted. In one example of a Gootloader compromise, Darktrace ensured a SOC went from detection to recovery within 5 days, 92.8% faster than the average containment time of 69 days.

Results like these, focused on user-led security, have secured Darktrace’s position within the latest NDR Leadership Compass.

To find out more about what makes Darktrace / NETWORK special, read the full KuppingerCole report.

References

[1] Osman Celik, KuppingerCole Leadership Compass:Network Detection and Response (2024)

[2] Darktrace's AI Analyst customer fleet data

[3] https://www.ibm.com/reports/data-breach

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Gabriel Few-Wiegratz
Product Marketing Manager

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November 1, 2024

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Inside the SOC

Phishing and Persistence: Darktrace’s Role in Defending Against a Sophisticated Account Takeover

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The exploitation of SaaS platforms

As businesses continue to grow and evolve, the need for sharing ideas through productivity and cloud Software-as-a-Service (SaaS) platforms is becoming increasingly crucial. However, these platforms have also become prime targets for cyber attackers.

Threat actors often exploit these widely-used services to gain unauthorized access, steal sensitive information, and disrupt business operations. The growing reliance on SaaS platforms makes them attractive entry points for cybercriminals, who use sophisticated techniques such as phishing, social engineering, and malware to compromise these systems.

Services like Microsoft 365 are regularly targeted by threat actors looking for an entry point into an organization’s environment to carry out malicious activities. Securing these platforms is crucial to protect business data and ensure operational continuity.

Darktrace / EMAIL detection of the phishing attack

In a recent case, Darktrace observed a customer in the manufacturing sector receiving a phishing email that led to a threat actor logging in and creating an email rule. Threat actors often create email rules to move emails to their inbox, avoiding detection. Additionally, Darktrace detected a spoofed domain registered by the threat actor. Despite already having access to the customer’s SaaS account, the actor seemingly registered this domain to maintain persistence on the network, allowing them to communicate with the spoofed domain and conduct further malicious activity.

Darktrace / EMAIL can help prevent compromises like this one by blocking suspicious emails as soon as they are identified. Darktrace’s AI-driven email detection and response recognizes anomalies that might indicate phishing attempts and applies mitigative actions autonomously to prevent the escalation of an attack.

Unfortunately, in this case, Darktrace was not configured in Autonomous Response mode at the time of the attack, meaning actions had to be manually applied by the customer’s security team. Had it been fully enabled, it would have held the emails, preventing them from reaching the intended recipient and stopping the attack at its inception.

However, Darktrace’s Managed Threat Detection alerted the Security Operations Center (SOC) team to the compromise, enabling them to thoroughly investigate the incident and notify the customer before further damage could occur.

The Managed Threat Detection service continuously monitors customer networks for suspicious activities that may indicate an emerging threat. When such activities are detected, alerts are sent to Darktrace’s expert Cyber Analysts for triage, significantly speeding up the remediation process.

Attack Overview

On May 2, 2024, Darktrace detected a threat actor targeting a customer in the manufacturing sector then an unusual login to their SaaS environment was observed prior to the creation of a new email rule.

Darktrace immediately identified the login as suspicious due to the rarity of the source IP (31.222.254[.]27) and ASN, coupled with the absence of multi-factor authentication (MFA), which was typically required for this account.

The new email rule was intended to mark emails as read and moved to the ‘Conversation History’ folder for inbound emails from a specific domain. The rule was named “….,,,”, likely the attacker attempting to setup their new rule with an unnoteworthy name to ensure it would not be noticed by the account’s legitimate owner. Likewise, by moving emails from a specific domain to ‘Conversation History’, a folder that is rarely used by most users, any phishing emails sent by that domain would remain undetected by the user.

Darktrace’s detection of the unusual SaaS login and subsequent creation of the new email rule “….,,,”.
Figure 1: Darktrace’s detection of the unusual SaaS login and subsequent creation of the new email rule “….,,,”.

The domain in question was identified as being newly registered and an example of a typosquat domain. Typosquatting involves registering new domains with intentional misspelling designed to convince users to visit fake, and often malicious, websites. This technique is often used in phishing campaigns to create a sense of legitimacy and trust and deceive users into providing sensitive information. In this case, the suspicious domain closely resembled several of the customer’s internal domains, indicating an attempt to impersonate the organization’s legitimate internal sites to gain the target’s trust. Furthermore, the creation of this lookalike domain suggests that the attack was highly targeted at this specific customer.

Interestingly, the threat actor registered this spoofed domain despite already having account access. This was likely intended to ensure persistence on the network without having to launch additional phishing attacks. Such use of spoofed domain could allow an attacker to maintain a foothold in their target network and escalate their malicious activities without having to regain access to the account. This persistence can be used for various purposes, including data exfiltration, spreading malware, or launching further attacks.

Following this, Darktrace detected a highly anomalous email being sent to the customer’s account from the same location as the initial unsual SaaS login. Darktrace’s anomaly-based detection is able to identify threats that human security teams and traditional signature-based methods might miss. By analyzing the expected behavior of network users, Darktrace can recognize the subtle deviations from the norm that may indicate malicious activity. Unfortunately, in this instance, without Darktrace’s Autonomous Response capability enabled, the phishing email was able to successfully reach the recipient. While Darktrace / EMAIL did suggest that the email should be held from the recipients inbox, the customer was required to manually approve it.

Despite this, the Darktrace SOC team were still able to support the customer as they were subscribed to the Managed Threat Detection service. Following the detection of the highlight anomalous activity surrounding this compromise, namely the unusual SaaS login followed by a new email rule, an alert was sent to the Darktrace SOC for immediate triage, who then contacted the customer directly urging immediate action.

Conclusion

This case underscores the need to secure SaaS platforms like Microsoft 365 against sophisticated cyber threats. As businesses increasingly rely on these platforms, they become prime targets for attackers seeking unauthorized access and disruption.

Darktrace’s anomaly-based detection and response capabilities are crucial in identifying and mitigating such threats. In this instance, Darktrace detected a phishing email that led to a threat actor logging in and creating a suspicious email rule. The actor also registered a spoofed domain to maintain persistence on the network.

Darktrace / EMAIL, with its AI-driven detection and analysis, can block suspicious emails before they reach the intended recipient, preventing attacks at their inception. Meanwhile, Darktrace’s SOC team promptly investigated the activity and alerted the customer to the compromise, enabling them to take immediate action to remediate the issue and prevent any further damage.

Credit to Vivek Rajan (Cyber Security Analyst) and Ryan Traill (Threat Content Lead).

Appendices

Darktrace Model Detections

  • SaaS / Access / Unusual External Source for SaaS Credential Use
  • SaaS / Compromise / Login From Rare Endpoint While User Is Active
  • SaaS / Resource / Unusual Access to Delegated Resource by Non Owner
  • SaaS / Email Nexus / Unusual Login Location Following Sender Spoof
  • Compliance / Anomalous New Email Rule
  • SaaS / Compromise / Unusual Login and New Email Rule

Indicators of Compromise (IoCs)

IoC - Type - Description + Confidence

31.222.254[.]27 – IP -  Suspicious Login Endpoint

MITRE ATT&CK Mapping

Tactic – Technqiue – Sub-technique of (if applicable)

Cloud Accounts - DEFENSE EVASION, PERSISTENCE, PRIVILEGE ESCALATION, INITIAL ACCESS - T1078.004 - T1078

Cloud Service Dashboard – DISCOVERY - T1538

Compromise Accounts - RESOURCE DEVELOPMENT - T1586

Steal Web Session Cookie - CREDENTIAL ACCESS - T1539

Outlook Rules – PERSISTENCE - T1137.005 - T1137

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About the author
Vivek Rajan
Cyber Analyst
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