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February 12, 2018

The Rise of Cryptocurrency Attacks & Cyber Defense Solutions

Darktrace can detect cryptocurrency-related attacks with machine learning. Identify nefarious use of resources and protect against Coinhive drive-by mining.
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.
Written by
Max Heinemeyer
Global Field CISO
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12
Feb 2018

Prelude

The last 12 months have shown tremendous volatility in the value of cryptocurrencies, of which Bitcoin is the most prominent example. At the start of 2017, Bitcoin lingered around the $2,000 mark before suddenly taking off, climbing to historic highs of close to $20,000 in December 2017. Demand has since subsided, and at the time of writing, the price of Bitcoin is near to $10,772.

While Bitcoin is the most popular cryptocurrency, numerous alternatives, often called ‘altcoins’ have emerged and grown in value in the last 12 months. For example, Dogecoin, originally created to be a spoof cryptocurrency after a widespread internet meme, reached a notable market capitalization milestone of $2bn in January 2018.

Nowadays it is almost impossible to profitably mine Bitcoin on commodity hardware such as laptops, smartphones or desktop computers. At this late state, it just takes too long to perform the relevant calculations, and the cost of electricity is higher than the anticipated revenue in most cases. Other altcoins such as Monero use different algorithms, making them viable alternatives for aspiring crypto miners. It is often still feasible to mine altcoins on commodity hardware and see a return on investment.

The value of most altcoins is closely tied to the value of Bitcoin and, in many cases, the relationship is broadly proportional – a rise in Bitcoin prompting a similar lift in the altcoins. Monero, which has been rapidly adopted by Darknet markets, has profited from this effect. While Monero was valued at around $10 in January 2017, its price has been pumped up to $419 a year later.

There is much that is still not clear about the cryptocurrency phenomenon. Debate as to its relative value and its status as a currency rages, and will not be resolved any time soon. However, from a cyber security perspective there can be no doubt that the combination of altcoins being mineable on commodity hardware, the fact that mining is now becoming profitable as a side-effect of Bitcoin’s rise, and a maturity in cryptocurrency-related tech has led to a surge in cryptocurrency-related attacks.

Attack vectors

Darktrace has observed an abrupt increase of cryptocurrency-related attacks over the last 12 months. Both the frequency and the diversity of these attacks has grown significantly and largely mirrors the remarkable rise in the value of Bitcoin over that period.

Previously, cyber-criminals monetized their operations via banking Trojans/credit card fraud, selling stolen data and ransomware on the Darknet. However, criminals are notoriously adaptable and will follow the money wherever it leads, leading to an increase in cryptojacking’s popularity.

Cryptocurrency mining might not be as profitable as ransomware is upfront, but it can be secretly pursued for months without creating the havoc that characterizes ransomware attacks. Most users and security products might not notice a cryptocurrency miner being installed on a corporate device as it does not show obvious threats or messages to a user, except for an occasional increase in CPU or RAM usage.

Identifying these attacks can be very difficult for traditional security tools as they were not originally designed to catch this type of threat. Nor was Darktrace, but its approach – which relies on its evolving understanding of patterns of behavior – means that it can detect such attacks without having to know what to look for in advance.

Darktrace has detected a number of different attack vectors related to cryptocurrency attacks.

  1. Nefarious use of corporate resources
    Darktrace has detected a range of incidents where employees were intentionally installing cryptocurrency mining software on their corporate devices to mine for personal gain. These employees do not have to pay for the electricity used to run the corporate device in the office – they are basically turning their employer’s electricity into cash by commandeering it for mining operations.

    This is commonly seen as a compliance breach and increases the attack surface of a device that has mining software installed. It puts the corporate device at risk and also increases operational costs as the power consumption usually goes up for mining devices. The most popular cryptocurrency choices for this kind of mining in the last 12 months were Etherium and Monero – altcoins that can profitably be mined without the need for inordinate electricity.
  2. Coinhive drive-by mining
    Coinhive is a technology that allows website owners to use their visitors’ computing power to mine a tiny fraction of cryptocurrency for the website owner. Visitors will experience a small increase in computer resource consumption while browsing the website. Some websites experiment with this model to create new forms of revenue streams alternative to advertisement and banner placements.

    Coinhive usage is often not an opt-in process. Darktrace has observed various customer devices that regularly visit websites leveraging Coinhive technology. While the power consumption increase for a device browsing a website with Coinhive is ultimately negligible, the cumulative effect of a sizeable portion of the workforce unwittingly browsing websites using Coinhive results in increased power consumption cost for the organization as a whole.
  3. Malicious insider
    A malicious insider compromised his employer’s website to put a Coinhive script on there. This then mined Monero for every visitor on the employer’s website for the malicious insider’s personal gain.
  4. Traditional malware
    Cyber criminals are constantly looking to improve the return on investment of their operations. Reports suggest that criminals are starting to adjust their monetization methods based on the financial means of their targets. Suppose you can’t pay the fee extorted in a ransomware attack? They’ll just install a crypto miner on your device instead to ensure that the attack is not completely fruitless.

    As malware authors become more sophisticated, they often deploy multi-staged malware that can swap weaponized payloads. Once malware has infected a system successfully, its authors can often decide what actions to take next. Encrypt the device and extort a ransom? Install a banking Trojan to harvest credit card details? Install more spyware modules to look for data exfiltration? Or, now, install a cryptocurrency miner.

    These pieces of malware operate stealthily and often go undetected for several weeks. An infection might start with a phishing email that contains a macro-enabled document. As soon as a user enabled the macro, the malware will download a file-less stager that lives in memory and cannot be detected by traditional antivirus. Command and control communication is usually maintained via IP addresses that change on a daily basis in order to outrun threat intelligence and blacklisting attempts. As no obvious damage is done straight away, these attacks often stay under the radar for prolonged times, so long as self-learning technology such as Darktrace is not employed.

    This becomes much more concerning as malware authors could swap one payload for another overnight if they deem it more profitable, switching from a furtive crypto mining Trojan to ransomware the next day. While we have not observed this kind of attack in the wild yet, it is plausible, and in cyberspace what can be done, will be done.

Conclusions

Revolutionary technologies like cryptocurrencies have both their dark and light aspects. For all of the creative energy released by the crypto-blockchain revolution, Bitcoin and its alternatives have quickly become the universal currency of the criminal underworld. Indeed, the former Chief Economist of the World Bank, Joseph Stiglitz – an adamant critic of cryptocurrencies – has said that the whole value of Bitcoin resides in its “potential for circumvention” and “lack of oversight”.

While Stiglitz’s case may be overstated, there can be no question that cyber criminals have sensed a new opportunity to make money. A lot of organizations still regard crypto mining as a compliance incident. This can lead to grave consequences as a cryptocurrency mining device might lead to more severe incidents that can have a serious effect on business operations.

This kind of threat is difficult to detect as no obvious damage is done. However, with Darktrace’s machine learning we can correlate even the weakest indicators of such an attack into a compelling picture of threat. While traditional tools may struggle to see these deviations, Darktrace can pinpoint the changes in behavior effected by cryptocurrency miners without having to rely on any blacklists or signatures.

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.
Written by
Max Heinemeyer
Global Field CISO

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January 13, 2026

Runtime Is Where Cloud Security Really Counts: The Importance of Detection, Forensics and Real-Time Architecture Awareness

runtime, cloud security, cnaapDefault blog imageDefault blog image

Introduction: Shifting focus from prevention to runtime

Cloud security has spent the last decade focused on prevention; tightening configurations, scanning for vulnerabilities, and enforcing best practices through Cloud Native Application Protection Platforms (CNAPP). These capabilities remain essential, but they are not where cloud attacks happen.

Attacks happen at runtime: the dynamic, ephemeral, constantly changing execution layer where applications run, permissions are granted, identities act, and workloads communicate. This is also the layer where defenders traditionally have the least visibility and the least time to respond.

Today’s threat landscape demands a fundamental shift. Reducing cloud risk now requires moving beyond static posture and CNAPP only approaches and embracing realtime behavioral detection across workloads and identities, paired with the ability to automatically preserve forensic evidence. Defenders need a continuous, real-time understanding of what “normal” looks like in their cloud environments, and AI capable of processing massive data streams to surface deviations that signal emerging attacker behavior.

Runtime: The layer where attacks happen

Runtime is the cloud in motion — containers starting and stopping, serverless functions being called, IAM roles being assumed, workloads auto scaling, and data flowing across hundreds of services. It’s also where attackers:

  • Weaponize stolen credentials
  • Escalate privileges
  • Pivot programmatically
  • Deploy malicious compute
  • Manipulate or exfiltrate data

The challenge is complex: runtime evidence is ephemeral. Containers vanish; critical process data disappears in seconds. By the time a human analyst begins investigating, the detail required to understand and respond to the alert, often is already gone. This volatility makes runtime the hardest layer to monitor, and the most important one to secure.

What Darktrace / CLOUD Brings to Runtime Defence

Darktrace / CLOUD is purpose-built for the cloud execution layer. It unifies the capabilities required to detect, contain, and understand attacks as they unfold, not hours or days later. Four elements define its value:

1. Behavioral, real-time detection

The platform learns normal activity across cloud services, identities, workloads, and data flows, then surfaces anomalies that signify real attacker behavior, even when no signature exists.

2. Automated forensic level artifact collection

The moment Darktrace detects a threat, it can automatically capture volatile forensic evidence; disk state, memory, logs, and process context, including from ephemeral resources. This preserves the truth of what happened before workloads terminate and evidence disappears.

3. AI-led investigation

Cyber AI Analyst assembles cloud behaviors into a coherent incident story, correlating identity activity, network flows, and Cloud workload behavior. Analysts no longer need to pivot across dashboards or reconstruct timelines manually.

4. Live architectural awareness

Darktrace continuously maps your cloud environment as it operates; including services, identities, connectivity, and data pathways. This real-time visibility makes anomalies clearer and investigations dramatically faster.

Together, these capabilities form a runtime-first security model.

Why CNAPP alone isn’t enough

CNAPP platforms excel at pre deployment checks all the way down to developer workstations, identifying misconfigurations, concerning permission combinations, vulnerable images, and risky infrastructure choices. But CNAPP’s breadth is also its limitation. CNAPP is about posture. Runtime defense is about behavior.

CNAPP tells you what could go wrong; runtime detection highlights what is going wrong right now.

It cannot preserve ephemeral evidence, correlate active behaviors across domains, or contain unfolding attacks with the precision and speed required during a real incident. Prevention remains essential, but prevention alone cannot stop an attacker who is already operating inside your cloud environment.

Real-world AWS Scenario: Why Runtime Monitoring Wins

A recent incident detected by Darktrace / CLOUD highlights how cloud compromises unfold, and why runtime visibility is non-negotiable. Each step below reflects detections that occur only when monitoring behavior in real time.

1. External Credential Use

Detection: Unusual external source for credential use: An attacker logs into a cloud account from a never-before-seen location, the earliest sign of account takeover.

2. AWS CLI Pivot

Detection: Unusual CLI activity: The attacker switches to programmatic access, issuing commands from a suspicious host to gain automation and stealth.

3. Credential Manipulation

Detection: Rare password reset: They reset or assign new passwords to establish persistence and bypass existing security controls.

4. Cloud Reconnaissance

Detection: Burst of resource discovery: The attacker enumerates buckets, roles, and services to map high value assets and plan next steps.

5. Privilege Escalation

Detection: Anomalous IAM update: Unauthorized policy updates or role changes grant the attacker elevated access or a backdoor.

6. Malicious Compute Deployment

Detection: Unusual EC2/Lambda/ECS creation: The attacker deploys compute resources for mining, lateral movement, or staging further tools.

7. Data Access or Tampering

Detection: Unusual S3 modifications: They alter S3 permissions or objects, often a prelude to data exfiltration or corruption.

Only some of these actions would appear in a posture scan, crucially after the fact.
Every one of these runtime detections is visible only through real-time behavioral monitoring while the attack is in progress.

The future of cloud security Is runtime-first

Cloud defense can no longer revolve solely around prevention. Modern attacks unfold in runtime, across a fast-changing mesh of workloads, services, and — critically — identities. To reduce risk, organizations must be able to detect, understand, and contain malicious activity as it happens, before ephemeral evidence disappears and before attacker's pivot across identity layers.

Darktrace / CLOUD delivers this shift by turning runtime, the most volatile and consequential layer in the cloud, into a fully defensible control point through unified visibility across behavior, workloads, and identities. It does this by providing:

  • Real-time behavior detection across workloads and identity activity
  • Autonomous response actions for rapid containment
  • Automated forensic level artifact preservation the moment events occur
  • AI-driven investigation that separates weak signals from true attacker patterns
  • Live cloud environment insight to understand context and impact instantly

Cloud security must evolve from securing what might go wrong to continuously understanding what is happening; in runtime, across identities, and at the speed attackers operate. Unifying runtime and identity visibility is how defenders regain the advantage.

[related-resource]

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About the author
Adam Stevens
Senior Director of Product, Cloud | Darktrace

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January 12, 2026

Maduro Arrest Used as a Lure to Deliver Backdoor

maduro arrest used as lure to deliver backdoorDefault blog imageDefault blog image

Introduction

Threat actors frequently exploit ongoing world events to trick users into opening and executing malicious files. Darktrace security researchers recently identified a threat group using reports around the arrest of Venezuelan President Nicolàs Maduro on January 3, 2025, as a lure to deliver backdoor malware.

Technical Analysis

While the exact initial access method is unknown, it is likely that a spear-phishing email was sent to victims, containing a zip archive titled “US now deciding what’s next for Venezuela.zip”. This file included an executable named “Maduro to be taken to New York.exe” and a dynamic-link library (DLL), “kugou.dll”.  

The binary “Maduro to be taken to New York.exe” is a legitimate binary (albeit with an expired signature) related to KuGou, a Chinese streaming platform. Its function is to load the DLL “kugou.dll” via DLL search order. In this instance, the expected DLL has been replaced with a malicious one with the same name to load it.  

DLL called with LoadLibraryW.
Figure 1: DLL called with LoadLibraryW.

Once the DLL is executed, a directory is created C:\ProgramData\Technology360NB with the DLL copied into the directory along with the executable, renamed as “DataTechnology.exe”. A registry key is created for persistence in “HKCU\Software\Microsoft\Windows\CurrentVersion\Run\Lite360” to run DataTechnology.exe --DATA on log on.

 Registry key added for persistence.
Figure 2. Registry key added for persistence.
Folder “Technology360NB” created.
Figure 3: Folder “Technology360NB” created.

During execution, a dialog box appears with the caption “Please restart your computer and try again, or contact the original author.”

Message box prompting user to restart.
Figure 4. Message box prompting user to restart.

Prompting the user to restart triggers the malware to run from the registry key with the command --DATA, and if the user doesn't, a forced restart is triggered. Once the system is reset, the malware begins periodic TLS connections to the command-and-control (C2) server 172.81.60[.]97 on port 443. While the encrypted traffic prevents direct inspection of commands or data, the regular beaconing and response traffic strongly imply that the malware has the ability to poll a remote server for instructions, configuration, or tasking.

Conclusion

Threat groups have long used geopolitical issues and other high-profile events to make malicious content appear more credible or urgent. Since the onset of the war in Ukraine, organizations have been repeatedly targeted with spear-phishing emails using subject lines related to the ongoing conflict, including references to prisoners of war [1]. Similarly, the Chinese threat group Mustang Panda frequently uses this tactic to deploy backdoors, using lures related to the Ukrainian war, conventions on Tibet [2], the South China Sea [3], and Taiwan [4].  

The activity described in this blog shares similarities with previous Mustang Panda campaigns, including the use of a current-events archive, a directory created in ProgramData with a legitimate executable used to load a malicious DLL and run registry keys used for persistence. While there is an overlap of tactics, techniques and procedures (TTPs), there is insufficient information available to confidently attribute this activity to a specific threat group. Users should remain vigilant, especially when opening email attachments.

Credit to Tara Gould (Malware Research Lead)
Edited by Ryan Traill (Analyst Content Lead)

Indicators of Compromise (IoCs)

172.81.60[.]97
8f81ce8ca6cdbc7d7eb10f4da5f470c6 - US now deciding what's next for Venezuela.zip
722bcd4b14aac3395f8a073050b9a578 - Maduro to be taken to New York.exe
aea6f6edbbbb0ab0f22568dcb503d731  - kugou.dll

References

[1] https://cert.gov.ua/article/6280422  

[2] https://www.ibm.com/think/x-force/hive0154-mustang-panda-shifts-focus-tibetan-community-deploy-pubload-backdoor

[3] https://www.ibm.com/think/x-force/hive0154-targeting-us-philippines-pakistan-taiwan

[4] https://www.ibm.com/think/x-force/hive0154-targeting-us-philippines-pakistan-taiwan

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About the author
Tara Gould
Malware Research Lead
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