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April 8, 2025

Cloud Security Evolution: Why Security Teams are Taking the Lead

While many internal teams contribute to general cloud hygiene, the security team has increasingly taken the lead on cloud security. Learn how AI-powered cloud detection and response tools can help these teams with new responsibilities.
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
Pallavi Singh
Product Marketing Manager, OT Security & Compliance
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08
Apr 2025

Cloud adoption is rapidly on the rise. Gartner estimates that 90% of organizations will adopt hybrid clouds through 2027 [1].  

There are many reasons why organizations are migrating on-premises infrastructure to the cloud. It can increase the speed and scale of computing resources, improve reliability and resilience, and save time by outsourcing the spinning up, patching, and updating of infrastructure.  

However, despite these benefits, it is complex to secure. Public clouds operate with a shared responsibility model, meaning that while the Cloud Service Provider (CSP) maintains the physical infrastructure and services, customer organizations are responsible for their own security and compliance in their cloud deployments.  

This customer responsibility is crucial. Gartner forecasted that through 2025, 99% of cloud security failures would be the customer’s fault [2]. As cloud environments grow, security teams are taking on a greater share of the responsibility to protect these assets.

The many teams involved in cloud security

Several teams work across the cloud, and all of them can contribute to cloud security. For example, basic cyber-hygiene and Identity and Access Management (IAM) should be practiced across teams.  

Not every organization has the same categorization of teams, but some common ones include:

  • Security: assessing and mitigating vulnerabilities, risks, and threats. This team must be ready to identify, investigate, respond, and recover from incidents.
  • Infrastructure and ITOps: deploying and maintaining resources. Security must be considered across all layers of the cloud, including gateways, identity, encryption, and attack surface.
  • Research & development: building cloud-based applications. Security must be baked into code, referenced data, access, APIs, and third-party integrations.
  • DevOps: improving the software development process. Security must be applied to code across the development and production stages.
  • Compliance: adhering to industry standards and frameworks. Security often comes up in compliance regulations.  
  • End users: working in the cloud. Security must be taught through employee training sessions to adopt best practices and increase resistance against threats like phishing or data loss.

Traditionally, many organizations left cloud security to dedicated cloud teams. However, it is becoming more and more common for security teams to take on the responsibilities of securing the cloud. This is also true of organizations undergoing cloud migration and spinning up cloud infrastructure for the first time.

The complexity of cloud security

Most organizations using the cloud today have hybrid and/or multi-cloud deployments. Hybrid deployments combine public and private cloud environments and multi-cloud deployments use a combination of public cloud providers or regions where servers are stored. In fact, Deloitte reports that as many as 85% of businesses, a vast majority, use two or more cloud platforms, and 25% use at least five [3].

While these diverse deployments can boost resiliency, they also complicate security. Multiple environments increase the attack surface and reduce architectural visibility, making misconfigurations, unmanaged access, and inconsistent policies more likely. This complexity creates gaps in security that often require specialized teams and expert personnel to address.  

Challenges driving security teams’ responsibility

The usual approaches to other types of cybersecurity can’t be applied the exact same way to the cloud. With the inherent dynamism and flexibility of the cloud, the necessary security mindset differs greatly from those for networks or data centers, with which security teams may be more familiar.

For example, IAM is both critical and distinct to cloud computing, and the associated policies, rules, and downstream impacts require intentional care. IAM rules not only govern people, but also non-human entities like service accounts, API keys, and OAuth tokens. These considerations are unique to cloud security, and established teams may need to learn new skills to reduce security gaps in the cloud.

Additionally, there are greater compliance pressures from GDPR, CCPA, and industry-specific regulations. While some companies have dedicated compliance teams, not every organization does and others are not always familiar with working in cloud environments. In these cases, responsibilities may fall to the security team.  

Finally, there has been a rise in sophisticated, cloud-based threats, such as account takeovers and misconfigurations. Preparing, responding to, and recovering from these cloud-specific threats lie with the security team as well.  

Learn more about the top risks and attacks faced in the cloud in the white paper: “Tackling the 11 Biggest Cloud Threats with AI-Powered Defense.

Solutions empowering security teams

The leading role of security teams in cloud security can put a strain on existing resources as well as exacerbate skills gaps. In response, security teams can turn to AI-powered tools like Darktrace / CLOUD to provide real-time detection and response in cloud environments.  

Darktrace uses multi-layered AI to learn normal ‘patterns of life’ for all users, technologies, and resources across the organization, enabling it to recognize the subtlest anomalies that point to an emerging threat.  

The use of AI allows for automation that reduces manual workloads and saves teams time. The self-learning capabilities also help the human team detect subtle indicators that can be hard to spot amid the immense noise of legitimate, day-to-day digital interactions.

With these, Darktrace can respond to both known and novel threats, helping security teams keep pace with today’s sophisticated threats, even if team members feel less confident in cloud environments.  

Crucially, Darktrace / CLOUD can enable proactive risk management as well. Attack Path Modeling for the cloud identifies exposed assets and highlights internal attack paths to give a dynamic view of the riskiest paths across cloud environments, network environments, and between – enabling security teams to prioritize based on unique business risk and address gaps to prevent future attacks.  

Darktrace / CLOUD dynamically adjusts its focus based on evolving risks, analyzing misconfigurations, and anomalous activity to prevent potential attacks. Its Entitlement Enumeration capability helps security teams gain visibility into all identities, roles, and permissions, allowing dynamic adjustments to stop insider threats and lateral movement.

In these ways, the AI-powered Darktrace / CLOUD can support security teams as they take on the lion’s share of responsibility in securing the cloud, regardless of any resource limitations or skills gaps.

Conclusion

Cloud security is both vital under the shared responsibility model and complex with hybrid and multi-cloud deployments and strict regulatory demands. While many teams contribute to cloud security, more and more responsibilities are shifting to security teams specifically.

AI-powered solutions that can detect and respond to threats spanning a wide range of risks and attack types can support security teams as they protect dynamic cloud environments. By adopting real-time cloud detection and response tools, security teams have more time to dedicate to proactive projects and high-level tasks as well as reduced burden on less specialized team members.  

Discover how advanced AI solutions like Darktrace / CLOUD can address evolving cloud security needs in the solution brief.  

Read more about the latest trends in cloud security in the blog “Protecting Your Hybrid Cloud: The Future of Cloud Security in 2025 and Beyond.”

References:

1. Gartner, November 19, 2024, “Cloud End-User Spending to Total $723 Billion in 2025”  

2. Gartner, October 10, 2019, “Is the Cloud Secure?

3. Deloitte, December 6, 2022, “Above the clouds: Taming multicloud chaos”  

Protect Your Hybrid Cloud

Discover how advanced AI solutions like Darktrace / CLOUD can address evolving cloud security needs in this solution brief

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
Pallavi Singh
Product Marketing Manager, OT Security & Compliance

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January 13, 2026

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

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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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