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January 13, 2025

Agent vs. Agentless Cloud Security: Why Deployment Methods Matter

Cloud security solutions can be deployed with agentless or agent-based approaches or use a combination of methods. Organizations must weigh which method applies best to the assets and data the tool will protect.
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
Kellie Regan
Director, Product Marketing - Cloud Security
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13
Jan 2025

The rapid adoption of cloud technologies has brought significant security challenges for organizations of all sizes. According to recent studies, over 70% of enterprises now operate in hybrid or multi-cloud environments, with 93% employing a multi-cloud strategy[1]. This complexity requires robust security tools, but opinions vary on the best deployment method—agent-based, agentless, or a combination of both.

Agent-based and agentless cloud security approaches offer distinct benefits and limitations, and organizations often make deployment choices based on their unique needs depending on the function of the specific assets covered, the types of data stored, and cloud architecture, such as hybrid or multi-cloud deployments.

For example, agentless solutions are increasingly favored for their ease of deployment and ability to provide broad visibility across dynamic cloud environments. These are especially useful for DevOps teams, with 64% of organizations citing faster deployment as a key reason for adopting agentless tools[2].

On the other hand, agent-based solutions remain the preferred choice for environments requiring deep monitoring and granular control, such as securing sensitive high-value workloads in industries like finance and healthcare. In fact, over 50% of enterprises with critical infrastructure report relying on agent-based solutions for their advanced protection capabilities[3].

As the debate continues, many organizations are turning to combined approaches, leveraging the strengths of both agent-based and agentless tools to address the full spectrum of their security needs for comprehensive coverage. Understanding the capabilities and limitations of these methods is critical to building an effective cloud security strategy that adapts to evolving threats and complex infrastructures.

Agent-based cloud security

Agent-based security solutions involve deploying software agents on each device or system that needs protection. Agent-based solutions are great choices when you need in-depth monitoring and protection capabilities. They are ideal for organizations that require deep security controls and real-time active response, particularly in hybrid and on-premises environments.

Key advantages include:

1. Real-time monitoring and protection: Agents detect and block threats like malware, ransomware, and anomalous behaviors in real time, providing ongoing protection and enforcing compliance by continuously monitoring workload activities.  Agents enable full control over workloads for active response such as blocking IP addresses, killing processes, disabling accounts, and isolating infected systems from the network, stopping lateral movement.

2. Deep visibility for hybrid environments: Agent-based approaches allow for full visibility across on-premises, hybrid, and multi-cloud environments by deploying agents on physical and virtual machines. Agents offer detailed insights into system behavior, including processes, files, memory, network connections, and more, detecting subtle anomalies that might indicate security threats. Host-based monitoring tracks vulnerabilities at the system and application level, including unpatched software, rogue processes, and unauthorized network activity.

3. Comprehensive coverage: Agents are very effective in hybrid environments (cloud and on-premises), as they can be installed on both physical and virtual machines.  Agents can function independently on each host device onto which they are installed, which is especially helpful for endpoints that may operate outside of constant network connectivity.

Challenges:

1. Resource-intensive: Agents can consume CPU, memory, and network resources, which may affect performance, especially in environments with large numbers of workloads or ephemeral resources.

2. Challenging in dynamic environments: Managing hundreds or thousands of agents in highly dynamic or ephemeral environments (e.g., containers, serverless functions) can be complex and labor-intensive.

3. Slower deployment: Requires agent installation on each workload or instance, which can be time-consuming, particularly in large or complex environments.  

Agentless cloud security

Agentless security does not require software agents to be installed on each device. Instead, it uses cloud infrastructure and APIs to perform security checks. Agentless solutions are highly scalable with minimal impact on performance, and ideal for cloud-native and highly dynamic environments like serverless and containerized. These solutions are great choices for your cloud-native and multi-cloud environments where rapid deployment, scalability, and minimal impact on performance are critical, but response actions can be handled through external tools or manual processes.

Key advantages include:

1. Scalability and ease of deployment: Because agentless security doesn’t require installation on each individual device, it is much easier to deploy and can quickly scale across a vast number of cloud assets. This approach is ideal for environments where resources are frequently created and destroyed (e.g., serverless, containerized workloads), as there is no need for agent installation or maintenance.

2. Reduced system overhead: Without the need to run local agents, agentless security minimizes the impact on system performance. This is crucial in high-performance environments.

3. Broad visibility: Agentless security connects via API to cloud service providers, offering near-instant visibility and threat detection. It provides a comprehensive view of your cloud environment, making it easier to manage and secure large and complex infrastructures.

Challenges

1. Infrastructure-level monitoring: Agentless solutions rely on cloud service provider logs and API calls, meaning that detection might not be as immediate as agent-based solutions. They collect configuration data and logs, focusing on infrastructure misconfigurations, identity risks, exposed resources, and network traffic, but lack visibility and access to detailed, system-level information such as running processes and host-level vulnerabilities.

2. Cloud-focused: Primarily for cloud environments, although some tools may integrate with on-premises systems through API-based data gathering. For organizations with hybrid cloud environments, this approach fragments visibility and security, leading to blind spots and increasing security risk.

3. Passive remediation: Typically provides alerts and recommendations, but lacks deep control over workloads, requiring manual intervention or orchestration tools (e.g., SOAR platforms) to execute responses. Some agentless tools trigger automated responses via cloud provider APIs (e.g., revoking permissions, adjusting security groups), but with limited scope.

Combined agent-based and agentless approaches

A combined approach leverages the strengths of both agent-based and agentless security for complete coverage. This hybrid strategy helps security teams achieve comprehensive coverage by:

  • Using agent-based solutions for deep, real-time protection and detailed monitoring of critical systems or sensitive workloads.
  • Employing agentless solutions for fast deployment, broader visibility, and easier scalability across all cloud assets, which is particularly useful in dynamic cloud environments where workloads frequently change.

The combined approach has distinct practical applications. For example, imagine a financial services company that deals with sensitive transactions. Its security team might use agent-based security for critical databases to ensure stringent protections are in place. Meanwhile, agentless solutions could be ideal for less critical, transient workloads in the cloud, where rapid scalability and minimal performance impact are priorities. With different data types and infrastructures, the combined approach is best.

Best of both worlds: The benefits of a combined approach

The combined approach not only maximizes security efficacy but also aligns with diverse operational needs. This means that all parts of the cloud environment are secured according to their risk profile and functional requirements. Agent-based deployment provides in-depth monitoring and active protection against threats, suitable for environments requiring tight security controls, such as financial services or healthcare data processing systems. Agentless deployment complements agents by offering broader visibility and easier scalability across diverse and dynamic cloud environments, ideal for rapidly changing cloud resources.

There are three major benefits from combining agent-based and agentless approaches.

1. Building a holistic security posture: By integrating both agent-based and agentless technologies, organizations can ensure that all parts of their cloud environments are covered—from persistent, high-risk endpoints to transient cloud resources. This comprehensive coverage is crucial for detecting and responding to threats promptly and effectively.

2. Reducing overhead while boosting scalability: Agentless systems require no software installation on each device, reducing overhead and eliminating the need to update and maintain agents on a large number of endpoints. This makes it easier to scale security as the organization grows or as the cloud environment changes.

3. Applying targeted protection where needed: Agent-based solutions can be deployed on selected assets that handle sensitive information or are critical to business operations, thus providing focused protection without incurring the costs and complexity of universal deployment.

Use cases for a combined approach

A combined approach gives security teams the flexibility to deploy agent-based and agentless solutions based on the specific security requirements of different assets and environments. As a result, organizations can optimize their security expenditures and operational efforts, allowing for greater adaptability in cloud security use cases.

Let’s take a look at how this could practically play out. In the combined approach, agent-based security can perform the following:

1. Deep monitoring and real-time protection:

  • Workload threat detection: Agent-based solutions monitor individual workloads for suspicious activity, such as unauthorized file changes or unusual resource usage, providing high granularity for detecting threats within critical cloud applications.
  • Behavioral analysis of applications: By deploying agents on virtual machines or containers, organizations can monitor behavior patterns and flag anomalies indicative of insider threats, lateral movement, or Advanced Persistent Threats (APTs).
  • Protecting high-sensitivity environments: Agents provide continuous monitoring and advanced threat protection for environments processing sensitive data, such as payment processing systems or healthcare records, leveraging capabilities like memory protection and file integrity monitoring.

2. Cloud asset protection:

  • Securing critical infrastructure: Agent-based deployments are ideal for assets like databases or storage systems that require real-time defense against exploits and ransomware.
  • Advanced packet inspection: For high-value assets, agents offer deep packet inspection and in-depth logging to detect stealthy attacks such as data exfiltration.
  • Customizable threat response: Agents allow for tailored security rules and automated responses at the workload level, such as shutting down compromised instances or quarantining infected files.

At the same time, agentless cloud security provides complementary benefits such as:

1. Broad visibility and compliance:

  • Asset discovery and management: Agentless systems can quickly scan the entire cloud environment to identify and inventory all assets, a crucial capability for maintaining compliance with regulations like GDPR or HIPAA, which require up-to-date records of data locations and usage.
  • Regulatory compliance auditing and configuration management: Quickly identify gaps in compliance frameworks like PCI DSS or SOC 2 by scanning configurations, permissions, and audit trails without installing agents. Using APIs to check configurations across cloud services ensures that all instances comply with organizational and regulatory standards, an essential aspect for maintaining security hygiene and compliance.
  • Shadow IT Detection: Detect and map unauthorized cloud services or assets that are spun up without security oversight, ensuring full inventory coverage.

2. Rapid environmental assessment:

  • Vulnerability assessment of new deployments: In environments where new code is frequently deployed, agentless security can quickly assess new instances, containers, or workloads in CI/CD pipelines for vulnerabilities and misconfigurations, enabling secure deployments at DevOps speed.
  • Misconfiguration alerts: Detect and alert on common cloud configuration issues, such as exposed storage buckets or overly permissive IAM roles, across cloud providers like AWS, Azure, and GCP.
  • Policy enforcement: Validate that new resources adhere to established security baselines and organizational policies, preventing security drift during rapid cloud scaling.

Combining agent-based and agentless approaches in cloud security not only maximizes the protective capabilities, but also offers flexibility, efficiency, and comprehensive coverage tailored to the diverse and evolving needs of modern cloud environments. This integrated strategy ensures that organizations can protect their assets more effectively while also adapting quickly to new threats and regulatory requirements.

Darktrace offers complementary and flexible deployment options for holistic cloud security

Powered by multilayered AI, Darktrace / CLOUD is a Cloud Detection and Response (CDR) solution that is agentless by default, with optional lightweight, host-based server agents for enhanced real-time actioning and deep inspection. As such, it can deploy in cloud environments in minutes and provide unified visibility and security across hybrid, multi-cloud environments.

With any deployment method, Darktrace supports multi-tenant, hybrid, and serverless cloud environments. Its Self-Learning AI learns the normal behavior across architectures, assets, and users to identify unusual activity that may indicate a threat. With this approach, Darktrace / CLOUD quickly disarms threats, whether they are known, unknown, or completely novel. It then accelerates the investigation process and responds to threats at machine speed.

Learn more about how Darktrace / CLOUD secures multi and hybrid cloud environments in the Solution Brief.

References:

1. Flexera 2023 State of the Cloud Report

2. ESG Research 2023 Report on Cloud-Native Security

3. Gartner, Market Guide for Cloud Workload Protection Platforms, 2023

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
Kellie Regan
Director, Product Marketing - Cloud Security

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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

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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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