Blog
/
/
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
person on computer cybersecurityDefault blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog image
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

More in this series

No items found.

Blog

/

/

March 5, 2026

Inside Cloud Compromise: Investigating Attacker Activity with Darktrace / Forensic Acquisition & Investigation

Forensic Acquisition and investigationDefault blog imageDefault blog image

Investigating cloud attacks with Darktrace/ Forensic Acquisition & Investigation

Darktrace / Forensic Acquisition & Investigation™ is the industry’s first truly automated forensic solution purpose-built for the cloud. This blog will demonstrate how an investigation can be carried out against a compromised cloud server in minutes, rather than hours or days.

The compromised server investigated in this case originates from Darktrace’s Cloudypots system, a global honeypot network designed to observe adversary activity in real time across a wide range of cloud services. Whenever an attacker successfully compromises one of these honeypots, a forensic copy of the virtual server's disk is preserved for later analysis. Using Forensic Acquisition & Investigation, analysts can then investigate further and obtain detailed insights into the compromise including complete attacker timelines and root cause analysis.

Forensic Acquisition & Investigation supports importing artifacts from a variety of sources, including EC2 instances, ECS, S3 buckets, and more. The Cloudypots system produces a raw disk image whenever an attack is detected and stores it in an S3 bucket. This allows the image to be directly imported into Forensic Acquisition & Investigation using the S3 bucket import option.

As Forensic Acquisition & Investigation runs cloud-natively, no additional configuration is required to add a specific S3 bucket. Analysts can browse and acquire forensic assets from any bucket that the configured IAM role is permitted to access. Operators can also add additional IAM credentials, including those from other cloud providers, to extend access across multiple cloud accounts and environments.

Figure 1: Forensic Acquisition & Investigation import screen.

Forensic Acquisition & Investigation then retrieves a copy of the file and automatically begins running the analysis pipeline on the artifact. This pipeline performs a full forensic analysis of the disk and builds a timeline of the activity that took place on the compromised asset. By leveraging Forensic Acquisition & Investigation’s cloud-native analysis system, this process condenses hour of manual work into just minutes.

Successful import of a forensic artifact and initiation of the analysis pipeline.
Figure 2: Successful import of a forensic artifact and initiation of the analysis pipeline.

Once processing is complete, the preserved artifact is visible in the Evidence tab, along with a summary of key information obtained during analysis, such as the compromised asset’s hostname, operating system, cloud provider, and key event count.

The Evidence overview showing the acquired disk image.
Figure 3: The Evidence overview showing the acquired disk image.

Clicking on the “Key events” field in the listing opens the timeline view, automatically filtered to show system- generated alarms.

The timeline provides a chronological record of every event that occurred on the system, derived from multiple sources, including:

  • Parsed log files such as the systemd journal, audit logs, application specific logs, and others.
  • Parsed history files such as .bash_history, allowing executed commands to be shown on the timeline.
  • File-specific events, such as files being created, accessed, modified, or executables being run, etc.

This approach allows timestamped information and events from multiple sources to be aggregated and parsed into a single, concise view, greatly simplifying the data review process.

Alarms are created for specific timeline events that match either a built-in system rule, curated by Darktrace’s Threat Research team or an operator-defined rule  created at the project level. These alarms help quickly filter out noise and highlight on events of interest, such as the creation of a file containing known malware, access to sensitive files like Amazon Web Service (AWS) credentials, suspicious arguments or commands, and more.

 The timeline view filtered to alarm_severity: “1” OR alarm_severity: “3”, showing only events that matched an alarm rule.
Figure 4: The timeline view filtered to alarm_severity: “1” OR alarm_severity: “3”, showing only events that matched an alarm rule.

In this case, several alarms were generated for suspicious Base64 arguments being passed to Selenium. Examining the event data, it appears the attacker spawned a Selenium Grid session with the following payload:

"request.payload": "[Capabilities {browserName: chrome, goog:chromeOptions: {args: [-cimport base64;exec(base64...], binary: /usr/bin/python3, extensions: []}, pageLoadStrategy: normal}]"

This is a common attack vector for Selenium Grid. The chromeOptions object is intended to specify arguments for how Google Chrome should be launched; however, in this case the attacker has abused the binary field to execute the Python3 binary instead of Chrome. Combined with the option to specify command-line arguments, the attacker can use Python3’s -c option to execute arbitrary Python code, in this instance, decoding and executing a Base64 payload.

Selenium’s logs truncate the Arguments field automatically, so an alternate method is required to retrieve the full payload. To do this, the search bar can be used to find all events that occurred around the same time as this flagged event.

Pivoting off the previous event by filtering the timeline to events within the same window using timestamp: [“2026-02-18T09:09:00Z” TO “2026-02-18T09:12:00Z”].
Figure 5: Pivoting off the previous event by filtering the timeline to events within the same window using timestamp: [“2026-02-18T09:09:00Z” TO “2026-02-18T09:12:00Z”].

Scrolling through the search results, an entry from Java’s systemd journal can be identified. This log contains the full, unaltered payload. GCHQ’s CyberChef can then be used to decode the Base64 data into the attacker’s script, which will ultimately be executed.

Decoding the attacker’s payload in CyberChef.
Figure 6: Decoding the attacker’s payload in CyberChef.

In this instance, the malware was identified as a variant of a campaign that has been previously documented in depth by Darktrace.

Investigating Perfctl Malware

This campaign deploys a malware sample known as ‘perfctl to the compromised host. The script executed by the attacker downloads a Go binary named “promocioni.php” from 200[.]4.115.1. Its functionality is consistent with previously documented perfctl samples, with only minor changes such as updated filenames and a new command-and-control (C2) domain.

Perfctl is a stealthy malware that has several systems designed  to evade detection. The main binary is packed with UPX, with the header intentionally tampered with to prevent unpacking using regular tools. The binary also avoids executing any malicious code if it detects debugging or tracing activity, or if artifacts left by earlier stages are missing.

To further aid its evasive capabilities, perfctl features a usermode rootkit using an LD preload. This causes dynamically linked executables to load perfctl’s rootkit payload before other system modules, allowing it to override functions, such as intercepting calls to list files and hiding output from the returned list. Perfctl uses this to hide its own files, as well as other files like the ld.so.preload file, preventing users from identifying that a rootkit is present in the first place.

This also makes it difficult to dynamically analyze, as even analysts aware of the rootkit will struggle to get around it due to its aggressiveness in hiding its components. A useful trick is to use the busybox-static utilities, which are statically linked and therefore immune to LD preloading.

Perfctl will attempt to use sudo to escalate its permissions to root if the user it was executed as has the required privileges. Failing this, it will attempt to exploit the vulnerability CVE-2021-4034.

Ultimately, perfctl will attempt to establish a C2 link via Tor and spawn an XMRig miner to mine the Monero cryptocurrency. The traffic to the mining pool is encapsulated within Tor to limit network detection of the mining traffic.

Darktrace’s Cloudypots system has observed 1,959 infections of the perfctl campaign across its honeypot network in the past year, making it one of the most aggressive campaigns seen by Darktrace.

Key takeaways

This blog has shown how Darktrace / Forensic Acquisition & Investigation equips defenders in the face of a real-world attacker campaign. By using this solution, organizations can acquire forensic evidence and investigate intrusions across multiple cloud resources and providers, enabling defenders to see the full picture of an intrusion on day one. Forensic Acquisition & Investigation’s patented data-processing system takes advantage of the cloud’s scale to rapidly process large amounts of data, allowing triage to take minutes, not hours.

Darktrace / Forensic Acquisition & Investigation is available as Software-as-a-Service (SaaS) but can also be deployed on-premises as a virtual application or natively in the cloud, providing flexibility between convenience and data sovereignty to suit any use case.

Support for acquiring traditional compute instances like EC2, as well as more exotic and newly targeted platforms such as ECS and Lambda, ensures that attacks taking advantage of Living-off-the-Cloud (LOTC) strategies can be triaged quickly and easily as part of incident response. As attackers continue to develop new techniques, the ability to investigate how they use cloud services to persist and pivot throughout an environment is just as important to triage as a single compromised EC2 instance.

Credit to Nathaniel Bill (Malware Research Engineer)

Continue reading
About the author
Nathaniel Bill
Malware Research Engineer

Blog

/

Network

/

February 19, 2026

CVE-2026-1731: How Darktrace Sees the BeyondTrust Exploitation Wave Unfolding

Default blog imageDefault blog image

Note: Darktrace's Threat Research team is publishing now to help defenders. We will continue updating this blog as our investigations unfold.

Background

On February 6, 2026, the Identity & Access Management solution BeyondTrust announced patches for a vulnerability, CVE-2026-1731, which enables unauthenticated remote code execution using specially crafted requests.  This vulnerability affects BeyondTrust Remote Support (RS) and particular older versions of Privileged Remote Access (PRA) [1].

A Proof of Concept (PoC) exploit for this vulnerability was released publicly on February 10, and open-source intelligence (OSINT) reported exploitation attempts within 24 hours [2].

Previous intrusions against Beyond Trust technology have been cited as being affiliated with nation-state attacks, including a 2024 breach targeting the U.S. Treasury Department. This incident led to subsequent emergency directives from  the Cybersecurity and Infrastructure Security Agency (CISA) and later showed attackers had chained previously unknown vulnerabilities to achieve their goals [3].

Additionally, there appears to be infrastructure overlap with React2Shell mass exploitation previously observed by Darktrace, with command-and-control (C2) domain  avg.domaininfo[.]top seen in potential post-exploitation activity for BeyondTrust, as well as in a React2Shell exploitation case involving possible EtherRAT deployment.

Darktrace Detections

Darktrace’s Threat Research team has identified highly anomalous activity across several customers that may relate to exploitation of BeyondTrust since February 10, 2026. Observed activities include:

Outbound connections and DNS requests for endpoints associated with Out-of-Band Application Security Testing; these services are commonly abused by threat actors for exploit validation.  Associated Darktrace models include:

  • Compromise / Possible Tunnelling to Bin Services

Suspicious executable file downloads. Associated Darktrace models include:

  • Anomalous File / EXE from Rare External Location

Outbound beaconing to rare domains. Associated Darktrace models include:

  • Compromise / Agent Beacon (Medium Period)
  • Compromise / Agent Beacon (Long Period)
  • Compromise / Sustained TCP Beaconing Activity To Rare Endpoint
  • Compromise / Beacon to Young Endpoint
  • Anomalous Server Activity / Rare External from Server
  • Compromise / SSL Beaconing to Rare Destination

Unusual cryptocurrency mining activity. Associated Darktrace models include:

  • Compromise / Monero Mining
  • Compromise / High Priority Crypto Currency Mining

And model alerts for:

  • Compromise / Rare Domain Pointing to Internal IP

IT Defenders: As part of best practices, we highly recommend employing an automated containment solution in your environment. For Darktrace customers, please ensure that Autonomous Response is configured correctly. More guidance regarding this activity and suggested actions can be found in the Darktrace Customer Portal.  

Appendices

Potential indicators of post-exploitation behavior:

·      217.76.57[.]78 – IP address - Likely C2 server

·      hXXp://217.76.57[.]78:8009/index.js - URL -  Likely payload

·      b6a15e1f2f3e1f651a5ad4a18ce39d411d385ac7  - SHA1 - Likely payload

·      195.154.119[.]194 – IP address – Likely C2 server

·      hXXp://195.154.119[.]194/index.js - URL – Likely payload

·      avg.domaininfo[.]top – Hostname – Likely C2 server

·      104.234.174[.]5 – IP address - Possible C2 server

·      35da45aeca4701764eb49185b11ef23432f7162a – SHA1 – Possible payload

·      hXXp://134.122.13[.]34:8979/c - URL – Possible payload

·      134.122.13[.]34 – IP address – Possible C2 server

·      28df16894a6732919c650cc5a3de94e434a81d80 - SHA1 - Possible payload

References:

1.        https://nvd.nist.gov/vuln/detail/CVE-2026-1731

2.        https://www.securityweek.com/beyondtrust-vulnerability-targeted-by-hackers-within-24-hours-of-poc-release/

3.        https://www.rapid7.com/blog/post/etr-cve-2026-1731-critical-unauthenticated-remote-code-execution-rce-beyondtrust-remote-support-rs-privileged-remote-access-pra/

Continue reading
About the author
Emma Foulger
Global Threat Research Operations Lead
Your data. Our AI.
Elevate your network security with Darktrace AI