July 8, 2025

Defending the Cloud: Stopping Cyber Threats in Azure and AWS with Darktrace

This blog examines three real-world cloud-based attacks in Azure and AWS environments, including credential compromise, data exfiltration, and ransomware detonation. Learn how Darktrace’s AI-driven threat detection and Autonomous Response capabilities help organizations defend against evolving threats in complex cloud environments.

Written by

Alexandra Sentenac

Cyber Analyst

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

Alexandra Sentenac

Cyber Analyst

Jul 2025

Real-world intrusions across Azure and AWS

As organizations pursue greater scalability and flexibility, cloud platforms like Microsoft Azure and Amazon Web Services (AWS) have become essential for enabling remote operations and digitalizing corporate environments. However, this shift introduces a new set of security risks, including expanding attack surfaces, misconfigurations, and compromised credentials frequently exploited by threat actors.

This blog dives into three instances of compromise within a Darktrace customer’s Azure and AWS environment which Darktrace.

The first incident took place in early 2024 and involved an attacker compromising a legitimate user account to gain unauthorized access to a customer’s Azure environment.
The other two incidents, taking place in February and March 2025, targeted AWS environments. In these cases, threat actors exfiltrated corporate data, and in one instance, was able to detonate ransomware in a customer’s environment.

Case 1 - Microsoft Azure

Figure 1: Simplified timeline of the attack on a customer’s Azure environment.

In early 2024, Darktrace identified a cloud compromise on the Azure cloud environment of a customer in the Europe, the Middle East and Africa (EMEA) region.

Initial access

In this case, a threat actor gained access to the customer’s cloud environment after stealing access tokens and creating a rogue virtual machine (VM). The malicious actor was found to have stolen access tokens belonging to a third-party external consultant’s account after downloading cracked software.

With these stolen tokens, the attacker was able to authenticate to the customer’s Azure environment and successfully modified a security rule to allow inbound SSH traffic from a specific IP range (i.e., securityRules/AllowCidrBlockSSHInbound). This was likely performed to ensure persistent access to internal cloud resources.

Detection and investigation of the threat

Darktrace / IDENTITY recognized that this activity was highly unusual, triggering the “Repeated Unusual SaaS Resource Creation” alert.

Cyber AI Analyst launched an autonomous investigation into additional suspicious cloud activities occurring around the same time from the same unusual location, correlating the individual events into a broader account hijack incident.

Figure 2: Cyber AI Analyst’s investigation into unusual cloud activity performed by the compromised account.

Figure 2: Surrounding resource creation events highlighted by Cyber AI Analyst. — Figure 3: Surrounding resource creation events highlighted by Cyber AI Analyst.

Figure 4: Surrounding resource creation events highlighted by Cyber AI Analyst.

“Create resource service limit” events typically indicate the creation or modification of service limits (i.e., quotas) for a specific Azure resource type within a region. Meanwhile, “Registers the Capacity Resource Provider” events refer to the registration of the Microsoft Capacity resource provider within an Azure subscription, responsible for managing capacity-related resources, particularly those related to reservations and service limits. These events suggest that the threat actor was looking to create new cloud resources within the environment.

Around ten minutes later, Darktrace detected the threat actor creating or modifying an Azure disk associated with a virtual machine (VM), suggesting an attempt to create a rogue VM within the environment.

Threat actors can leverage such rogue VMs to hijack computing resources (e.g., by running cryptomining malware), maintain persistent access, move laterally within the cloud environment, communicate with command-and-control (C2) infrastructure, and stealthily deliver and deploy malware.

Persistence

Several weeks later, the compromised account was observed sending an invitation to collaborate to an external free mail (Google Mail) address.

Darktrace deemed this activity as highly anomalous, triggering a compliance alert for the customer to review and investigate further.

The next day, the threat actor further registered new multi-factor authentication (MFA) information. These actions were likely intended to maintain access to the compromised user account. The customer later confirmed this activity by reviewing the corresponding event logs within Darktrace.

Case 2 – Amazon Web Services

Figure 5: Simplified timeline of the attack on a customer’s AWS environment

In February 2025, another cloud-based compromised was observed on a UK-based customer subscribed to Darktrace’s Managed Detection and Response (MDR) service.

How the attacker gained access

The threat actor was observed leveraging likely previously compromised credential to access several AWS instances within customer’s Private Cloud environment and collecting and exfiltrating data, likely with the intention of deploying ransomware and holding the data for ransom.

Darktrace alerting to malicious activity

This observed activity triggered a number of alerts in Darktrace, including several high-priority Enhanced Monitoring alerts, which were promptly investigated by Darktrace’s Security Operations Centre (SOC) and raised to the customer’s security team.

The earliest signs of attack observed by Darktrace involved the use of two likely compromised credentials to connect to the customer’s Virtual Private Network (VPN) environment.

Internal reconnaissance

Once inside, the threat actor performed internal reconnaissance activities and staged the Rclone tool “ProgramData\rclone-v1.69.0-windows-amd64.zip”, a command-line program to sync files and directories to and from different cloud storage providers, to an AWS instance whose hostname is associated with a public key infrastructure (PKI) service.

The threat actor was further observed accessing and downloading multiple files hosted on an AWS file server instance, notably finance and investment-related files. This likely represented data gathering prior to exfiltration.

Shortly after, the PKI-related EC2 instance started making SSH connections with the Rclone SSH client “SSH-2.0-rclone/v1.69.0” to a RockHoster Virtual Private Server (VPS) endpoint (193.242.184[.]178), suggesting the threat actor was exfiltrating the gathered data using the Rclone utility they had previously installed. The PKI instance continued to make repeated SSH connections attempts to transfer data to this external destination.

Darktrace’s Autonomous Response

In response to this activity, Darktrace’s Autonomous Response capability intervened, blocking unusual external connectivity to the C2 server via SSH, effectively stopping the exfiltration of data.

This activity was further investigated by Darktrace’s SOC analysts as part of the MDR service. The team elected to extend the autonomously applied actions to ensure the compromise remained contained until the customer could fully remediate the incident.

Continued reconissance

Around the same time, the threat actor continued to conduct network scans using the Nmap tool, operating from both a separate AWS domain controller instance and a newly joined device on the network. These actions were accompanied by further internal data gathering activities, with around 5 GB of data downloaded from an AWS file server.

The two devices involved in reconnaissance activities were investigated and actioned by Darktrace SOC analysts after additional Enhanced Monitoring alerts had triggered.

Lateral movement attempts via RDP connections

Unusual internal RDP connections to a likely AWS printer instance indicated that the threat actor was looking to strengthen their foothold within the environment and/or attempting to pivot to other devices, likely in response to being hindered by Autonomous Response actions.

This triggered multiple scanning, internal data transfer and unusual RDP alerts in Darktrace, as well as additional Autonomous Response actions to block the suspicious activity.

Suspicious outbound SSH communication to known threat infrastructure

Darktrace subsequently observed the AWS printer instance initiating SSH communication with a rare external endpoint associated with the web hosting and VPS provider Host Department (67.217.57[.]252), suggesting that the threat actor was attempting to exfiltrate data to an alternative endpoint after connections to the original destination had been blocked.

Further investigation using open-source intelligence (OSINT) revealed that this IP address had previously been observed in connection with SSH-based data exfiltration activity during an Akira ransomware intrusion [1].

Once again, connections to this IP were blocked by Darktrace’s Autonomous Response and subsequently these blocks were extended by Darktrace’s SOC team.

The above behavior generated multiple Enhanced Monitoring alerts that were investigated by Darktrace SOC analysts as part of the Managed Threat Detection service.

Figure 5: Enhanced Monitoring alerts investigated by SOC analysts as part of the Managed Detection and Response service.

Final containment and collaborative response

Upon investigating the unusual scanning activity, outbound SSH connections, and internal data transfers, Darktrace analysts extended the Autonomous Response actions previously triggered on the compromised devices.

As the threat actor was leveraging these systems for data exfiltration, all outgoing traffic from the affected devices was blocked for an additional 24 hours to provide the customer’s security team with time to investigate and remediate the compromise.

Additional investigative support was provided by Darktrace analysts through the Security Operations Service, after the customer's opened of a ticket related to the unfolding incident.

Figure 8: Simplified timeline of the attack

Around the same time of the compromise in Case 2, Darktrace observed a similar incident on the cloud environment of a different customer.

Initial access

On this occasion, the threat actor appeared to have gained entry into the AWS-based Virtual Private Cloud (VPC) network via a SonicWall SMA 500v EC2 instance allowing inbound traffic on any port.

The instance received HTTPS connections from three rare Vultr VPS endpoints (i.e., 45.32.205[.]52, 207.246.74[.]166, 45.32.90[.]176).

Lateral movement and exfiltration

Around the same time, the EC2 instance started scanning the environment and attempted to pivot to other internal systems via RDP, notably a DC EC2 instance, which also started scanning the network, and another EC2 instance.

The latter then proceeded to transfer more than 230 GB of data to the rare external GTHost VPS endpoint 23.150.248[.]189, while downloading hundreds of GBs of data over SMB from another EC2 instance.

Figure 7: Cyber AI Analyst incident generated following the unusual scanning and RDP connections from the initial compromised device.

The same behavior was replicated across multiple EC2 instances, whereby compromised instances uploaded data over internal RDP connections to other instances, which then started transferring data to the same GTHost VPS endpoint over port 5000, which is typically used for Universal Plug and Play (UPnP).

What Darktrace detected

Darktrace observed the threat actor uploading a total of 718 GB to the external endpoint, after which they detonated ransomware within the compromised VPC networks.

This activity generated nine Enhanced Monitoring alerts in Darktrace, focusing on the scanning and external data activity, with the earliest of those alerts triggering around one hour after the initial intrusion.

Darktrace’s Autonomous Response capability was not configured to act on these devices. Therefore, the malicious activity was not autonomously blocked and escalated to the point of ransomware detonation.

Conclusion

This blog examined three real-world compromises in customer cloud environments each illustrating different stages in the attack lifecycle.

The first case showcased a notable progression from a SaaS compromise to a full cloud intrusion, emphasizing the critical role of anomaly detection when legitimate credentials are abused.

The latter two incidents demonstrated that while early detection is vital, the ability to autonomously block malicious activity at machine speed is often the most effective way to contain threats before they escalate.

Together, these incidents underscore the need for continuous visibility, behavioral analysis, and machine-speed intervention across hybrid environments. Darktrace's AI-driven detection and Autonomous Response capabilities, combined with expert oversight from its Security Operations Center, give defenders the speed and clarity they need to contain threats and reduce operational disruption, before the situation spirals.

Credit to Alexandra Sentenac (Senior Cyber Analyst) and Dylan Evans (Security Research Lead)

References

[1] https://www.virustotal.com/gui/ip-address/67.217.57.252/community

Case 1

Darktrace / IDENTITY model alerts

IaaS / Compliance / Uncommon Azure External User Invite

SaaS / Resource / Repeated Unusual SaaS Resource Creation

IaaS / Compute / Azure Compute Resource Update

Cyber AI Analyst incidents

Possible Unsecured AzureActiveDirectory Resource

Possible Hijack of Office365 Account

Case 2

Darktrace / NETWORK model alerts

Compromise / SSH Beacon

Device / Multiple Lateral Movement Model Alerts

Device / Suspicious SMB Scanning Activity

Device / SMB Lateral Movement

Compliance / SSH to Rare External Destination

Device / Anomalous SMB Followed By Multiple Model Alerts

Device / Anonymous NTLM Logins

Anomalous Connection / SMB Enumeration

Device / New or Uncommon SMB Named Pipe Device / Network Scan

Device / Suspicious Network Scan Activity

Device / New Device with Attack Tools

Device / RDP Scan Device / Attack and Recon Tools

Compliance / High Priority Compliance Model Alert

Compliance / Outgoing NTLM Request from DC

Compromise / Large Number of Suspicious Successful Connections

Device / Large Number of Model Alerts

Anomalous Connection / Multiple Failed Connections to Rare Endpoint

Unusual Activity / Internal Data Transfer

Anomalous Connection / Unusual Internal Connections

Device / Anomalous RDP Followed By Multiple Model Alerts

Unusual Activity / Unusual External Activity

Unusual Activity / Enhanced Unusual External Data Transfer

Unusual Activity / Unusual External Data Transfer

Unusual Activity / Unusual External Data to New Endpoint

Anomalous Connection / Multiple Connections to New External TCP Port

Darktrace / Autonomous Response model alerts

Antigena / Network / Significant Anomaly / Antigena Enhanced Monitoring from Server Block

Antigena / Network / Manual / Quarantine Device

Antigena / MDR / MDR-Quarantined Device

Antigena / MDR / Model Alert on MDR-Actioned Device

Antigena / Network / Significant Anomaly / Antigena Enhanced Monitoring from Client Block

Antigena / Network / Significant Anomaly / Antigena Alerts Over Time Block

Antigena / Network / Insider Threat / Antigena Network Scan Block

Antigena / Network / Significant Anomaly / Antigena Significant Server Anomaly Block

Antigena / Network / Insider Threat / Antigena SMB Enumeration Block

Antigena / Network / Significant Anomaly / Antigena Controlled and Model Alert

Antigena / Network / Significant Anomaly / Antigena Significant Anomaly from Client Block

Antigena / Network / External Threat / Antigena Suspicious Activity Block

Antigena / Network / Insider Threat / Antigena Internal Data Transfer Block

Cyber AI Analyst incidents

Possible Application Layer Reconnaissance Activity

Scanning of Multiple Devices

Unusual Repeated Connections

Unusual External Data Transfer

Case 3

Darktrace / NETWORK model alerts

Unusual Activity / Unusual Large Internal Transfer

Compliance / Incoming Remote Desktop

Unusual Activity / High Volume Server Data Transfer

Unusual Activity / Internal Data Transfer

Anomalous Connection / Unusual Internal Remote Desktop

Anomalous Connection / Unusual Incoming Data Volume

Anomalous Server Activity / Domain Controller Initiated to Client

Device / Large Number of Model Alerts

Anomalous Connection / Possible Flow Device Brute Force

Device / RDP Scan

Device / Suspicious Network Scan Activity

Device / Network Scan

Anomalous Server Activity / Anomalous External Activity from Critical Network Device

Anomalous Connection / Download and Upload

Unusual Activity / Unusual External Data Transfer

Unusual Activity / High Volume Client Data Transfer

Unusual Activity / Unusual External Activity

Anomalous Connection / Uncommon 1 GiB Outbound

Device / Increased External Connectivity

Compromise / Large Number of Suspicious Successful Connections

Anomalous Connection / Data Sent to Rare Domain

Anomalous Connection / Low and Slow Exfiltration to IP

Unusual Activity / Enhanced Unusual External Data Transfer

Anomalous Connection / Multiple Connections to New External TCP Port

Anomalous Server Activity / Outgoing from Server

Anomalous Connection / Multiple Connections to New External UDP Port

Anomalous Connection / Possible Data Staging and External Upload

Unusual Activity / Unusual External Data to New Endpoint

Device / Large Number of Model Alerts from Critical Network Device

Compliance / External Windows Communications

Anomalous Connection / Unusual Internal Connections

Cyber AI Analyst incidents

Scanning of Multiple Devices

Extensive Unusual RDP Connections

MITRE ATT&CK mapping

(Technique name – Tactic ID)

Case 1

Defense Evasion - Modify Cloud Compute Infrastructure: Create Cloud Instance

Persistence – Account Manipulation

Case 2

Initial Access - External Remote Services

Execution - Inter-Process Communication

Persistence - External Remote Services

Discovery - System Network Connections Discovery

Discovery - Network Service Discovery

Discovery - Network Share Discovery

Lateral Movement - Remote Desktop Protocol

Lateral Movement - Remote Services: SMB/Windows Admin Shares

Collection - Data from Network Shared Drive

Command and Control - Protocol Tunneling

Exfiltration - Exfiltration Over Asymmetric Encrypted Non-C2 Protocol

Case 3

Initial Access - Exploit Public-Facing Application

Discovery - Remote System Discovery

Discovery - Network Service Discovery

Lateral Movement - Remote Services

Lateral Movement - Remote Desktop Protocol

Collection - Data from Network Shared Drive

Collection - Data Staged: Remote Data Staging

Exfiltration - Exfiltration Over C2 Channel

Command and Control - Non-Standard Port

Command and Control – Web Service

Impact - Data Encrypted for Impact

List of IoCs

IoC Type Description + Probability

193.242.184[.]178 - IP Address - Possible Exfiltration Server

45.32.205[.]52 - IP Address - Possible C2 Infrastructure

45.32.90[.]176 - IP Address - Possible C2 Infrastructure

207.246.74[.]166 - IP Address - Likely C2 Infrastructure

67.217.57[.]252 - IP Address - Likely C2 Infrastructure

23.150.248[.]189 - IP Address - Possible Exfiltration Server

Written by

Alexandra Sentenac

Cyber Analyst

Inside the SOC

Written by

Alexandra Sentenac

Cyber Analyst

Director of Product, Cloud Security

Watch the NIS2 Webinar

Blog

Network

August 8, 2025

Ivanti Under Siege: Investigating the Ivanti Endpoint Manager Mobile Vulnerabilities (CVE-2025-4427 & CVE-2025-4428)

ivanti cve exploitation edge infrastructure

Ivanti & Edge infrastructure exploitation

Edge infrastructure exploitations continue to prevail in today’s cyber threat landscape; therefore, it was no surprise that recent Ivanti Endpoint Manager Mobile (EPMM) vulnerabilities CVE-2025-4427 and CVE-2025-4428 were exploited targeting organizations in critical sectors such as healthcare, telecommunications, and finance across the globe, including across the Darktrace customer base in May 2025.

Exploiting these types of vulnerabilities remains a popular choice for threat actors seeking to enter an organization’s network to perform malicious activity such as cyber espionage, data exfiltration and ransomware detonation.

Vulnerabilities in Ivanti EPMM

Ivanti EPMM allows organizations to manage and configure enterprise mobile devices. On May 13, 2025, Ivanti published a security advisory [1] for their Ivanti Endpoint Manager Mobile (EPMM) devices addressing a medium and high severity vulnerability:

CVE-2025-4427, CVSS: 5.6: An authentication bypass vulnerability
CVE-2025-4428, CVSS: 7.2: Remote code execution vulnerability

Successfully exploiting both vulnerabilities at the same time could lead to unauthenticated remote code execution from an unauthenticated threat actor, which could allow them to control, manipulate, and compromise managed devices on a network [2].

Shortly after the disclosure of these vulnerabilities, external researchers uncovered evidence that they were being actively exploited in the wild and identified multiple indicators of compromise (IoCs) related to post-exploitation activities for these vulnerabilities [2] [3]. Research drew particular attention to the infrastructure utilized in ongoing exploitation activity, such as leveraging the two vulnerabilities to eventually deliver malware contained within ELF files from Amazon Web Services (AWS) S3 bucket endpoints and to deliver KrustyLoader malware for persistence. KrustyLoader is a Rust based malware that was discovered being downloaded in compromised Ivanti Connect Secure systems back in January 2024 when the zero-day critical vulnerabilities; CVE-2024-21887 and CVE-2023-46805 [10].

This suggests the involvement of the threat actor UNC5221, a suspected China-nexus espionage actor [3].

In addition to exploring the post-exploit tactics, techniques, and procedures (TTPs) observed for these vulnerabilities across Darktrace’s customer base, this blog will also examine the subtle changes and similarities in the exploitation of earlier Ivanti vulnerabilities—specifically Ivanti Connect Secure (CS) and Policy Secure (PS) vulnerabilities CVE-2023-46805 and CVE-2024-21887 in early 2024, as well as CVE-2025-0282 and CVE-2025-0283, which affected CS, PS, and Zero Trust Access (ZTA) in January 2025.

Darktrace Coverage

In May 2025, shortly after Ivanti disclosed vulnerabilities in their EPMM product, Darktrace’s Threat Research team identified attack patterns potentially linked to the exploitation of these vulnerabilities across multiple customer environments. The most noteworthy attack chain activity observed included exploit validation, payload delivery via AWS S3 bucket endpoints, subsequent delivery of script-based payloads, and connections to dpaste[.]com, possibly for dynamic payload retrieval. In a limited number of cases, connections were also made to an IP address associated with infrastructure linked to SAP NetWeaver vulnerability CVE-2025-31324, which has been investigated by Darktrace in an earlier case.

Exploit Validation

Darktrace observed devices within multiple customer environments making connections related to Out-of-Band Application Security Testing (OAST). These included a range of DNS requests and connections, most of which featured a user agent associated with the command-line tool cURL, directed toward associated endpoints. The hostnames of these endpoints consisted of a string of randomly generated characters followed by an OAST domain, such as 'oast[.]live', 'oast[.]pro', 'oast[.]fun', 'oast[.]site', 'oast[.]online', or 'oast[.]me'. OAST endpoints can be leveraged by malicious actors to trigger callbacks from targeted systems, such as for exploit validation. This activity, likely representing the initial phase of the attack chain observed across multiple environments, was also seen in the early stages of previous investigations into the exploitation of Ivanti vulnerabilities [4]. Darktrace also observed similar exploit validation activity during investigations conducted in January 2024 into the Ivanti CS vulnerabilities CVE-2023-46805 and CVE-2024-21887.

Payload Delivery via AWS

Devices across multiple customer environments were subsequently observed downloading malicious ELF files—often with randomly generated filenames such as 'NVGAoZDmEe'—from AWS S3 bucket endpoints like 's3[.]amazonaws[.]com'. These downloads occurred over HTTP connections, typically using wget or cURL user agents. Some of the ELF files were later identified to be KrustyLoader payloads using open-source intelligence (OSINT). External researchers have reported that the KrustyLoader malware is executed in cases of Ivanti EPMM exploitation to gain and maintain a foothold in target networks [2].

In one customer environment, after connections were made to the endpoint fconnect[.]s3[.]amazonaws[.]com, Darktrace observed the target system downloading the ELF file mnQDqysNrlg via the user agent Wget/1.14 (linux-gnu). Further investigation of the file’s SHA1 hash (1dec9191606f8fc86e4ae4fdf07f09822f8a94f2) linked it to the KrustyLoader malware [5]. In another customer environment, connections were instead made to tnegadge[.]s3[.]amazonaws[.]com using the same user agent, from which the ELF file “/dfuJ8t1uhG” was downloaded. This file was also linked to KrustyLoader through its SHA1 hash (c47abdb1651f9f6d96d34313872e68fb132f39f5) [6].

The pattern of activity observed so far closely mirrors previous exploits associated with the Ivanti vulnerabilities CVE-2023-46805 and CVE-2024-21887 [4]. As in those cases, Darktrace observed exploit validation using OAST domains and services, along with the use of AWS endpoints to deliver ELF file payloads. However, in this instance, the delivered payload was identified as KrustyLoader malware.

Later-stage script file payload delivery

In addition to the ELF file downloads, Darktrace also detected other file downloads across several customer environments, potentially representing the delivery of later-stage payloads.

The downloaded files included script files with the .sh extension, featuring randomly generated alphanumeric filenames. One such example is “4l4md4r.sh”, which was retrieved during a connection to the IP address 15.188.246[.]198 using a cURL-associated user agent. This IP address was also linked to infrastructure associated with the SAP NetWeaver remote code execution vulnerability CVE-2025-31324, which enables remote code execution on NetWeaver Visual Composer. External reporting has attributed this infrastructure to a China-nexus state actor [7][8][9].

In addition to the script file downloads, devices on some customer networks were also observed making connections to pastebin[.]com and dpaste[.]com, two sites commonly used to host or share malicious payloads or exploitation instructions [2]. Exploits, including those targeting Ivanti EPMM vulnerabilities, can dynamically fetch malicious commands from sites like dpaste[.]com, enabling threat actors to update payloads. Unlike the previously detailed activity, this behavior was not identified in any prior Darktrace investigations into Ivanti-related vulnerabilities, suggesting a potential shift in the tactics used in post-exploitation stages of Ivanti attacks.

Conclusion

Edge infrastructure vulnerabilities, such as those found in Ivanti EPMM and investigated across customer environments with Darktrace / NETWORK, have become a key tool in the arsenal of attackers in today’s threat landscape. As highlighted in this investigation, while many of the tactics employed by threat actors following successful exploitation of vulnerabilities remain the same, subtle shifts in their methods can also be seen.

These subtle and often overlooked changes enable threat actors to remain undetected within networks, highlighting the critical need for organizations to maintain continuous extended visibility, leverage anomaly based behavioral analysis, and deploy machine speed intervention across their environments.

Credit to Nahisha Nobregas (Senior Cyber Analyst) and Anna Gilbertson (Senior Cyber Analyst)

Appendices

Mid-High Confidence IoCs

(IoC – Type - Description)

- trkbucket.s3.amazonaws[.]com – Hostname – C2 endpoint

- trkbucket.s3.amazonaws[.]com/NVGAoZDmEe – URL – Payload

- tnegadge.s3.amazonaws[.]com – Hostname – C2 endpoint

- tnegadge.s3.amazonaws[.]com/dfuJ8t1uhG – URL – Payload

- c47abdb1651f9f6d96d34313872e68fb132f39f5 - SHA1 File Hash – Payload

- 4abfaeadcd5ab5f2c3acfac6454d1176 - MD5 File Hash - Payload

- fconnect.s3.amazonaws[.]com – Hostname – C2 endpoint

- fconnect.s3.amazonaws[.]com/mnQDqysNrlg – URL - Payload

- 15.188.246[.]198 – IP address – C2 endpoint

- 15.188.246[.]198/4l4md4r.sh?grep – URL – Payload

- 185.193.125[.]65 – IP address – C2 endpoint

- 185.193.125[.]65/c4qDsztEW6/TIGHT_UNIVERSITY – URL – C2 endpoint

- d8d6fe1a268374088fb6a5dc7e5cbb54 – MD5 File Hash – Payload

- 64.52.80[.]21 – IP address – C2 endpoint

- 0d8da2d1.digimg[.]store – Hostname – C2 endpoint

- 134.209.107[.]209 – IP address – C2 endpoint

Darktrace Model Detections

- Compromise / High Priority Tunnelling to Bin Services (Enhanced Monitoring Model)

- Compromise / Possible Tunnelling to Bin Services

- Anomalous Server Activity / New User Agent from Internet Facing System

- Compliance / Pastebin

- Device / Internet Facing Device with High Priority Alert

- Anomalous Connection / Callback on Web Facing Device

- Anomalous File / Script from Rare External Location

- Anomalous File / Incoming ELF File

- Device / Suspicious Domain

- Device / New User Agent

- Anomalous Connection / Multiple Connections to New External TCP Port

- Anomalous Connection / New User Agent to IP Without Hostname

- Anomalous File / EXE from Rare External Location

- Anomalous File / Internet Facing System File Download

- Anomalous File / Multiple EXE from Rare External Locations

- Compromise / Suspicious HTTP and Anomalous Activity

- Device / Attack and Recon Tools

- Device / Initial Attack Chain Activity

- Device / Large Number of Model Alerts

- Device / Large Number of Model Alerts from Critical Network Device

References

1. https://forums.ivanti.com/s/article/Security-Advisory-Ivanti-Endpoint-Manager-Mobile-EPMM?language=en_US

2. https://blog.eclecticiq.com/china-nexus-threat-actor-actively-exploiting-ivanti-endpoint-manager-mobile-cve-2025-4428-vulnerability

3. https://www.wiz.io/blog/ivanti-epmm-rce-vulnerability-chain-cve-2025-4427-cve-2025-4428

4. https://www.darktrace.com/blog/the-unknown-unknowns-post-exploitation-activities-of-ivanti-cs-ps-appliances

5. https://www.virustotal.com/gui/file/ac91c2c777c9e8638ec1628a199e396907fbb7dcf9c430ca712ec64a6f1fcbc9/community

6. https://www.virustotal.com/gui/file/f3e0147d359f217e2aa0a3060d166f12e68314da84a4ecb5cb205bd711c71998/community

7. https://www.virustotal.com/gui/ip-address/15.188.246.198

8. https://blog.eclecticiq.com/china-nexus-nation-state-actors-exploit-sap-netweaver-cve-2025-31324-to-target-critical-infrastructures

9. https://www.darktrace.com/blog/tracking-cve-2025-31324-darktraces-detection-of-sap-netweaver-exploitation-before-and-after-disclosure

10. https://www.synacktiv.com/en/publications/krustyloader-rust-malware-linked-to-ivanti-connectsecure-compromises

_{The content provided in this blog is published by Darktrace for general informational purposes only and reflects our understanding of cybersecurity topics, trends, incidents, and developments at the time of publication. While we strive to ensure accuracy and relevance, the information is provided “as is” without any representations or warranties, express or implied. Darktrace makes no guarantees regarding the completeness, accuracy, reliability, or timeliness of any information presented and expressly disclaims all warranties.}

_{Nothing in this blog constitutes legal, technical, or professional advice, and readers should consult qualified professionals before acting on any information contained herein.}

_{Any references to third-party organizations, technologies, threat actors, or incidents are for informational purposes only and do not imply affiliation, endorsement, or recommendation.}

_{Darktrace, its affiliates, employees, or agents shall not be held liable for any loss, damage, or harm arising from the use of or reliance on the information in this blog.}

_{The cybersecurity landscape evolves rapidly, and blog content may become outdated or superseded. We reserve the right to update, modify, or remove any content without notice.}

About the author

Nahisha Nobregas

SOC Analyst

Blog

Cloud

August 7, 2025

How CDR & Automated Forensics Transform Cloud Incident Response

cloud security investigation guy on computer doing work

Introduction: Cloud investigations

In cloud security, speed, automation and clarity are everything. However, for many SOC teams, responding to incidents in the cloud is often very difficult especially when attackers move fast, infrastructure is ephemeral, and forensic skills are scarce.

In this blog we will walk through an example that shows exactly how Darktrace Cloud Detection and Response (CDR) and automated cloud forensics together, solve these challenges, automating cloud detection, and deep forensic investigation in a way that’s fast, scalable, and deeply insightful.

The Problem: Cloud incidents are hard to investigate

Security teams often face three major hurdles when investigating cloud detections:

Lack of forensic expertise: Most SOCs and security teams aren’t natively staffed with forensics specialists.

Ephemeral infrastructure: Cloud assets spin up and down quickly, leaving little time to capture evidence.

Lack of existing automation: Gathering forensic-level data often requires manual effort and leaves teams scrambling around during incidents — accessing logs, snapshots, and system states before they disappear. This process is slow and often blocked by permissions, tooling gaps, or lack of visibility.

How Darktrace augments cloud investigations‍

1. Darktrace’s CDR finds anomalous activity in the cloud

An alert is generated for a large outbound data transfer from an externally facing EC2 instance to a rare external endpoint. It’s anomalous, unexpected, and potentially serious.

2. AI-led investigation stitches together the incident for a SOC analyst to look into

When a security incident unfolds, Darktrace’s Cyber AI Analyst ^TM is the first to surface it, automatically correlating behaviors, surfacing anomalies, and presenting a cohesive incident summary. It’s fast, detailed, and invaluable.

Once the incident is created, more questions are raised.

How were the impacted resources compromised?
How did the attack unfold over time – what tools and malware were used?
What data was accessed and exfiltrated?

What you’ll see as a SOC analyst: The incident begins in Darktrace’s Threat Visualizer, where a Cyber AI Analyst incident has been generated automatically highlighting large anomalous data transfer to a suspicious external IP. This isn’t just another alert, it’s a high-fidelity signal backed by Darktrace’s Self-Learning AI.

Figure 1: Cyber AI Analyst incident created for anomalous outbound data transfer

The analyst can then immediately pivot to Darktrace / CLOUD’s architecture view (see below), gaining context on the asset’s environment, ingress/egress points, connected systems, potential attack paths and whether there are any current misconfigurations detected on the asset.

Figure 2: Darktrace / CLOUD architecture view providing critical cloud context

3. Automated forensic capture — No expertise required

Then comes the game-changer, Darktrace’s recent acquisition of Cado enhances its cloud forensics capabilities. From the first alert triggered, Darktrace has already kicked in and automatically processed and analyzed a full volume capture of the EC2. Everything, past and present, is preserved. No need for manual snapshots, CLI commands, or specialist intervention.

Darktrace then provides a clear timeline highlighting the evidence and preserving it. In our example we identify:

A brute-force attempt on a file management app, followed by a successful login
A reverse shell used to gain unauthorized remote access to the EC2
A reverse TCP connection to the same suspicious IP flagged by Darktrace
Attacker commands showing how the data was split and prepared for exfiltration
A file (a.tar) created from two sensitive archives: product_plans.zip and research_data.zip

All of this is surfaced through the timeline view, ranked by significance using machine learning. The analyst can pivot through time, correlate events, and build a complete picture of the attack — without needing cloud forensics expertise.

Darktrace even gives the ability to:

Download and inspect gathered files in full detail, enabling teams to verify exactly what data was accessed or exfiltrated.
Interact with the file system as if it were live, allowing investigators to explore directories, uncover hidden artifacts, and understand attacker movement with precision.

Figure 3 Cado critical forensic investigation automated insights — Figure 3: Cado critical forensic investigation automated insights

Figure 4: Cado forensic file analysis of reverse shell and download option

Figure 5: a.tar created from two sensitive archives: product_plans.zip and research_data.zip

Figure 6: Traverse the full file system of the asset

Why this matters?

This workflow solves the hardest parts of cloud investigation:

Capturing evidence before it disappears
Understanding attacker behavior in detail - automatically
Linking detections to impact with full incident visibility

This kind of insight is invaluable for organizations especially regulated industries, where knowing exactly what data was affected is critical for compliance and reporting. It’s also a powerful tool for detecting insider threats, not just external attackers.

Darktrace / CLOUD and Cado together acts as a force multiplier helping with:

Reducing investigation time from hours to minutes
Preserving ephemeral evidence automatically
Empowering analysts with forensic-level visibility

Cloud threats aren’t slowing down. Your response shouldn’t either. Darktrace / CLOUD + Cado gives your SOC the tools to detect, contain, and investigate cloud incidents — automatically, accurately, and at scale.

[related-resource]

About the author

Adam Stevens

Director of Product, Cloud Security

Your data. Our AI.

Elevate your network security with Darktrace AI

Get a demo

Check out this article by Darktrace: Stopping cloud threats in Azure and AWS with Darktrace

Defending the Cloud: Stopping Cyber Threats in Azure and AWS with Darktrace

Real-world intrusions across Azure and AWS

Case 1 - Microsoft Azure

Initial access

Detection and investigation of the threat

Persistence

Case 2 – Amazon Web Services

How the attacker gained access

Darktrace alerting to malicious activity

Internal reconnaissance

Darktrace’s Autonomous Response

Continued reconissance

Lateral movement attempts via RDP connections

Suspicious outbound SSH communication to known threat infrastructure

Final containment and collaborative response

Initial access

Lateral movement and exfiltration

What Darktrace detected

Conclusion

References

Case 1

Darktrace / IDENTITY model alerts

Cyber AI Analyst incidents

Case 2

Darktrace / NETWORK model alerts

Cyber AI Analyst incidents

Case 3

Darktrace / NETWORK model alerts

MITRE ATT&CK mapping

Case 1

Case 2

Case 3

List of IoCs

Ivanti Under Siege: Investigating the Ivanti Endpoint Manager Mobile Vulnerabilities (CVE-2025-4427 & CVE-2025-4428)

How CDR & Automated Forensics Transform Cloud Incident Response

Enjoying the blog?

More in this series

Top Eight Threats to SaaS Security and How to Combat Them

From Rockstar2FA to FlowerStorm: Investigating a Blooming Phishing-as-a-Service Platform

MFA Under Attack: AiTM Phishing Kits Abusing Legitimate Services

Blog

Network

August 8, 2025

Ivanti Under Siege: Investigating the Ivanti Endpoint Manager Mobile Vulnerabilities (CVE-2025-4427 & CVE-2025-4428)

Ivanti & Edge infrastructure exploitation

Vulnerabilities in Ivanti EPMM

Darktrace Coverage

Exploit Validation

Payload Delivery via AWS

Later-stage script file payload delivery

Conclusion

Appendices

Blog

Cloud

August 7, 2025

How CDR & Automated Forensics Transform Cloud Incident Response

Introduction: Cloud investigations

The Problem: Cloud incidents are hard to investigate

How Darktrace augments cloud investigations‍

1. Darktrace’s CDR finds anomalous activity in the cloud

2. AI-led investigation stitches together the incident for a SOC analyst to look into

3. Automated forensic capture — No expertise required

Why this matters?