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February 20, 2020

Lessons Learned from a Sodinokibi Ransomware Attack

Gain insights into a targeted Sodinokibi ransomware attack and learn how to better prepare your organization for potential cyber threats.
Inside the SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Written by
Max Heinemeyer
Global Field CISO
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20
Feb 2020

Introduction

Last week, Darktrace detected a targeted Sodinokibi ransomware attack during a 4-week trial with a mid-sized company.

This blog post will go through every stage of the attack lifecycle and detail the attacker’s techniques, tools and procedures used, and how Darktrace detected the attack.

The Sodinokibi group is an innovative threat-actor that is sometimes referred to as a ‘double-threat’, due to their ability to run targeted attacks using ransomware while simultaneously exfiltrating their victim’s data. This enables them to threaten to make the victim’s data publicly available if the ransom is not paid.

While Darktrace’s AI was able to identify the attack in real time as it was emerging, unfortunately the security team didn’t have eyes on the technology and was unable to action the alerts — nor was Antigena set in active mode, which would have slowed down and contained the threat instantaneously.

Timeline

The timeline below provides a rough overview of the major attack phases. Most of the attack took place over the course of a week, with the majority of activity distributed over the last three days.

Technical analysis

Darktrace detected two main devices being hit by the attack: an internet-facing RDP server (‘RDP server’) and a Domain Controller (‘DC’), that also acts as a SMB file server.

In previous attacks, Sodinokibi has used host-level encryption for ransomware activity where the encryption takes place on the compromised host itself — in contrast to network-level encryption where the bulk of the ransomware activity takes place over network protocols such as SMB.

Initial compromise

Over several days, the victim’s external-facing RDP server was receiving successful RDP connections from a rare external IP address located in Ukraine.

Shortly before the initial reconnaissance started, Darktrace saw another RDP connection coming into the RDP server with the same RDP account as seen before. This connection lasted for almost an hour.

It is highly likely that the RDP credential used in this attack had been compromised prior to the attack, either via common brute-force methods, credential stuffing attacks, or phishing.

Thanks to Darktrace’s Deep-Packet Inspection, we can clearly see the connection and all related information.

Suspicious RDP connection information:

Time: 2020-02-10 16:57:06 UTC
Source: 46.150.70[.]86 (Ukraine)
Destination: 192.168.X.X
Destination Port: 64347
Protocol: RDP
Cookie: [REDACTED]
Duration: 00h41m40s
Data out: 8.44 MB
Data in: 1.86 MB

Darktrace detects incoming RDP connections from IP addresses that usually do not connect to the organization.

Attack tools download

Approximately 45 minutes after the suspicious RDP connection from Ukraine, the RDP server connected to the popular file sharing platform, Megaupload, and downloaded close to 300MB from there.

Darktrace’s AI recognized that neither this server, nor its automatically detected peer group, nor, in fact, anyone else on the network commonly utilized Megaupload — and therefore instantly detected this as anomalous behavior, and flagged it as unusual.

As well as the full hostname and actual IP used for the download, Megaupload is 100% rare for this organization.

Later on, we will see over 40GB being uploaded to Megaupload. This initial download of 300MB however is likely additional tooling and C2 implants downloaded by the threat-actor into the victim’s environment.

Internal reconnaissance

Only 3 minutes after the download from Megaupload onto the RDP server, Darktrace alerted on the RDP server doing an anomalous network scan:

The RDP server scanned 9 other internal devices on the same subnet on 7 unique ports: 21, 80, 139, 445, 3389, 4899, 8080
 . Anybody with some offensive security know-how will recognize most of these ports as default ports one would scan for in a Windows environment for lateral movement. Since this RDP server does not usually conduct network scans, Darktrace again identified this activity as highly anomalous.

Later on, we see the threat-actor do more network scanning. They become bolder and use more generic scans — one of them showing that they are using Nmap with a default user agent:

Additional Command and Control traffic

While the initial Command and Control traffic was most likely using predominantly RDP, the threat-actor now wanted to establish more persistence and create more resilient channels for C2.

Shortly after concluding the initial network scans (ca. 19:17 on 10th February 2020), the RDP server starts communicating with unusual external services that are unique and unusual for the victim’s environment.

Communications to Reddcoin

Again, nobody else is using Reddcoin on the network. The combination of application protocol and external port is extremely unusual for the network as well.

The communications also went to the Reddcoin API, indicating the installation of a software agent rather than manual communications. This was detected as Reddcoin was not only rare for the network, but also ‘young’ — i.e. this particular external destination had never been seen to be contacted before on the network until 25 minutes before.

Communications to the Reddcoin API

Communications to Exceptionless[.]io

As we can see, the communications to exceptionalness[.]io were done in a beaconing manner, using a Let’s Encrypt certificate, being rare for the network and using an unusual JA3 client hash. All of this indicates the presence of new software on the device, shortly after the threat-actor downloaded their 300MB of tooling.

While most of the above network activity started directly after the threat-actor dropped their tooling on the RDP server, the exact purpose of interfacing with Reddcoin and Exceptionless is unclear. The attacker seems to favor off-the-shelf tooling (Megaupload, Nmap, …) so they might use these services for C2 or telemetry-gathering purposes.

This concluded most of the activity on February 10.

More Command and Control traffic

Why would an attacker do this? Surely using all this C2 at the same time is much noisier than just using 1 or 2 channels?

Another significant burst of activity was observed on February 12 and 13.

The RDP server started making a lot of highly anomalous and rare connections to external destinations. It is inconclusive if all of the below services, IPs, and domains were used for C2 purposes only, but they are linked with high-confidence to the attacker’s activities:

  • HTTP beaconing to vkmuz[.]net
  • Significant amount of Tor usage
  • RDP connections to 198-0-244-153-static.hfc.comcastbusiness[.]net over non-standard RDP port 29348
  • RDP connections to 92.119.160[.]60 using an administrative account (geo-located in Russia)
  • Continued connections to Megaupload
  • Continued SSL beaconing to Exceptionless[.]io
  • Continued connections to api.reddcoin[.]com
  • SSL beaconing to freevpn[.]zone
  • HTTP beaconing to 31.41.116[.]201 to /index.php using a new User Agent
  • Unusual SSL connections to aj1713[.]online
  • Connections to Pastebin
  • SSL beaconing to www.itjx3no[.]com using an unusual JA3 client hash
  • SSL beaconing to safe-proxy[.]com
  • SSL connection to westchange[.]top without prior DNS hostname lookups (likely machine-driven)

What is significant here is the diversity in (potential) C2 channels: Tor, RDP going to dynamic ISP addresses, VPN solutions and possibly custom / customized off-the-shelf implants (the DGA-looking domains and HTTP to IP addresses to /index.php).

Why would an attacker do this? Surely using all this C2 at the same time is much noisier than just using 1 or 2 channels?

One answer might be that the attacker cared much more about short-term resilience than about stealth. As the overall attack in the network took less than 7 days, with a majority of the activity taking place over 2.5 days, this makes sense. Another possibility might be that various individuals were involved in parallel during this attack — maybe one attacker prefers the comfort of RDP sessions for hacking while another is more skilled and uses a particular post-exploitation framework.

The overall modus operandi in this financially-motivated attack is much more smash-and-grab than in the stealthy, espionage-related incidents observed in Advanced Persistent Threat campaigns (APT).

Data exfiltration

The DC uploaded around 40GB of data to Megaupload over the course of 24 hours.

While all of the above activity was seen on the RDP server (acting as the initial beach-head), the following data exfiltration activity was observed on a Domain Controller (DC) on the same subnet as the RDP server.

The DC uploaded around 40GB of data to Megaupload over the course of 24 hours.

Darktrace detected this data exfiltration while it was in progress — never did the DC (or any similar devices) upload similar amounts of data to the internet. Neither did any client nor server in the victim’s environment use Megaupload:

Ransom notes

Finally, Darktrace observed unusual files being accessed on internal SMB shares on February 13. These files appear to be ransom notes — they follow a similar, randomly-generated naming convention as other victims of the Sodinokibi group have reported:

413x0h8l-readme.txt
4omxa93-readme.txt

Conclusion and observations

The threat-actor seems to be using mostly off-the-shelf tooling which makes attribution harder — while also making detection more difficult.

This attack is representative of many of the current ransomware attacks: financially motivated, fast-acting, and targeted.

The threat-actor seems to be using mostly off-the-shelf tooling (RDP, Nmap, Mega, VPN solutions) which makes attribution harder — while also making detection more difficult. Using this kind of tooling often allows to blend in with regular admin activity — only once anomaly detection is used can this kind of activity be detected.

How can you spot the one anomalous outbound RDP connection amongst the thousands of regular RDP connections leaving your environment? How do you know when the use of Megaupload is malicious — compared to your users’ normal use of it? This is where the power of Darktrace’s self-learning AI comes into play.

Darktrace detected every stage of the visible attack lifecycle without using any threat intelligence or any static signatures.

The graphics below show an overview of detections on both compromised devices. The compromised devices were the highest-scoring assets for the network — even a level 1 analyst with limited previous exposure to Darktrace could detect such an in-progress attack in real time.

RDP Server

Some of the detections on the RDP server include:

  • Compliance / File Storage / Mega — using Megaupload in an unusual way
  • Device / Network Scan — detecting unusual network scans
  • Anomalous Connection / Application Protocol on Uncommon Port — detecting the use of protocols on unusual ports
  • Device / New Failed External Connections — detecting unusual failing C2
  • Compromise / Unusual Connections to Let’s Encrypt — detecting potential C2 over SSL using Let’s Encrypt
  • Compromise / Beacon to Young Endpoint — detecting C2 to new external endpoints for the network
  • Device / Attack and Recon Tools — detecting known offensive security tools like Nmap
  • Compromise / Tor Usage — detecting unusual Tor usage
  • Compromise / SSL Beaconing to Rare Destination — detecting generic SSL C2
  • Compromise / HTTP Beaconing to Rare Destination — detecting generic HTTP C2
  • Device / Long Agent Connection to New Endpoint — detecting unusual services on a device
  • Anomalous Connection / Outbound RDP to Unusual Port — detecting unusual RDP C2

DC

Some of the detections on the DC include:

  • Anomalous Activity / Anomalous External Activity from Critical Device — detecting unusual behaviour on dcs
  • Compliance / File storage / Mega — using Megaupload in an unusual way
  • Anomalous Connection / Data Sent to New External Device — data exfiltration to unusual locations
  • Anomalous Connection / Uncommon 1GB Outbound — large amounts of data leaving to unusual destinations
  • Anomalous Server Activity / Outgoing from Server — likely C2 to unusual endpoint on the internet


Inside the SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Written by
Max Heinemeyer
Global Field CISO

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September 25, 2025

Announcing Unified Real-Time CDR and Automated Investigations to Transform Cloud Security Operations

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Fragmented Tools are Failing SOC Teams in the Cloud Era

The cloud has transformed how businesses operate, reshaping everything from infrastructure to application delivery. But cloud security has not kept pace. Most tools still rely on traditional models of logging, policy enforcement, and posture management; approaches that provide surface-level visibility but lack the depth to detect or investigate active attacks.

Meanwhile, attackers are exploiting vulnerabilities, delivering cloud-native exploits, and moving laterally in ways that posture management alone cannot catch fast enough. Critical evidence is often missed, and alerts lack the forensic depth SOC analysts need to separate noise from true risk. As a result, organizations remain exposed: research shows that nearly nine in ten organizations have suffered a critical cloud breach despite investing in existing security tools [1].

SOC teams are left buried in alerts without actionable context, while ephemeral workloads like containers and serverless functions vanish before evidence can be preserved. Point tools for logging or forensics only add complexity, with 82% of organizations using multiple platforms to investigate cloud incidents [2].

The result is a broken security model: posture tools surface risks but don’t connect them to active attacker behaviors, while investigation tools are too slow and fragmented to provide timely clarity. Security teams are left reactive, juggling multiple point solutions and still missing critical signals. What’s needed is a unified approach that combines real-time detection and response for active threats with automated investigation and cloud posture management in a single workflow.

Just as security teams once had to evolve beyond basic firewalls and antivirus into network and endpoint detection, response, and forensics, cloud security now requires its own next era: one that unifies detection, response, and investigation at the speed and scale of the cloud.

A Powerful Combination: Real-Time CDR + Automated Cloud Forensics

Darktrace / CLOUD now uniquely unites detection, investigation, and response into one workflow, powered by Self-Learning AI. This means every alert, from any tool in your stack, can instantly become actionable evidence and a complete investigation in minutes.

With this release, Darktrace / CLOUD delivers a more holistic approach to cloud defense, uniting real-time detection, response, and investigation with proactive risk reduction. The result is a single solution that helps security teams stay ahead of attackers while reducing complexity and blind spots.

  • Automated Cloud Forensic Investigations: Instantly capture and analyze volatile evidence from cloud assets, reducing investigation times from days to minutes and eliminating blind spots
  • Enhanced Cloud-Native Threat Detection: Detect advanced attacker behaviors such as lateral movement, privilege escalation, and command-and-control in real time
  • Enhanced Live Cloud Topology Mapping: Gain continuous insight into cloud environments, including ephemeral workloads, with live topology views that simplify investigations and expose anomalous activity
  • Agentless Scanning for Proactive Risk Reduction: Continuously monitor for misconfigurations, vulnerabilities, and risky exposures to reduce attack surface and stop threats before they escalate.

Automated Cloud Forensic Investigations

Darktrace / CLOUD now includes capabilities introduced with Darktrace / Forensic Acquisition & Investigation, triggering automated forensic acquisition the moment a threat is detected. This ensures ephemeral evidence, from disks and memory to containers and serverless workloads can be preserved instantly and analyzed in minutes, not days. The integration unites detection, response, and forensic investigation in a way that eliminates blind spots and reduces manual effort.

Figure 1: Easily view Forensic Investigation of a cloud resource within the Darktrace / CLOUD architecture map

Enhanced Cloud-Native Threat Detection

Darktrace / CLOUD strengthens its real-time behavioral detection to expose early attacker behaviors that logs alone cannot reveal. Enhanced cloud-native detection capabilities include:

• Reconnaissance & Discovery – Detects enumeration and probing activity post-compromise.

• Privilege Escalation via Role Assumption – Identifies suspicious attempts to gain elevated access.

• Malicious Compute Resource Usage – Flags threats such as crypto mining or spam operations.

These enhancements ensure active attacks are detected earlier, before adversaries can escalate or move laterally through cloud environments.

Figure 2: Cyber AI Analyst summary of anomalous behavior for privilege escalation and establishing persistence.

Enhanced Live Cloud Topology Mapping

New enhancements to live topology provide real-time mapping of cloud environments, attacker movement, and anomalous behavior. This dynamic visibility helps SOC teams quickly understand complex environments, trace attack paths, and prioritize response. By integrating with Darktrace / Proactive Exposure Management (PEM), these insights extend beyond the cloud, offering a unified view of risks across networks, endpoints, SaaS, and identity — giving teams the context needed to act with confidence.

Figure 3: Enhanced live topology maps unify visibility across architectures, identities, network connections and more.

Agentless Scanning for Proactive Risk Reduction

Darktrace / CLOUD now introduces agentless scanning to uncover malware and vulnerabilities in cloud assets without impacting performance. This lightweight, non-disruptive approach provides deep visibility into cloud workloads and surfaces risks before attackers can exploit them. By continuously monitoring for misconfigurations and exposures, the solution strengthens posture management and reduces attack surface across hybrid and multi-cloud environments.

Figure 4: Agentless scanning of cloud assets reveals vulnerabilities, which are prioritized by severity.

Together, these capabilities move cloud security operations from reactive to proactive, empowering security teams to detect novel threats in real time, reduce exposures before they are exploited, and accelerate investigations with forensic depth. The result is faster triage, shorter MTTR, and reduced business risk — all delivered in a single, AI-native solution built for hybrid and multi-cloud environments.

Accelerating the Evolution of Cloud Security

Cloud security has long been fragmented, forcing teams to stitch together posture tools, log-based monitoring, and external forensics to get even partial coverage. With this release, Darktrace / CLOUD delivers a holistic, unified approach that covers every stage of the cloud lifecycle, from proactive posture management and risk identification to real-time detection, to automated investigation and response.

By bringing these capabilities together in a single AI-native solution, Darktrace is advancing cloud security beyond incremental change and setting a new standard for how organizations protect their hybrid and multi-cloud environments.

With Darktrace / CLOUD, security teams finally gain end-to-end visibility, response, and investigation at the speed of the cloud, transforming cloud defense from fragmented and reactive to unified and proactive.

[related-resource]

Sources: [1], [2] Darktrace Report: Organizations Require a New Approach to Handle Investigations in the Cloud

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

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September 25, 2025

Introducing the Industry’s First Truly Automated Cloud Forensics Solution

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Why Cloud Investigations Fail Today

Cloud investigations have become one of the hardest problems in modern cybersecurity. Traditional DFIR tools were built for static, on-prem environments, rather than dynamic and highly scalable cloud environments, containing ephemeral workloads that disappear in minutes. SOC analysts are flooded with cloud security alerts with one-third lacking actionable data to confirm or dismiss a threat[1], while DFIR teams waste 3-5 days requesting access and performing manual collection, or relying on external responders.

These delays leave organizations vulnerable. Research shows that nearly 90% of organizations suffer some level of damage before they can fully investigate and contain a cloud incident [2]. The result is a broken model: alerts are closed without a complete understanding of the threat due to a lack of visibility and control, investigations drag on, and attackers retain the upper hand.

For SOC teams, the challenge is scale and clarity. Analysts are inundated with alerts but lack the forensic depth to quickly distinguish real threats from noise. Manual triage wastes valuable time, creates alert fatigue, and often forces teams to escalate or dismiss incidents without confidence — leaving adversaries with room to maneuver.

For DFIR teams, the challenge is depth and speed. Traditional forensics tools were built for static, on-premises environments and cannot keep pace with ephemeral workloads that vanish in minutes. Investigators are left chasing snapshots, requesting access from cloud teams, or depending on external responders, leading to blind spots and delayed response.

That’s why we built Darktrace / Forensic Acquisition & Investigation, the first automated forensic solution designed specifically for the speed, scale, and complexities of the cloud. It addresses both sets of challenges by combining automated forensic evidence capture, attacker timeline reconstruction, and cross-cloud scale. The solution empowers SOC analysts with instant clarity and DFIR teams with forensic depth, all in minutes, not days. By leveraging the very nature of the cloud, Darktrace makes these advanced capabilities accessible to security teams of all sizes, regardless of expertise or resources.

Introducing Automated Forensics at the Speed and Scale of Cloud

Darktrace / Forensic Acquisition & Investigation transforms cloud investigations by capturing, processing, and analyzing forensic evidence of cloud workloads, instantly, even from time-restricted ephemeral resources. Triggered by a detection from any cloud security tool, the entire process is automated, providing accurate root cause analysis and deep insights into attacker behavior in minutes rather than days or weeks. SOC and DFIR teams no longer have to rely on manual processes, snapshots, or external responders, they can now leverage the scale and elasticity of the cloud to accelerate triage and investigations.

Seamless Integration with Existing Detection Tools

Darktrace / Forensic Acquisition & Investigation does not require customers to replace their detection stack. Instead, it integrates with cloud-native providers, XDR platforms, and SIEM/SOAR tools, automatically initiating forensic capture whenever an alert is raised. This means teams can continue leveraging their existing investments while gaining the forensic depth required to validate alerts, confirm root cause, and accelerate response.

Most importantly, the solution is natively integrated with Darktrace / CLOUD, turning real-time detections of novel attacker behaviors into full forensic investigations instantly. When Darktrace / CLOUD identifies suspicious activity such as lateral movement, privilege escalation, or abnormal usage of compute resources, Darktrace / Forensic Acquisition & Investigation automatically preserves the underlying forensic evidence before it disappears. This seamless workflow unites detection, response, and investigation in a way that eliminates gaps, accelerates triage, and gives teams confidence that every critical cloud alert can be investigated to completion.

Figure 1: Integration with Darktrace / CLOUD – this example is showing the ability to pivot into the forensic investigation associated with a compromised cloud asset

Automated Evidence Collection Across Hybrid and Multi-Cloud

The solution provides automated forensic acquisition across AWS, Microsoft Azure, GCP, and on-prem environments. It supports both full volume capture, creating a bit-by-bit copy of an entire storage device for the most comprehensive preservation of evidence, and triage collection, which prioritizes speed by gathering only the most essential forensic artifacts such as process data, logs, network connections, and open file contents. This flexibility allows teams to strike the right balance between speed and depth depending on the investigation at hand.

Figure 2: Ability to acquire forensic data from Cloud, SaaS and on-prem environments

Automated Investigations, Root Cause Analysis and Attacker Timelines

Once evidence is collected, Darktrace applies automation to reconstruct attacker activity into a unified timeline. This includes correlating commands, files, lateral movement, and network activity into a single investigative view enriched with custom threat intelligence such as IOCs. Detailed investigation reporting including an investigation summary, an overview of the attacker timeline, and key events. Analysts can pivot into detailed views such as the filesystem view, traversing directories or inspecting file content, or filter and search using faceted options to quickly narrow the scope of an investigation.

Figure 3: Automated Investigation view surfacing the most significant attacker activity, which is contextualized with Alarm information

Forensics for Containers and Ephemeral Assets

Investigating containers and serverless workloads has historically been one of the hardest challenges for DFIR teams, as these assets often disappear before evidence can be preserved. Darktrace / Forensic Acquisition & Investigation captures forensic evidence across managed Kubernetes cloud services, even from distroless or no-shell containers, AWS ECS and other environments, ensuring that ephemeral activity is no longer a blind spot. For hybrid organizations, this extends to on-premises Kubernetes and OpenShift deployments, bringing consistency across environments.

Figure 4: Container investigations – this example is showing the ability to capture containers from managed Kubernetes cloud services

SaaS Log Collection for Modern Investigations

Beyond infrastructure-level data, the solution collects logs from SaaS providers such as Microsoft 365, Entra ID, and Google Workspace. This enables investigations into common attack types like business email compromise (BEC), account takeover (ATO), and insider threats — giving teams visibility into both infrastructure-level and SaaS-driven compromise from a single platform.

Figure 5: Ability to import logs from SaaS providers including Microsoft 365, Entra ID, and Google Workspace

Proactive Vulnerability and Malware Discovery

Finally, the solution surfaces risk proactively with vulnerability and malware discovery for Linux-based cloud resources. Vulnerabilities are presented in a searchable table and correlated with the attacker timeline, enabling teams to quickly understand not just which packages are exposed, but whether they have been targeted or exploited in the context of an incident.

Figure 6: Vulnerability data with pivot points into the attacker timeline

Cloud-Native Scale and Performance

Darktrace / Forensic Acquisition & Investigation uses a cloud-native parallel processing architecture that spins up compute resources on demand, ensuring that investigations run at scale without bottlenecks. Detailed reporting and summaries are automatically generated, giving teams a clear record of the investigation process and supporting compliance, litigation readiness, and executive reporting needs.

Scalable and Flexible Deployment Options

Every organization has different requirements for speed, control, and integration. Darktrace / Forensic Acquisition & Investigation is designed to meet those needs with two flexible deployment models.

  • Self-Hosted Virtual Appliance delivers deep integration and control across hybrid environments, preserving forensic data for compliance and litigation while scaling to the largest enterprise investigations.
  • SaaS-Delivered Deployment provides fast time-to-value out of the box, enabling automated forensic response without requiring deep cloud expertise or heavy setup.

Both models are built to scale across regions and accounts, ensuring organizations of any size can achieve rapid value and adapt the solution to their unique operational and compliance needs. This flexibility makes advanced cloud forensics accessible to every security team — whether they are optimizing for speed, integration depth, or regulatory alignment

Delivering Advanced Cloud Forensics for Every Team

Until now, forensic investigations were slow, manual, and reserved for only the largest organizations with specialized DFIR expertise. Darktrace / Forensic Acquisition & Investigation changes that by leveraging the scale and elasticity of the cloud itself to automate the entire investigation process. From capturing full disk and memory at detection to reconstructing attacker timelines in minutes, the solution turns fragmented workflows into streamlined investigations available to every team.

Whether deployed as a SaaS-delivered service for fast time-to-value or as a self-hosted appliance for deep integration, Darktrace / Forensic Acquisition & Investigation provides the features that matter most: automated evidence capture, cross-cloud investigations, forensic depth for ephemeral assets, and root cause clarity without manual effort.

With Darktrace / Forensic Acquisition & Investigation, what once took days now takes minutes. Now, forensic investigations in the cloud are faster, more scalable, and finally accessible to every security team, no matter their size or expertise.

[related-resource]

Sources: [1], [2] Darktrace Report: Organizations Require a New Approach to Handle Investigations in the Cloud

Additional Resources

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About the author
Paul Bottomley
Director of Product Management | Darktrace
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