August 2, 2023

Darktrace's Detection of Ransomware & Syssphinx

Read how Darktrace identified an attack technique by the threat group, Syssphinx. Learn how Darktrace's quick identification process can spot a threat.

Written by

Adam Potter

Senior 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

Adam Potter

Senior Cyber Analyst

Aug 2023

Introduction

As the threat of costly cyber-attacks continues represent a real concern to security teams across the threat landscape, more and more organizations are strengthening their defenses with additional security tools to identify attacks and protect their networks. As a result, malicious actors are being forced to adapt their tactics, modify existing variants of malicious software, or utilize entirely new variants.

Symantec recently released an article about Syssphinx, the financially motivated cyber threat group previously known for their point-of-sale attacks. Syssphinx attempts to deploy ransomware on customer networks via a modified version of their ‘Sardonic’ backdoor. Such activity highlights the ability of threat actors to alter the composition and presentation of payloads, tools, and tactics.

Darktrace recently detected some of the same indicators suggesting a likely Syssphinx compromise within the network of a customer trialing the Darktrace DETECT™ and RESPOND™ products. Despite the potential for variations in the construction of backdoors and payloads used by the group, Darktrace’s anomaly-based approach to threat detection allowed it to stitch together a detailed account of compromise activity and identify the malicious activity prior to disruptive events on the customer’s network.

What is Syssphinx?

Syssphinx is a notorious cyber threat entity known for its financially motivated compromises. Also referred to as FIN8, Syssphinx has been observed as early as 2016 and is largely known to target private sector entities in the retail, hospitality, insurance, IT, and financial sectors.^[1]

Although Syssphinx primarily began focusing on point-of-sale style attacks, the activity associated with the group has more recently incorporated ransomware variants into their intrusions in a potential bid to further extract funds from target organizations.^[2]

Syssphinx Sardonic Backdoor

Given this gradual opportunistic incorporation of ransomware, it should not be surprising that Syssphinx has slowly expanded its repertoire of tools. When primarily performing point-of-sale compromises, the group was known for its use of point-of-sale specific malwares including BadHatch, PoSlurp/PunchTrack, and PowerSniff/PunchBuggy/ShellTea.^[3]

However, in a seeming response to updates in detection systems while using previous indicators of compromise (IoCs), Syssphinx began to modify its BadHatch malware. This resulted in the use of a C++ derived backdoor known as “Sardonic”, which has the ability to aggregate host credentials, spawn additional command sessions, and deliver payloads to compromised devices via dynamic-link library (DLL).^[4],[5]

Analysis of the latest version of Sardonic reveals further changes to the malware to elude detection. These shifts include the implementation of the backdoor in the C programming language, and additional over-the-network communication obfuscation techniques.[6]

During the post-exploitation phase, the group tends to rely on “living-off-the-land” tactics, whereby an attacker utilizes tools already present within the organization’s digital environment to avoid detection. Syssphinx seems to utilize system-native tools such as PowerShell and the Windows Management Instrumentation (WMI) interface.^[7] It is also not uncommon to see Windows-based vulnerability exploits employed on compromised devices. This has been observed by researchers who have examined previous iterations of Syssphinx backdoors.^[8] Syssphinx also appears to exhibit elements of strategic patience and discipline in its operations, with significant time gaps in operations noted by researchers. During this time, it appears likely that updates and tweaks were applied to Syssphinx payloads.

Compromise Details

In late April 2023, Darktrace identified an active compromise on the network of a prospective customer who was trialing Darktrace DETECT+RESPOND. The customer, a retailer in EMEA with hundreds of tracked devices, reached out to the Darktrace Analyst team via the Ask the Expert (ATE) service for support and further investigation, following the encryption of their server and backup data storage in an apparent ransomware attack. Although the encryption events fell outside Darktrace’s purview due to a limited set up of trial appliances, Darktrace was able to directly track early stages of the compromise before exfiltration and encryption events began. If a full deployment had been set up and RESPOND functionality had been configured in autonomous response mode, Darktrace may have helped mitigate such encryption events and would have aided in the early identification of this ransomware attack.

Initial Intrusion and Establishment of Command and Control (C2) Infrastructure

As noted by security researchers, Syssphinx largely relies on social engineering and phishing emails to deliver its backdoor payloads. As there were no Darktrace/Email™ products deployed for this customer, it would be difficult to directly observe the exact time and manner of initial payload delivery related to this compromise. This is compounded by the fact that the customer had only recently began using Darktrace’s products during their trial period. Given the penchant for patience and delay by Syssphinx, it is possible that the intrusion began well before Darktrace had visibility of the organization’s network.

However, beginning on April 30, 2023, at 07:17:31 UTC, Darktrace observed the domain controller dc01.corp.XXXX making repeated SSL connections to the endpoint 173-44-141-47[.]nip[.]io. In addition to the multiple open-source intelligence (OSINT) flags for this endpoint, the construction of the domain parallels that of the initial domain used to deliver a backdoor, as noted by Symantec in their analysis (37-10-71-215[.]nip[.]io). This activity likely represented the initial beaconing being performed by the compromised device. Additionally, an elevated level of incoming external data over port 443 was observed during this time, which may be associated with the delivery of the Sardonic backdoor payload. Given the unusual use of port 443 to perform SSH connections later seen in the kill chain of this attack, this activity could also parallel the employment of embedded backdoor payloads seen in the latest iteration of the Sardonic backdoor noted by Symantec.

Figure 1: Graph of the incoming external data surrounding the time of the initial establishment of command and control communication for the domain controller. As seen in the graph, the spike in incoming external data during this time may parallel the delivery of Syssphinx Sardonic backdoor.

Regardless, the domain controller proceeded to make repeated connections over port 443 to the noted domain.

Figure 2: Breach event log for the domain controller making repeated connections over port 443 to the rare external destination endpoint in constitute the establishment of C2 communication.

Internal Reconnaissance/Privilege Escalation

Following the establishment of C2 communication, Darktrace detected numerous elements of internal reconnaissance. On Apr 30, 2023, at 22:06:26 UTC, the desktop device desktop_02.corp.XXXX proceeded to perform more than 100 DRSGetNCChanges requests to the aforementioned domain controller. These commands, which are typically implemented over the RPC protocol on the DRSUAPI interface, are frequently utilized in Active Directory sync attacks to copy Active Directory information from domain controllers. Such activity, when not performed by new domain controllers to sync Active Directory contents, can indicate malicious domain or user enumeration, credential compromise or Active Directory enumeration.

Although the affected device made these requests to the previously noted domain controller, which was already compromised, such activity may have further enabled the compromise by allowing the threat actor to transfer these details to a more easily manageable device.

The device performing these DRSGetNCChanges requests would later be seen performing lateral movement activity and making connections to malicious endpoints.

Figure 3: Breach log highlighting the DRS operations performed by the corporate device to the destination domain controller. Such activity is rarely authorized for devices not tagged as administrative or as domain controllers.

Execution and Lateral Movement

At 23:09:53 UTC on April 30, 2023, the original domain server proceeded to make multiple uncommon WMI calls to a destination server on the same subnet (server01.corp.XXXX). Specifically, the device was observed making multiple RPC calls to IWbem endpoints on the server, which included login and ExecMethod (method execution) commands on the destination device. This destination device later proceeded to conduct additional beaconing activity to C2 endpoints and exfiltrate data.

Figure 4: Breach log for the domain controller performing WMI commands to the destination server during the lateral movement phase of the breach.

Similarly, beginning on May 1, 2023, at 00:11:09 UTC, the device desktop_02.corp.XXXX made multiple WMI requests to two additional devices, one server and one desktop, within the same subnet as the original domain controller. During this time, desktop_02.corp.XXXX also utilized SMBv1, an outdated and typically non-compliant version communication protocol, to write the file rclone.exe to the same two destination devices. Rclone.exe, and its accompanying bat file, is a command-line tool developed by IT provider Rclone, to perform file management tasks. During this time, Darktrace also observed the device reading and deleting an unexpected numeric file on the ADMIN$ of the destination server, which may represent additional defense evasion techniques and tool staging.

Figure 5: Event log highlighting the writing of rclone.exe using the outdated SMBv1 communication protocol.

Figure 6: SMB logs indicating the reading and deletion of numeric string files on ADMIN$ shares of the destination devices during the time of the rclone.exe SMB writes. Such activity may be associated with tool staging and could indicate potential defense evasion techniques.

Given that the net loader sample analyzed by Symantec injects the backdoor into a WmiPrvSE.exe process, the use of WMI operations is not unexpected. Employment of WMI also correlates with the previously mentioned “living-off-the-land” tactics, as WMI services are commonly used for regular network and system administration purposes. Moreover, the staging of rclone.exe, a legitimate file management tool, for data exfiltration underscores attempts to blend into existing and expected network traffic and remain undetected on the customer’s network.

Data Exfiltration and Impact

Initial stages of data exfiltration actually began prior to some of the lateral movement events described above. On April 30, 2023, 23:09:47 the device server01.corp.XXXX, transferred nearly 11 GB of data to 173.44[.]141[.]47, as well as to the rare external IP address 170.130[.]55[.]77, which appears to have served as the main exfiltration destination during this compromise. Furthermore, the host made repeated connections to the same external IP associated with the initial suspicious beaconing activity (173.44[.]141[.]47) over SSL.

While the data exfiltration event unfolded, the device, server01.corp.XXXX, made multiple HTTP requests to 37.10[.]71[.]215, which featured URIs requesting the rclone.exe and rclone.bat files. This IP address was directly involved in the sample analyzed by Symantec. Furthermore, one of the devices that received the SMB file writes of rclone.exe and the WMI commands from desktop_02.corp.XXXX also performed SSL beaconing to endpoints associated with the compromise.

Between 01:20:45 - 03:31:41 UTC on May 1, 2023, a Darktrace detected a series of devices on the network performing a repeated pattern of activity, namely external connectivity followed by suspicious file downloads and external data transfer operations. Specifically, each affected device made multiple HTTP requests to 37.10[.]71[.]215 for rclone files. The devices proceeded to download the executable and/or binary files, and then transfer large amounts of data to the aforementioned endpoints, 170.130[.]55[.]77 and or 173-44-141-47[.]nip[.]io. Although the devices involved in data exfiltration utilized port 443 as a destination port, the connections actually used the SSH protocol. Darktrace recognized this behavior as unusual as port 443 is typically associated with the SSL protocol, while port 22 is reserved for SSH. Therefore, this activity may represent the threat actor’s attempts to remain undetected by security tools.

This unexpected use of SSH over port 443 also correlates with the descriptions of the new Sardonic backdoor according to threat researchers. Further beaconing and exfiltration activity was performed by an additional host one day later whereby the device made suspicious repeated connections to the aforementioned external hosts.

Figure 7: Connection details highlighting the use of port 443 for SSH connections during the exfiltration events.

In total, nine separate devices were involved in this pattern of activity. Five of these devices were labeled as ‘administrative’ devices according to their hostnames. Over the course of the entire exfiltration event, the attackers exfiltrated almost 61 GB of data from the organization’s environment.

Figure 8: Graph showing the levels of external data transfer from a breach device for one day on either side of the breach time. There is a large spike in such activity during the time of the breach that underscores the exfiltration events.

In addition to the individual anomaly detections by DETECT, Darktrace’s Cyber AI Analyst™ launched an autonomous investigation into the unusual behavior carried out by affected devices, connecting and collating multiple security events into one AI Analyst Incident. AI Analyst ensures that Darktrace can recognize and link the individual steps of a wider attack, rather than just identifying isolated incidents. While traditional security tools may mistake individual breaches as standalone activity, Darktrace’s AI allows it to provide unparalleled visibility over emerging attacks and their kill chains. Furthermore, Cyber AI Analyst’s instant autonomous investigations help to save customer security teams invaluable time in triaging incidents in comparison with human teams who would have to commit precious time and resources to conduct similar pattern analysis.

In this specific case, AI Analyst identified 44 separate security events from 18 different devices and was able to tie them together into one incident. The events that made up this AI Analyst Incident included:

Possible SSL Command and Control
Possible HTTP Command and Control
Unusual Repeated Connections
Suspicious Directory Replication ServiceActivity
Device / New or Uncommon WMI Activity
SMB Write of Suspicious File
Suspicious File Download
Unusual External Data Transfer
Unusual External Data Transfer to MultipleRelated Endpoints

Figure 9: Cyber AI Incident log highlighting multiple unusual anomalies and connecting them into one incident.

Had Darktrace RESPOND been enabled in autonomous response mode on the network of this prospective customer, it would have been able to take rapid mitigative action to block the malicious external connections used for C2 communication and subsequent data exfiltration, ideally halting the attack at this stage. As previously discussed, the limited network configuration of this trial customer meant that the encryption events unfortunately took place outside of Darktrace’s scope. When fully configured on a customer environment, Darktrace DETECT can identify such encryption attempts as soon as they occur. Darktrace RESPOND, in turn, would be able to immediately intervene by applying preventative actions like blocking internal connections that may represent file encryption, or limiting potentially compromised devices to a previously established pattern of life, ensuring they cannot carry out any suspicious activity.

Conclusion

Despite the limitations posed by the customer’s trial configuration, Darktrace demonstrated its ability to detect malicious activity associated with Syssphinx and track it across multiple stages of the kill chain.

Darktrace’s ability to identify the early stages of a compromise and various steps of the kill chain, highlights the necessity for machine learning-enabled, anomaly-based detection. In the face of threats such as Syssphinx, that exhibit the propensity to recast backdoor payloads and incorporate on “living-off-the-land” tactics, signatures and rules-based detection may not prove as effective. While Syssphinx and other threat groups will continue to adopt new tools, methods, and techniques, Darktrace’s Self-Learning AI is uniquely positioned to meet the challenge of such threats.

Appendix

DETECT Model Breaches Observed

• Anomalous Server Activity / Anomalous External Activity from Critical Network Device

• Anomalous Connection / Anomalous DRSGetNCChanges Operation

• Device / New or Uncommon WMI Activity

• Compliance / SMB Drive Write

• Anomalous Connection / Data Sent to Rare Domain

• Anomalous Connection / Uncommon 1 GiB Outbound

• Unusual Activity / Unusual External Data Transfer

• Unusual Activity / Unusual External Data to New Endpoints

• Compliance / SSH to Rare External Destination

• Anomalous Connection / Unusual SMB Version 1 Connectivity

• Anomalous File / EXE from Rare External Location

• Anomalous File / Script from Rare External Location

• Compromise / Suspicious File and C2

• Device / Initial Breach Chain Compromise

‍

AI Analyst Incidents Observed

• Possible SSL Command and Control

• Possible HTTP Command and Control

• Unusual Repeated Connections

• Suspicious Directory Replication Service Activity

• Device / New or Uncommon WMI Activity

• SMB Write of Suspicious File

• Suspicious File Download

• Unusual External Data Transfer

• Unusual External Data Transfer to Multiple Related Endpoints

IoCs

IoC - Type - Description

37.10[.]71[.]215 – IP – C2 + payload endpoint

173-44-141-47[.]nip[.]io – Hostname – C2 – payload

173.44[.]141[.]47 – IP – C2 + potential payload

170.130[.]55[.]77 – IP – Data exfiltration endpoint

Rclone.exe – Exe File – Common data tool

Rclone.bat – Script file – Common data tool

MITRE ATT&CK Mapping

Command and Control

T1071 - Application Layer Protocol

T1071.001 – Web protocols

T1573 – Encrypted channels

T1573.001 – Symmetric encryption

T1573.002 – Asymmetric encryption

T1571 – Non-standard port

T1105 – Ingress tool transfer

Execution

T1047 – Windows Management Instrumentation

Credential Access‍

T1003 – OS Credential Dumping

T1003.006 – DCSync

Lateral Movement

T1570 – Lateral Tool Transfer

T1021 - Remote Services

T1021.002 - SMB/Windows Admin Shares

T1021.006 – Windows Remote Management

Exfiltration

T1048 - Exfiltration Over Alternative Protocol

T1048.001 - Exfiltration Over Symmetric Encrypted Non-C2 Protocol

T1048.002 - Exfiltration Over Symmetric Encrypted Non-C2 Protocol

T1041 - Exfiltration Over C2 Channel

References

^[1] https://cyberscoop.com/syssphinx-cybercrime-ransomware/

^[2] https://symantec-enterprise-blogs.security.com/blogs/threat-intelligence/Syssphinx-FIN8-backdoor

^[3] https://www.bleepingcomputer.com/news/security/fin8-deploys-alphv-ransomware-using-sardonic-malware-variant/

^[4] https://symantec-enterprise-blogs.security.com/blogs/threat-intelligence/Syssphinx-FIN8-backdoor

^[5] https://thehackernews.com/2023/07/fin8-group-using-modified-sardonic.html

^[6] https://symantec-enterprise-blogs.security.com/blogs/threat-intelligence/Syssphinx-FIN8-backdoor

^[7] https://symantec-enterprise-blogs.security.com/blogs/threat-intelligence/Syssphinx-FIN8-backdoor

^[8] https://www.mandiant.com/resources/blog/windows-zero-day-payment-cards

Written by

Adam Potter

Senior Cyber Analyst

Inside the SOC

Written by

Adam Potter

Senior Cyber Analyst

VP, Security & AI Strategy, Field CISO

Senior Director of Product, Cloud | Darktrace

Watch the NIS2 Webinar

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Cloud

January 14, 2026

React2Shell Reflections: Cloud Insights, Finance Sector Impacts, and How Threat Actors Moved So Quickly

Introduction

Last month’s disclosure of CVE 2025-55812, known as React2Shell, provided a reminder of how quickly modern threat actors can operationalize newly disclosed vulnerabilities, particularly in cloud-hosted environments.

The vulnerability was discovered on December 3, 2025, with a patch made available on the same day. Within 30 hours of the patch, a publicly available proof-of-concept emerged that could be used to exploit any vulnerable server. This short timeline meant many systems remained unpatched when attackers began actively exploiting the vulnerability.

Darktrace researchers rapidly deployed a new honeypot to monitor exploitation of CVE 2025-55812 in the wild.

Within two minutes of deployment, Darktrace observed opportunistic attackers exploiting this unauthenticated remote code execution flaw in React Server Components, leveraging a single crafted request to gain control of exposed Next.js servers. Exploitation quickly progressed from reconnaissance to scripted payload delivery, HTTP beaconing, and cryptomining, underscoring how automation and pre‑positioned infrastructure by threat actors now compress the window between disclosure and active exploitation to mere hours.

For cloud‑native organizations, particularly those in the financial sector, where Darktrace observed the greatest impact, React2Shell highlights the growing disconnect between patch availability and attacker timelines, increasing the likelihood that even short delays in remediation can result in real‑world compromise.‍

Cloud insights

In contrast to traditional enterprise networks built around layered controls, cloud architectures are often intentionally internet-accessible by default. When vulnerabilities emerge in common application frameworks such as React and Next.js, attackers face minimal friction. No phishing campaign, no credential theft, and no lateral movement are required; only an exposed service and exploitable condition.

The activity Darktrace observed during the React2shell intrusions reflects techniques that are familiar yet highly effective in cloud-based attacks. Attackers quickly pivot from an exposed internet-facing application to abusing the underlying cloud infrastructure, using automated exploitation to deploy secondary payloads at scale and ultimately act on their objectives, whether monetizing access through cryptomining or to burying themselves deeper in the environment for sustained persistence.

Cloud Case Study

In one incident, opportunistic attackers rapidly exploited an internet-facing Azure virtual machine (VM) running a Next.js application, abusing the React/next.js vulnerability to gain remote command execution within hours of the service becoming exposed. The compromise resulted in the staged deployment of a Go-based remote access trojan (RAT), followed by a series of cryptomining payloads such as XMrig.

Initial Access

Initial access appears to have originated from abused virtual private network (VPN) infrastructure, with the source IP (146.70.192[.]180) later identified as being associated with Surfshark

Figure 1: The IP address above is associated with VPN abuse leveraged for initial exploitation via Surfshark infrastructure.

The use of commercial VPN exit nodes reflects a wider trend of opportunistic attackers leveraging low‑cost infrastructure to gain rapid, anonymous access.

Parent process telemetry later confirmed execution originated from the Next.js server, strongly indicating application-layer compromise rather than SSH brute force, misused credentials, or management-plane abuse.

Payload execution

Shortly after successful exploitation, Darktrace identified a suspicious file and subsequent execution. One of the first payloads retrieved was a binary masquerading as “vim”, a naming convention commonly used to evade casual inspection in Linux environments. This directly ties the payload execution to the compromised Next.js application process, reinforcing the hypothesis of exploit-driven access.

Command-and-Control (C2)

Network flow logs revealed outbound connections back to the same external IP involved in the inbound activity. From a defensive perspective, this pattern is significant as web servers typically receive inbound requests, and any persistent outbound callbacks — especially to the same IP — indicate likely post-exploitation control. In this case, a C2 detection model alert was raised approximately 90 minutes after the first indicators, reflecting the time required for sufficient behavioral evidence to confirm beaconing rather than benign application traffic.

Cryptominers deployment and re-exploitation

Following successful command execution within the compromised Next.js workload, the attackers rapidly transitioned to monetization by deploying cryptomining payloads. Microsoft Defender observed a shell command designed to fetch and execute a binary named “x” via either curl or wget, ensuring successful delivery regardless of which tooling was availability on the Azure VM.

The binary was written to /home/wasiluser/dashboard/x and subsequently executed, with open-source intelligence (OSINT) enrichment strongly suggesting it was a cryptominer consistent with XMRig‑style tooling. Later the same day, additional activity revealed the host downloading a static XMRig binary directly from GitHub and placing it in a hidden cache directory (/home/wasiluser/.cache/.sys/).

The use of trusted infrastructure and legitimate open‑source tooling indicates an opportunistic approach focused on reliability and speed. The repeated deployment of cryptominers strongly suggests re‑exploitation of the same vulnerable web application rather than reliance on traditional persistence mechanisms. This behavior is characteristic of cloud‑focused attacks, where publicly exposed workloads can be repeatedly compromised at scale more easily.

Financial sector spotlight

During the mass exploitation of React2Shell, Darktrace observed targeting by likely North Korean affiliated actors focused on financial organizations in the United Kingdom, Sweden, Spain, Portugal, Nigeria, Kenya, Qatar, and Chile.

The targeting of the financial sector is not unexpected, but the emergence of new Democratic People’s Republic of Korea (DPRK) tooling, including a Beavertail variant and EtherRat, a previously undocumented Linux implant, highlights the need for updated rules and signatures for organizations that rely on them.

EtherRAT uses Ethereum smart contracts for C2 resolution, polling every 500 milliseconds and employing five persistence mechanisms. It downloads its own Node.js runtime from nodejs[.]org and queries nine Ethereum RPC endpoints in parallel, selecting the majority response to determine its C2 URL. EtherRAT also overlaps with the Contagious Interview campaign, which has targeted blockchain developers since early 2025.

Threat actor behavior and speed

Darktrace’s honeypot was exploited just two minutes after coming online, demonstrating how automated scanning, pre-positioned infrastructure and staging, and C2 infrastructure traced back to “bulletproof” hosting reflects a mature, well‑resourced operational chain.

For financial organizations, particularly those operating cloud‑native platforms, digital asset services, or internet‑facing APIs, this activity demonstrates how rapidly geopolitical threat actors can weaponize newly disclosed vulnerabilities, turning short patching delays into strategic opportunities for long‑term access and financial gain. This underscores the need for a behavioral-anomaly-led security posture.

Credit to Nathaniel Jones (VP, Security & AI Strategy, Field CISO)

Edited by Ryan Traill (Analyst Content Lead)

Appendices

Indicators of Compromise (IoCs)

146.70.192[.]180 – IP Address – Endpoint Associated with Surfshark

References

https://www.darktrace.com/resources/the-state-of-cybersecurity-in-the-finance-sector

About the author

Nathaniel Jones

VP, Security & AI Strategy, Field CISO

Blog

Cloud

January 13, 2026

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

Introduction: Shifting focus from prevention to runtime

Cloud security has spent the last decade focused on prevention; tightening configurations, scanning for vulnerabilities, and enforcing best practices through Cloud Native Application Protection Platforms (CNAPP). These capabilities remain essential, but they are not where cloud attacks happen.

Attacks happen at runtime: the dynamic, ephemeral, constantly changing execution layer where applications run, permissions are granted, identities act, and workloads communicate. This is also the layer where defenders traditionally have the least visibility and the least time to respond.

Today’s threat landscape demands a fundamental shift. Reducing cloud risk now requires moving beyond static posture and CNAPP only approaches and embracing realtime behavioral detection across workloads and identities, paired with the ability to automatically preserve forensic evidence. Defenders need a continuous, real-time understanding of what “normal” looks like in their cloud environments, and AI capable of processing massive data streams to surface deviations that signal emerging attacker behavior.

Runtime: The layer where attacks happen

Runtime is the cloud in motion — containers starting and stopping, serverless functions being called, IAM roles being assumed, workloads auto scaling, and data flowing across hundreds of services. It’s also where attackers:

Weaponize stolen credentials
Escalate privileges
Pivot programmatically
Deploy malicious compute
Manipulate or exfiltrate data

The challenge is complex: runtime evidence is ephemeral. Containers vanish; critical process data disappears in seconds. By the time a human analyst begins investigating, the detail required to understand and respond to the alert, often is already gone. This volatility makes runtime the hardest layer to monitor, and the most important one to secure.

What Darktrace / CLOUD Brings to Runtime Defence

Darktrace / CLOUD is purpose-built for the cloud execution layer. It unifies the capabilities required to detect, contain, and understand attacks as they unfold, not hours or days later. Four elements define its value:

1. Behavioral, real-time detection

The platform learns normal activity across cloud services, identities, workloads, and data flows, then surfaces anomalies that signify real attacker behavior, even when no signature exists.

2. Automated forensic level artifact collection

The moment Darktrace detects a threat, it can automatically capture volatile forensic evidence; disk state, memory, logs, and process context, including from ephemeral resources. This preserves the truth of what happened before workloads terminate and evidence disappears.

3. AI-led investigation

Cyber AI Analyst assembles cloud behaviors into a coherent incident story, correlating identity activity, network flows, and Cloud workload behavior. Analysts no longer need to pivot across dashboards or reconstruct timelines manually.

4. Live architectural awareness

Darktrace continuously maps your cloud environment as it operates; including services, identities, connectivity, and data pathways. This real-time visibility makes anomalies clearer and investigations dramatically faster.

Together, these capabilities form a runtime-first security model.

Why CNAPP alone isn’t enough

CNAPP platforms excel at pre deployment checks all the way down to developer workstations, identifying misconfigurations, concerning permission combinations, vulnerable images, and risky infrastructure choices. But CNAPP’s breadth is also its limitation. CNAPP is about posture. Runtime defense is about behavior.

CNAPP tells you what could go wrong; runtime detection highlights what is going wrong right now.

It cannot preserve ephemeral evidence, correlate active behaviors across domains, or contain unfolding attacks with the precision and speed required during a real incident. Prevention remains essential, but prevention alone cannot stop an attacker who is already operating inside your cloud environment.

Real-world AWS Scenario: Why Runtime Monitoring Wins

A recent incident detected by Darktrace / CLOUD highlights how cloud compromises unfold, and why runtime visibility is non-negotiable. Each step below reflects detections that occur only when monitoring behavior in real time.

1. External Credential Use

Detection: Unusual external source for credential use: An attacker logs into a cloud account from a never-before-seen location, the earliest sign of account takeover.

2. AWS CLI Pivot

Detection: Unusual CLI activity: The attacker switches to programmatic access, issuing commands from a suspicious host to gain automation and stealth.

3. Credential Manipulation

Detection: Rare password reset: They reset or assign new passwords to establish persistence and bypass existing security controls.

4. Cloud Reconnaissance

Detection: Burst of resource discovery: The attacker enumerates buckets, roles, and services to map high value assets and plan next steps.

5. Privilege Escalation

Detection: Anomalous IAM update: Unauthorized policy updates or role changes grant the attacker elevated access or a backdoor.

6. Malicious Compute Deployment

Detection: Unusual EC2/Lambda/ECS creation: The attacker deploys compute resources for mining, lateral movement, or staging further tools.

7. Data Access or Tampering

Detection: Unusual S3 modifications: They alter S3 permissions or objects, often a prelude to data exfiltration or corruption.

Only some of these actions would appear in a posture scan, crucially after the fact.
Every one of these runtime detections is visible only through real-time behavioral monitoring while the attack is in progress.

The future of cloud security Is runtime-first

Cloud defense can no longer revolve solely around prevention. Modern attacks unfold in runtime, across a fast-changing mesh of workloads, services, and — critically — identities. To reduce risk, organizations must be able to detect, understand, and contain malicious activity as it happens, before ephemeral evidence disappears and before attacker's pivot across identity layers.

Darktrace / CLOUD delivers this shift by turning runtime, the most volatile and consequential layer in the cloud, into a fully defensible control point through unified visibility across behavior, workloads, and identities. It does this by providing:

Real-time behavior detection across workloads and identity activity ‍
Autonomous response actions for rapid containment ‍
Automated forensic level artifact preservation the moment events occur ‍
AI-driven investigation that separates weak signals from true attacker patterns ‍
Live cloud environment insight to understand context and impact instantly

Cloud security must evolve from securing what might go wrong to continuously understanding what is happening; in runtime, across identities, and at the speed attackers operate. Unifying runtime and identity visibility is how defenders regain the advantage.

[related-resource]

About the author

Adam Stevens

Senior Director of Product, Cloud | Darktrace

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Check out this article by Darktrace: Darktrace's Detection of Ransomware & Syssphinx

Darktrace's Detection of Ransomware & Syssphinx

Introduction

What is Syssphinx?

Syssphinx Sardonic Backdoor

Compromise Details

Initial Intrusion and Establishment of Command and Control (C2) Infrastructure

Internal Reconnaissance/Privilege Escalation

Execution and Lateral Movement

Data Exfiltration and Impact

Conclusion

Appendix

IoCs

MITRE ATT&CK Mapping

References

React2Shell Reflections: Cloud Insights, Finance Sector Impacts, and How Threat Actors Moved So Quickly

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

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January 14, 2026

React2Shell Reflections: Cloud Insights, Finance Sector Impacts, and How Threat Actors Moved So Quickly

Introduction

Cloud insights

Cloud Case Study

Initial Access

Payload execution

Command-and-Control (C2)

Cryptominers deployment and re-exploitation

Financial sector spotlight

Read more finance‑sector insights in Darktrace’s white paper, The State of Cyber Security in the Finance Sector.

Threat actor behavior and speed

Appendices

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Cloud

January 13, 2026

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

Introduction: Shifting focus from prevention to runtime

Runtime: The layer where attacks happen

What Darktrace / CLOUD Brings to Runtime Defence

1. Behavioral, real-time detection

2. Automated forensic level artifact collection

3. AI-led investigation

4. Live architectural awareness

Why CNAPP alone isn’t enough

Real-world AWS Scenario: Why Runtime Monitoring Wins

1. External Credential Use

2. AWS CLI Pivot

3. Credential Manipulation

4. Cloud Reconnaissance

5. Privilege Escalation

6. Malicious Compute Deployment

7. Data Access or Tampering

The future of cloud security Is runtime-first