Blog
/
Network
/
April 5, 2023

Understanding Qakbot Infections and Attack Paths

Explore the network-based analysis of Qakbot infections with Darktrace. Learn about the various attack paths used by cybercriminals and Darktrace's response.
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
Sam Lister
Specialist Security Researcher
Written by
Connor Mooney
SOC Analyst
Default blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog image
05
Apr 2023

In an ever-changing threat landscape, security vendors around the world are forced to quickly adapt, react, and respond to known attack vectors and threats. In the face of this, malicious actors are constantly looking for novel ways to gain access to networks. Whether that’s through new exploitations of network vulnerabilities or new delivery methods, attackers and their methods are continually evolving. Although it is valuable for organizations to leverage threat intelligence to keep abreast of known threats to their networks, intelligence alone is not enough to defend against increasingly versatile attackers. Having an autonomous decision maker able to detect and respond to emerging threats, even those employing novel or unknown techniques, is paramount to defend against network compromise.

At the end of January 2023, threat actors began to abuse OneNote attachments to deliver the malware strain, Qakbot, onto users' devices. Widespread adoption of this novel delivery method resulted in a surge in Qakbot infections across Darktrace's customer base between the end of January 2023 and the end of February 2023. Using its Self-Learning AI, Darktrace was able to uncover and respond to these so-called ‘QakNote’ infections as the new trend emerged. Darktrace detected and responded to the threat at multiple stages of the kill chain, preventing damaging and widespread compromise to customer networks.

Qakbot and The Recent Weaponization of OneNote

Qakbot first appeared in 2007 as a banking trojan designed to steal sensitive data such as banking credentials. Since then, Qakbot has evolved into a highly modular, multi-purpose tool, with backdoor, payload delivery, reconnaissance, lateral movement, and data exfiltration capabilities. Although Qakbot's primary delivery method has always been email-based, threat actors have been known to modify their email-based delivery methods of Qakbot in the face of changing circumstances. In the first half of 2022, Microsoft started rolling out versions of Office which block XL4 and VBA macros by default [1]/[2]/[3]. Prior to this change, Qakbot email campaigns typically consisted in the spreading of deceitful emails with Office attachments containing malicious macros. In the face of Microsoft's default blocking of macros, threat actors appeared to cease delivering Qakbot via Office attachments, and shifted to primarily using HTML attachments, through a method known as 'HTML smuggling' [4]/[5]. After the public disclosure [6] of the Follina vulnerability (CVE-2022-30190) in Microsoft Support Diagnostic Tool (MSDT) in May 2022, Qakbot actors were seen capitalizing on the vulnerability to facilitate their email-based delivery of Qakbot payloads [7]/[8]/[9]. 

Given the inclination of Qakbot actors to adapt their email-based delivery methods, it is no surprise that they were quick to capitalize on the novel OneNote-based delivery method which emerged in December 2022. Since December 2022, threat actors have been seen using OneNote attachments to deliver a variety of malware strains, ranging from Formbook [10] to AsynRAT [11] to Emotet [12]. The abuse of OneNote documents to deliver malware is made possible by the fact that OneNote allows for the embedding of executable file types such as HTA files, CMD files, and BAT files. At the end of January 2023, actors started to leverage OneNote attachments to deliver Qakbot [13]/[14]. The adoption of this novel delivery method by Qakbot actors resulted in a surge in Qakbot infections in the wider threat landscape and across the Darktrace customer base.

Observed Activity Chains

Between January 31 and February 24, 2023, Darktrace observed variations of the following pattern of activity across its customer base:

1. User's device contacts OneNote-related endpoint 

2. User's device makes an external GET request with an empty Host header, a target URI whose final segment consists in 5 or 6 digits followed by '.dat', and a User-Agent header referencing either cURL or PowerShell. The GET request is responded to with a DLL file

3. User's device makes SSL connections over ports 443 and 2222 to unusual external endpoints, and makes TCP connections over port 65400 to 23.111.114[.]52

4. User's device makes SSL connections over port 443 to an external host named 'bonsars[.]com' (IP: 194.165.16[.]56) and TCP connections over port 443 to 78.31.67[.]7

5. User’s device makes call to Endpoint Mapper service on internal systems and then connects to the Service Control Manager (SCM) 

6. User's device uploads files with algorithmically generated names and ‘.dll’ or ‘.dll.cfg’ file extensions to SMB shares on internal systems

7. User's device makes Service Control requests to the systems to which it uploaded ‘.dll’ and ‘.dll.cfg’ files 

Further investigation of these chains of activity revealed that they were parts of Qakbot infections initiated via interactions with malicious OneNote attachments. 

Figure 1: Steps of observed QakNote infections.

Delivery Phase

Users' interactions with malicious OneNote attachments, which were evidenced by devices' HTTPS connections to OneNote-related endpoints, such as 'www.onenote[.]com', 'contentsync.onenote[.]com', and 'learningtools.onenote[.]com', resulted in the retrieval of Qakbot DLLs from unusual, external endpoints. In some cases, the user's interaction with the malicious OneNote attachment caused their device to fetch a Qakbot DLL using cURL, whereas, in other cases, it caused their device to download a Qakbot DLL using PowerShell. These different outcomes reflected variations in the contents of the executable files embedded within the weaponized OneNote attachments. In addition to having cURL and PowerShell User-Agent headers, the HTTP requests triggered by interaction with these OneNote attachments had other distinctive features, such as empty host headers and target URIs whose last segment consists in 5 or 6 digits followed by '.dat'. 

Figure 2: Model breach highlighting a user’s device making a HTTP GET request to 198.44.140[.]78 with a PowerShell User-Agent header and the target URI ‘/210/184/187737.dat’.
Figure 3: Model breach highlighting a user’s device making a HTTP GET request to 103.214.71[.]45 with a cURL User-Agent header and the target URI ‘/70802.dat’.
Figure 4: Event Log showing a user’s device making a GET request with a cURL User-Agent header to 185.231.205[.]246 after making an SSL connection to contentsync.onenote[.]com.
Figure 5: Event Log showing a user’s device making a GET request with a cURL User-Agent header to 185.231.205[.]246 after making an SSL connection to www.onenote[.]com.

Command and Control Phase

After fetching Qakbot DLLs, users’ devices were observed making numerous SSL connections over ports 443 and 2222 to highly unusual, external endpoints, as well as large volumes of TCP connections over port 65400 to 23.111.114[.]52. These connections represented Qakbot-infected devices communicating with command and control (C2) infrastructure. Qakbot-infected devices were also seen making intermittent connections to legitimate endpoints, such as 'xfinity[.]com', 'yahoo[.]com', 'verisign[.]com', 'oracle[.]com', and 'broadcom[.]com', likely due to Qakbot making connectivity checks. 

Figure 6: Event Log showing a user’s device contacting Qakbot C2 infrastructure and making connectivity checks to legitimate domains.
Figure 7: Event Log showing a user’s device contacting Qakbot C2 infrastructure and making connectivity checks to legitimate domains.

Cobalt Strike and VNC Phase

After Qakbot-infected devices established communication with C2 servers, they were observed making SSL connections to the external endpoint, bonsars[.]com, and TCP connections to the external endpoint, 78.31.67[.]7. The SSL connections to bonsars[.]com were C2 connections from Cobalt Strike Beacon, and the TCP connections to 78.31.67[.]7 were C2 connections from Qakbot’s Virtual Network Computing (VNC) module [15]/[16]. The occurrence of these connections indicate that actors leveraged Qakbot infections to drop Cobalt Strike Beacon along with a VNC payload onto infected systems. The deployment of Cobalt Strike and VNC likely provided actors with ‘hands-on-keyboard’ access to the Qakbot-infected systems. 

Figure 8: Advanced Search logs showing a user’s device contacting OneNote endpoints, fetching a Qakbot DLL over HTTP, making SSL connections to Qakbot infrastructure and connectivity checks to legitimate domains, and then making SSL connections to the Cobalt Strike endpoint, bonsars[.]com.
Figure 9: Event Log showing a user’s device contacting the Cobalt Strike C2 endpoint, bonsars[.]com, and the VNC C2 endpoint, 78.31.67[.]7, whilst simultaneously contacting the Qakbot C2 endpoint, 47.32.78[.]150.

Lateral Movement Phase

After dropping Cobalt Strike Beacon and a VNC module onto Qakbot-infected systems, actors leveraged their strengthened foothold to connect to the Service Control Manager (SCM) on internal systems in preparation for lateral movement. Before connecting to the SCM, infected systems were seen making calls to the Endpoint Mapper service, likely to identify exposed Microsoft Remote Procedure Call (MSRPC) services on internal systems. The MSRPC service, Service Control Manager (SCM), is known to be abused by Cobalt Strike to create and start services on remote systems. Connections to this service were evidenced by OpenSCManager2  (Opnum: 0x40) and OpenSCManagerW (Opnum: 0xf) calls to the svcctl RPC interface. 

Figure 10: Advanced Search logs showing a user’s device contacting the Endpoint Mapper and Service Control Manager (SCM) services on internal systems. 

After connecting to the SCM on internal systems, infected devices were seen using SMB to distribute files with ‘.dll’ and ‘.dll.cfg’ extensions to SMB shares. These uploads were followed by CreateWowService (Opnum: 0x3c) calls to the svcctl interface, likely intended to execute the uploaded payloads. The naming conventions of the uploaded files indicate that they were Qakbot payloads. 

Figure 11: Advanced Search logs showing a user’s device making Service Control DCE-RPC requests to internal systems after uploading ‘.dll’ and ‘.dll.cfg’ files to them over SMB.

Fortunately, none of the observed QakNote infections escalated further than this. If these infections had escalated, it is likely that they would have resulted in the widespread detonation of additional malicious payloads, such as ransomware.  

Darktrace Coverage of QakNote Activity

Figure 1 shows the steps involved in the QakNote infections observed across Darktrace’s customer base. How far attackers got along this chain was in part determined by the following three factors:

The presence of Darktrace/Email typically stopped QakNote infections from moving past the initial infection stage. The presence of RESPOND/Network significantly slowed down observed activity chains, however, infections left unattended and not mitigated by the security teams were able to progress further along the attack chain. 

Darktrace observed varying properties in the QakNote emails detected across the customer base. OneNote attachments were typically detected as either ‘application/octet-stream’ files or as ‘application/x-tar’ files. In some cases, the weaponized OneNote attachment embedded a malicious file, whereas in other cases, the OneNote file embedded a malicious link (typically a ‘.png’ or ‘.gif’ link) instead. In all cases Darktrace observed, QakNote emails used subject lines starting with ‘RE’ or ‘FW’ to manipulating their recipients into thinking that such emails were part of an existing email chain/thread. In some cases, emails impersonated users known to their recipients by including the names of such users in their header-from personal names. In many cases, QakNote emails appear to have originated from likely hijacked email accounts. These are highly successful methods of social engineering often employed by threat actors to exploit a user’s trust in known contacts or services, convincing them to open malicious emails and making it harder for security tools to detect.

The fact that observed QakNote emails used the fake-reply method, were sent from unknown email accounts, and contained attachments with unusual MIME types, caused such emails to breach the following Darktrace/Email models:

  • Association / Unknown Sender
  • Attachment / Unknown File
  • Attachment / Unsolicited Attachment
  • Attachment / Highly Unusual Mime
  • Attachment / Unsolicited Anomalous Mime
  • Attachment / Unusual Mime for Organisation
  • Unusual / Fake Reply
  • Unusual / Unusual Header TLD
  • Unusual / Fake Reply + Unknown Sender
  • Unusual / Unusual Connection from Unknown
  • Unusual / Off Topic

QakNote emails impersonating known users also breached the following DETECT & RESPOND/Email models:

  • Unusual / Unrelated Personal Name Address
  • Spoof / Basic Known Entity Similarities
  • Spoof / Internal User Similarities
  • Spoof / External User Similarities
  • Spoof / Internal User Similarities + Unrelated Personal Name Address
  • Spoof / External User Similarities + Unrelated Personal Name Address
  • Spoof / Internal User Similarities + Unknown File
  • Spoof / External User Similarities + Fake Reply
  • Spoof / Possible User Spoof from New Address - Enhanced Internal Similarities
  • Spoof / Whale

The actions taken by Darktrace on the observed emails is ultimately determined by Darktrace/Email models are breached. Those emails which did not breach Spoofing models (due to lack of impersonation indicators) received the ‘Convert Attachment’ action. This action converts suspicious attachments into neutralized PDFs, in this case successfully unweaponizing the malicious OneNote attachments. QakNote emails which did breach Spoofing models (due to the presence of impersonation indicators) received the strongest possible action, ‘Hold Message’. This action prevents suspicious emails from reaching the recipients’ mailbox. 

Figure 12: Email log showing a malicious OneNote email (without impersonation indicators) which received a 87% anomaly score, a ‘Move to junk’ action, and a ‘Convert attachment’ actions from Darktrace/Email.
Figure 13: Email log showing a malicious OneNote email (with impersonation indicators) which received an anomaly score of 100% and a ‘Hold message’ action from Darktrace/Email.
Figure 14: Email log showing a malicious OneNote email (with impersonation indicators) which received an anomaly score of 100% and a ‘Hold message’ action from Darktrace/Email.

If threat actors managed to get past the first stage of the QakNote kill chain, likely due to the absence of appropriate email security tools, the execution of the subsequent steps resulted in strong intervention from Darktrace/Network. 

Interactions with malicious OneNote attachments caused their devices to fetch a Qakbot DLL from a remote server via HTTP GET requests with an empty Host header and either a cURL or PowerShell User-Agent header. These unusual HTTP behaviors caused the following Darktrace/Network models to breach:

  • Device / New User Agent
  • Device / New PowerShell User Agent
  • Device / New User Agent and New IP
  • Anomalous Connection / New User Agent to IP Without Hostname
  • Anomalous Connection / Powershell to Rare External
  • Anomalous File / Numeric File Download
  • Anomalous File / EXE from Rare External Location
  • Anomalous File / New User Agent Followed By Numeric File Download

For customers with RESPOND/Network active, these breaches resulted in the following autonomous actions:

  • Enforce group pattern of life for 30 minutes
  • Enforce group pattern of life for 2 hours
  • Block connections to relevant external endpoints over relevant ports for 2 hours   
  • Block all outgoing traffic for 10 minutes
Figure 15: Event Log showing a user’s device receiving Darktrace RESPOND/Network actions after downloading a Qakbot DLL. 
Figure 16: Event Log showing a user’s device receiving Darktrace RESPOND/Network actions after downloading a Qakbot DLL.

Successful, uninterrupted downloads of Qakbot DLLs resulted in connections to Qakbot C2 servers, and subsequently to Cobalt Strike and VNC C2 connections. These C2 activities resulted in breaches of the following DETECT/Network models:

  • Compromise / Suspicious TLS Beaconing To Rare External
  • Compromise / Large Number of Suspicious Successful Connections
  • Compromise / Large Number of Suspicious Failed Connections
  • Compromise / Sustained SSL or HTTP Increase
  • Compromise / Sustained TCP Beaconing Activity To Rare Endpoint
  • Compromise / Beaconing Activity To External Rare
  • Compromise / Slow Beaconing Activity To External Rare
  • Anomalous Connection / Multiple Connections to New External TCP Port
  • Anomalous Connection / Multiple Failed Connections to Rare Endpoint
  • Device / Initial Breach Chain Compromise

For customers with RESPOND/Network active, these breaches caused RESPOND to autonomously perform the following actions:

  • Block connections to relevant external endpoints over relevant ports for 1 hour
Figure 17: Event Log showing a user’s device receiving RESPOND/Network actions after contacting the Qakbot C2 endpoint,  Cobalt Strike C2 endpoint, bonsars[.]com.

In cases where C2 connections were allowed to continue, actors attempted to move laterally through usage of SMB and Service Control Manager. This lateral movement activity caused the following DETECT/Network models to breach:

  • Device / Possible SMB/NTLM Reconnaissance
  • Anomalous Connection / New or Uncommon Service Control 

For customers with RESPOND/Network enabled, these breaches caused RESPOND to autonomously perform the following actions:

  • Block connections to relevant internal endpoints over port 445 for 1 hour
Figure 18: Event Log shows a user’s device receiving RESPOND/Network actions after contacting the Qakbot C2 endpoint, 5.75.205[.]43, and distributing ‘.dll’ and ‘.dll.cfg’ files internally.

The QakNote infections observed across Darktrace’s customer base involved several steps, each of which elicited alerts and autonomous preventative actions from Darktrace. By autonomously investigating the alerts from DETECT, Darktrace’s Cyber AI Analyst was able to connect the distinct steps of observed QakNote infections into single incidents. It then produced incident logs to present in-depth details of the activity it uncovered, provide full visibility for customer security teams.

Figure 19: AI Analyst incident entry showing the steps of a QakNote infection which AI Analyst connected following its autonomous investigations.

Conclusion

Faced with the emerging threat of QakNote infections, Darktrace demonstrated its ability to autonomously detect and respond to arising threats in a constantly evolving threat landscape. The attack chains which Darktrace observed across its customer base involved the delivery of Qakbot via malicious OneNote attachments, the usage of ports 65400 and 2222 for Qakbot C2 communication, the usage of Cobalt Strike Beacon and VNC for ‘hands-on-keyboard’ activity, and the usage of SMB and Service Control Manager for lateral movement. 

Despite the novelty of the OneNote-based delivery method, Darktrace was able to identify QakNote infections across its customer base at various stages of the kill chain, using its autonomous anomaly-based detection to identify unusual activity or deviations from expected behavior. When active, Darktrace/Email neutralized malicious QakNote attachments sent to employees. In cases where Darktrace/Email was not active, Darktrace/Network detected and slowed down the unusual network activities which inevitably ensued from Qakbot infections. Ultimately, this intervention from Darktrace’s products prevented infections from leading to further harmful activity, such as data exfiltration and the detonation of ransomware.

Darktrace is able to offer customers an unparalleled level of network security by combining both Darktrace/Network and Darktrace/Email, safeguarding both their email and network environments. With its suite of products, including DETECT and RESPOND, Darktrace can autonomously uncover threats to customer networks and instantaneously intervene to prevent suspicious activity leading to damaging compromises. 

Appendices

MITRE ATT&CK Mapping 

Initial Access:

T1566.001 – Phishing: Spearphishing Attachment

Execution:

T1204.001 – User Execution: Malicious Link

T1204.002 – User Execution: Malicious File

T1569.002 – System Services: Service Execution

Lateral Movement:

T1021.002 – Remote Services: SMB/Windows Admin Shares

Command and Control:

T1573.002 – Encrypted Channel : Asymmetric Cryptography

T1571 – Non-Standard Port 

T1105 – Ingress Tool Transfer

T1095 –  Non-Application Layer Protocol

T1219 – Remote Access Software

List of IOCs

IP Addresses and/or Domain Names:

- 103.214.71[.]45 - Qakbot download infrastructure 

- 141.164.35[.]94 - Qakbot download infrastructure 

- 95.179.215[.]225 - Qakbot download infrastructure 

- 128.254.207[.]55 - Qakbot download infrastructure

- 141.164.35[.]94 - Qakbot download infrastructure

- 172.96.137[.]149 - Qakbot download infrastructure

- 185.231.205[.]246 - Qakbot download infrastructure

- 216.128.146[.]67 - Qakbot download infrastructure 

- 45.155.37[.]170 - Qakbot download infrastructure

- 85.239.41[.]55 - Qakbot download infrastructure

- 45.67.35[.]108 - Qakbot download infrastructure

- 77.83.199[.]12 - Qakbot download infrastructure 

- 45.77.63[.]210 - Qakbot download infrastructure 

- 198.44.140[.]78 - Qakbot download infrastructure

- 47.32.78[.]150 - Qakbot C2 infrastructure

- 197.204.13[.]52 - Qakbot C2 infrastructure

- 68.108.122[.]180 - Qakbot C2 infrastructure

- 2.50.48[.]213 - Qakbot C2 infrastructure

- 66.180.227[.]60 - Qakbot C2 infrastructure

- 190.206.75[.]58 - Qakbot C2 infrastructure

- 109.150.179[.]236 - Qakbot C2 infrastructure

- 86.202.48[.]142 - Qakbot C2 infrastructure

- 143.159.167[.]159 - Qakbot C2 infrastructure

- 5.75.205[.]43 - Qakbot C2 infrastructure

- 184.176.35[.]223 - Qakbot C2 infrastructure 

- 208.187.122[.]74 - Qakbot C2 infrastructure

- 23.111.114[.]52 - Qakbot C2 infrastructure 

- 74.12.134[.]53 – Qakbot C2 infrastructure

- bonsars[.]com • 194.165.16[.]56 - Cobalt Strike C2 infrastructure 

- 78.31.67[.]7 - VNC C2 infrastructure

Target URIs of GET Requests for Qakbot DLLs:

- /70802.dat 

- /51881.dat

- /12427.dat

- /70136.dat

- /35768.dat

- /41981.dat

- /30622.dat

- /72286.dat

- /46557.dat

- /33006.dat

- /300332.dat

- /703558.dat

- /760433.dat

- /210/184/187737.dat

- /469/387/553748.dat

- /282/535806.dat

User-Agent Headers of GET Requests for Qakbot DLLs:

- curl/7.83.1

- curl/7.55.1

- Mozilla/5.0 (Windows NT; Windows NT 10.0; en-US) WindowsPowerShell/5.1.19041.2364

- Mozilla/5.0 (Windows NT; Windows NT 10.0; en-US) WindowsPowerShell/5.1.17763.3770

- Mozilla/5.0 (Windows NT; Windows NT 10.0; en-GB) WindowsPowerShell/5.1.19041.2364

SHA256 Hashes of Downloaded Qakbot DLLs:  

- 83e9bdce1276d2701ff23b1b3ac7d61afc97937d6392ed6b648b4929dd4b1452

- ca95a5dcd0194e9189b1451fa444f106cbabef3558424d9935262368dba5f2c6 

- fa067ff1116b4c8611eae9ed4d59a19d904a8d3c530b866c680a7efeca83eb3d

- e6853589e42e1ab74548b5445b90a5a21ff0d7f8f4a23730cffe285e2d074d9e

- d864d93b8fd4c5e7fb136224460c7b98f99369fc9418bae57de466d419abeaf6

- c103c24ccb1ff18cd5763a3bb757ea2779a175a045e96acbb8d4c19cc7d84bea

Names of Internally Distributed Qakbot DLLs: 

- rpwpmgycyzghm.dll

- rpwpmgycyzghm.dll.cfg

- guapnluunsub.dll

- guapnluunsub.dll.cfg

- rskgvwfaqxzz.dll

- rskgvwfaqxzz.dll.cfg

- hkfjhcwukhsy.dll

- hkfjhcwukhsy.dll.cfg

- uqailliqbplm.dll

- uqailliqbplm.dll.cfg

- ghmaorgvuzfos.dll

- ghmaorgvuzfos.dll.cfg

Links Found Within Neutralized QakNote Email Attachments:

- hxxps://khatriassociates[.]com/MBt/3.gif

- hxxps://spincotech[.]com/8CoBExd/3.gif

- hxxps://minaato[.]com/tWZVw/3.gif

- hxxps://famille2point0[.]com/oghHO/01.png

- hxxps://sahifatinews[.]com/jZbaw/01.png

- hxxp://87.236.146[.]112/62778.dat

- hxxp://87.236.146[.]112/59076.dat

- hxxp://185.231.205[.]246/73342.dat

References

[1] https://techcommunity.microsoft.com/t5/excel-blog/excel-4-0-xlm-macros-now-restricted-by-default-for-customer/ba-p/3057905

[2] https://techcommunity.microsoft.com/t5/microsoft-365-blog/helping-users-stay-safe-blocking-internet-macros-by-default-in/ba-p/3071805

[3] https://learn.microsoft.com/en-us/deployoffice/security/internet-macros-blocked

[4] https://www.cyfirma.com/outofband/html-smuggling-a-stealthier-approach-to-deliver-malware/

[5] https://www.trustwave.com/en-us/resources/blogs/spiderlabs-blog/html-smuggling-the-hidden-threat-in-your-inbox/

[6] https://twitter.com/nao_sec/status/1530196847679401984

[7] https://www.fortiguard.com/threat-signal-report/4616/qakbot-delivered-through-cve-2022-30190-follina

[8] https://isc.sans.edu/diary/rss/28728

[9] https://darktrace.com/blog/qakbot-resurgence-evolving-along-with-the-emerging-threat-landscape

[10] https://www.trustwave.com/en-us/resources/blogs/spiderlabs-blog/trojanized-onenote-document-leads-to-formbook-malware/

[11] https://www.proofpoint.com/uk/blog/threat-insight/onenote-documents-increasingly-used-to-deliver-malware

[12] https://www.malwarebytes.com/blog/threat-intelligence/2023/03/emotet-onenote

[13] https://blog.cyble.com/2023/02/01/qakbots-evolution-continues-with-new-strategies/

[14] https://news.sophos.com/en-us/2023/02/06/qakbot-onenote-attacks/

[15] https://isc.sans.edu/diary/rss/29210

[16] https://unit42.paloaltonetworks.com/feb-wireshark-quiz-answers/

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
Sam Lister
Specialist Security Researcher
Written by
Connor Mooney
SOC Analyst

More in this series

No items found.

Blog

/

Network

/

April 2, 2026

How Chinese-Nexus Cyber Operations Have Evolved – And What It Means For Cyber Risk and Resilience 

Chinese-Nexus Cyber OperationsDefault blog imageDefault blog image

Cybersecurity has traditionally organized risk around incidents, breaches, campaigns, and threat groups. Those elements still matter—but if we fixate on individual incidents, we risk missing the shaping of the entire ecosystem. Nation‑state–aligned operators are increasingly using cyber operations to establish long-term strategic leverage, not just to execute isolated attacks or short‑term objectives.  

Our latest research, Crimson Echo, shifts the lens accordingly. Instead of dissecting campaigns, malware families, or actor labels as discrete events, the threat research team analyzed Chinese‑nexus activity as a continuum of behaviors over time. That broader view reveals how these operators position themselves within environments: quietly, patiently, and persistently—often preparing the ground long before any recognizable “incident” occurs.  

How Chinese-nexus cyber threats have changed over time

Chinese-nexus cyber activity has evolved in four phases over the past two decades. This ranges from early, high-volume operations in the 1990s and early 2000s to more structured, strategically-aligned activity in the 2010s, and now toward highly adaptive, identity-centric intrusions.  

Today’s phase is defined by scale, operational restraint, and persistence. Attackers are establishing access, evaluating its strategic value, and maintaining it over time. This reflects a broader shift: cyber operations are increasingly integrated into long-term economic and geopolitical strategies. Access to digital environments, specifically those tied to critical national infrastructure, supply chains, and advanced technology, has become a form of strategic leverage for the long-term.  

How Darktrace analysts took a behavioral approach to a complex problem

One of the challenges in analyzing nation-state cyber activity is attribution. Traditional approaches often rely on tracking specific threat groups, malware families, or infrastructure. But these change constantly, and in the case of Chinese-nexus operations, they often overlap.

Crimson Echo is the result of a retrospective analysis of three years of anomalous activity observed across the Darktrace fleet between July 2022 and September 2025. Using behavioral detection, threat hunting, open-source intelligence, and a structured attribution framework (the Darktrace Cybersecurity Attribution Framework), the team identified dozens of medium- to high-confidence cases and analyzed them for recurring operational patterns.  

This long-horizon, behavior-centric approach allows Darktrace to identify consistent patterns in how intrusions unfold, reinforcing that behavioral patterns that matter.  

What the data shows

Several clear trends emerged from the analysis:

  • Targeting is concentrated in strategically important sectors. Across the dataset, 88% of intrusions occurred in organizations classified as critical infrastructure, including transportation, critical manufacturing, telecommunications, government, healthcare, and Information Technology (IT) services.  
  • Strategically important Western economies are a primary focus. The US alone accounted for 22.5% of observed cases, and when combined with major European economies including Germany, Italy, Spain and the UK, over half of all intrusions (55%) were concentrated in these regions.  
  • Nearly 63% of intrusions of intrusions began with the exploitation of internet-facing systems, reinforcing the continued risk posed by externally exposed infrastructure.  

Two models of cyber operations

Across the dataset, Chinese-nexus activity followed two operational models.  

The first is best described as “smash and grab.” These are short-horizon intrusions optimized for speed. Attackers move quickly – often exfiltrating data within 48 hours – and prioritize scale over stealth. The median duration of these compromises is around 10 days. It’s clear they are willing to risk detection for short-term gain.  

The second is “low and slow.” These operations were less prevalent in the dataset, but potentially more consequential. Here, attackers prioritize persistence, establishing durable access through identity systems and legitimate administrative tools, so they can maintain access undetected for months or even years. In one notable case, the actor had fully compromised the environment and established persistence, only to resurface in the environment more than 600 days after. The operational pause underscores both the depth of the intrusion and the actor’s long‑term strategic intent. This suggests that cyber access is a strategic asset to preserve and leverage over time, and we observed these attacks most often inin sectors of the high strategic importance.  

It’s important to note that the same operational ecosystem can employ both models concurrently, selecting the appropriate model based on target value, urgency, intended access. The observation of a “smash and grab” model should not be solely interpreted as a failure of tradecraft, but instead an operational choice likely aligned with objectives. Where “low and slow” operations are optimized for patience, smash and grab is optimized for speed; both seemingly are deliberate operational choices, not necessarily indicators of capability.  

Rethinking cyber risk

For many organizations, cyber risk is still framed as a series of discrete events. Something happens, it is detected and contained, and the organization moves on. But persistent access, particularly in deeply interconnected environments that span cloud, identity-based SaaS and agentic systems, and complex supply chain networks, creates a major ongoing exposure risk. Even in the absence of disruption or data theft, that access can provide insight into operations, dependencies, and strategic decision-making. Cyber risk increasingly resembles long-term competitive intelligence.  

This has impact beyond the Security Operations Center. Organizations need to shift how they think about governance, visibility, and resilience, and treat cyber exposure as a structural business risk instead of an incident response challenge.  

What comes next

The goal of this research is to provide a clearer understanding of how these operations work, so defenders can recognize them earlier and respond more effectively. That includes shifting from tracking indicators to understanding behaviors, treating identity providers as critical infrastructure risks, expanding supplier oversight, investing in rapid containment capabilities, and more.  

Learn more about the findings of Darktrace’s latest research, Crimson Echo: Understanding Chinese-nexus Cyber Operations Through Behavioral Analysis, by downloading the full report and summaries for business leaders, CISOs, and SOC analysts here.  

Continue reading
About the author
Nathaniel Jones
VP, Security & AI Strategy, Field CISO

Blog

/

Proactive Security

/

April 1, 2026

AI-powered security for a rapidly growing grocery enterprise

Default blog imageDefault blog image

Protecting a complex, fast-growing retail organization

For this multi-banner grocery holding organization, cybersecurity is considered an essential business enabler, protecting operations, growth, and customer trust. The organization’s lean IT team manages a highly distributed environment spanning corporate offices, 100+ stores, distribution centers and  thousands of endpoints, users, and third-party connections.

Mergers and acquisitions fueled rapid growth, but they also introduced escalating complexity that constrained visibility into users, endpoints, and security risks inherited across acquired environments.

Closing critical visibility gaps with limited resources

Enterprise-wide visibility is a top priority for the organization, says the  Vice President of Information Technology. “We needed insights beyond the perimeter into how users and devices were behaving across the organization.”

A security breach that occurred before the current IT leadership joined the company reinforced the urgency and elevated cybersecurity to an executive-level priority with a focus on protecting customer trust. The goal was to build a multi-layered security model that could deliver autonomous, enterprise-wide protection without adding headcount.

Managing cyber risk in M&A

Mergers and acquisitions are central to the grocery holding company’s growth strategy. But each transaction introduces new cyber risk, including inherited network architectures, inconsistent tooling, excessive privileges, and remnants of prior security incidents that were never fully remediated.

“Our M&A targets range from small chains with a single IT person and limited cyber tools to large chains with more developed IT teams, toolsets and instrumentation,” explains the VP of IT. “We needed a fast, repeatable, and reliable way to assess cyber risk before transactions closed.”

AI-driven security built for scale, speed, and resilience

Rather than layering additional point tools onto an already complex environment, the retailer adopted the Darktrace ActiveAI Security Platform™ in 2020 as part of a broader modernization effort to improve resilience, close visibility gaps, and establish a security foundation that could scale with growth.

“Darktrace’s AI-driven approach provided the ideal solution to these challenges,” shares the VP of IT. “It has empowered our organization to maintain a robust security strategy, ensuring the protection of our network and the smooth operation of our business.”

Enterprise-wide visibility into traffic  

By monitoring both north-south and east-west traffic and applying Self-Learning AI, Darktrace develops a dynamic understanding of how users and devices normally behave across locations, roles, and systems.

“Modeling normal behavior across the environment enables us to quickly spot behavior that doesn’t fit. Even subtle changes that could signal a threat but appear legitimate at first glance,” explains the VP of IT.

Real-time threat containment, 24/7

Adopting autonomous response has created operational breathing room for the security team, says the company’s Cybersecurity  Engineer.

“Early on, we enabled full Darktrace autonomous mode and we continue to do so today,” shares the IT Security Architect. “Allowing the technology to act first gives us the time we need to investigate incidents during business hours without putting the business at risk.”

Unified, actionable view of security ecosystem

The grocery retailer integrated Darktrace with its existing security ecosystem of firewalls, vulnerability management tools, and endpoint detection and response, and the VP of IT described the adoption process as “exceptionally smooth.”

The team can correlate enterprise-wide security data for a unified and actionable picture of all activity and risk. Using this “single pane of glass” approach, the retailer trains Level 1 and Level 2 operations staff to assist with investigations and user follow-ups, effectively extending the reach of the security function without expanding headcount.

From reactive defense to security at scale

With Darktrace delivering continuous visibility, autonomous containment, and integrated security workflows, the organization has strengthened its cybersecurity posture while improving operational efficiency. The result is a security model that not only reduces risk, but also supports growth, resilience, and informed decision-making at the business level.

Faster detection, faster resolution

With autonomous detection and response, the retailer can immediately contain risk while analysts investigate and validate activity. With this approach, the company can maintain continuous protection even outside business hours and reduce the chance of lateral spread across systems or locations.

Enterprise-grade protection with a lean team

From cloud environments to clients to SaaS collaboration tools, Darktrace provides holistic autonomous AI defense, processing petabytes of the organization’s network traffic and investigating millions of individual events that could be indicative of a wider incident.

Today, Darktrace autonomously conducts the majority of all investigations on behalf of the IT team, escalating only a tiny fraction for analyst review. The impact has been profound, freeing analysts from endless alerts and hours of triage so they can focus on more valuable, proactive, and gratifying work.

“From an operational perspective, Darktrace gives us time back,” says the Cybersecurity Engineer. More importantly, says the VP of IT, “it gives us peace of mind that we’re protected even if we’re not actively monitoring every alert.”

A strategic input for M&A decision-making

One of the most strategic outcomes has been the role of cybersecurity on M&A. 90 days prior to closing a transaction, the security team uses Darktrace alongside other tools to perform a cyber risk assessment of the potential acquisition. “Our approach with Darktrace has consistently identified gaps and exposed risks,” says the VP of IT, including:

  • Remnants of previous incidents that were never fully remediated
  • Network configurations with direct internet exposure
  • Excessive administrative privileges in Active Directory or on critical hosts

While security findings may not alter deal timelines, the VP of IT says they can have enormous business implications. “With early visibility into these risks, we can reduce exposure to inherited cyber threats, strengthen our position during negotiations, and establish clear remediation requirements.”

A security strategy built to evolve with the business

As the holding group expands its cloud footprint, it will extend Darktrace protections into Azure, applying the same AI-driven visibility and autonomous response to cloud workloads. The VP of IT says Darktrace's evolving capabilities will be instrumental in addressing the organization’s future cybersecurity needs and ability to adapt to the dynamic nature of cloud security.

“With Darktrace’s AI-driven approach, we have moved beyond reactive defense, establishing a resilient security foundation for confident expansion and modernization.”

Continue reading
About the author
Your data. Our AI.
Elevate your network security with Darktrace AI