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.

Written by

Sam Lister

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

SOC Analyst

Written by

Connor Mooney

SOC Analyst

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:

Whether the targeted customer had Darktrace/Email
Whether the targeted customer had Darktrace RESPOND/Network
Whether the targeted customer acted in response to Darktrace DETECT/Network alerts

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

Written by

Sam Lister

SOC Analyst

Written by

Connor Mooney

SOC Analyst

Watch the NIS2 Webinar

Blog

August 13, 2025

ISO/IEC 42001: 2023: A milestone in AI standards at Darktrace

Darktrace announces ISO/IEC 42001 accreditation

Darktrace is thrilled to announce that we are one of the first cybersecurity companies to achieve ISO/IEC 42001 accreditation for the responsible management of AI systems. This isn’t just a milestone for us, it’s a sign of where the AI industry is headed. ISO/IEC 42001 is quickly emerging as the global benchmark for separating vendors who truly innovate with AI from those who simply market it.

For customers, it’s more than a badge, it’s assurance that a vendor’s AI is built responsibly, governed with rigor, and backed by the expertise of real AI teams, keeping your data secure while driving meaningful innovation.

This is a critical milestone for Darktrace as we continue to strengthen our offering, mature our governance and compliance frameworks for AI management, expand our research and development capabilities, and further our commitment to the development of responsible AI.

It cements our commitment to providing secure, trustworthy and proactive cybersecurity solutions that our customers can rely on and complements our existing compliance framework, consisting of certifications for:

ISO/IEC 27001:2022 – Information Security Management System
ISO/IEC 27018:2019 – Protection of Personally Identifiable Information in Public Cloud Environments
Cyber Essentials – A UK Government-backed certification scheme for cybersecurity baselines

What is ISO/IEC 42001:2023?

In response to the unique challenges that AI poses, the International Organization for Standardization (ISO) introduced the ISO/IEC 42001:2023 framework in December 2023 to help organizations providing or utilizing AI-based products or services to demonstrate responsible development and use of AI systems. To achieve the accreditation, organizations are required to establish, implement, maintain, and continually improve their Artificial Intelligence Management System (AIMS).

ISO/IEC 42001:2023 is the first of its kind, providing valuable guidance for this rapidly changing field of technology. It addresses the unique ethical and technical challenges AI poses by setting out a structured way to manage risks such as transparency, accuracy and misuse without losing opportunities. By design, it balances the benefits of innovation against the necessity of a proper governance structure.

Being certified means the organization has met the requirements of the ISO/IEC 42001 standard, is conforming to all applicable regulatory and legislative requirements, and has implemented thorough processes to address AI risks and opportunities.

What is the ISO/IEC 42001:2023 accreditation process?

Darktrace partnered with BSI over an 11-month period to undertake the accreditation. The process involved developing and implementing a comprehensive AI management system that builds on our existing certified frameworks, addresses the risks and opportunities of using and developing cutting-edge AI systems, underpins our AI objectives and policies, and meets our regulatory and legal compliance requirements.

The AI Management System, which takes in our people, processes, and products, was extensively audited by BSI against the requirements of the standard, covering all aspects spanning the design of our AI, use of AI within the organization, and our competencies, resources and HR processes. It is an in-depth process that we’re thrilled to have undertaken, making us one of the first in our industry to achieve certification for a globally recognized AI system.

The scope of Darktrace’s certification is particularly wide due to our unique Self-Learning approach to AI for cybersecurity, which uses multi-layered AI systems consisting of varied AI techniques to address distinct cybersecurity tasks. The certification encompasses production and provision of AI systems based on anomaly detection, clustering, classifiers, regressors, neural networks, proprietary and third-party large language models for proactive, detection, response and recovery cybersecurity applications. Darktrace additionally elected to adopt all Annex A controls present in the ISO/IEC 42001 standard.

What are the benefits of an AI Management System?

While AI is not a new or novel concept, the AI industry has accelerated at an unprecedented rate in the past few years, increasing operational efficiency, driving innovation, and automating cumbersome processes in the workplace.

At the same time, the data privacy, security and bias risks created by rapid innovation in AI have been well documented.

Thus, an AI Management System enables organizations to confidently establish and adhere to governance in a way that conforms to best practice, promotes adherence, and is in line with current and emerging regulatory standards.

Not only is this vital in a unique and rapidly evolving field like AI, it additionally helps organization’s balance the drive for innovation with the risks the technology can present, helping to get the best out of their AI development and usage.

What are the key components of ISO/IEC 42001?

The Standard puts an emphasis on responsible AI development and use, requiring organizations to:

Establish and implement an AI Management System
Commit to the responsible development of AI against established, measurable objectives
Have in place a process to manage, monitor and adapt to risks in an effective manner
Commit to continuous improvement of their AI Management System

The AI Standard is similar in composition to other ISO standards, such as ISO/IEC 27001:2022, which many organizations may already be familiar with. Further information as to the structure of ISO/IEC 42001 can be found in Annex A.

What it means for Darktrace’s customers

Our certification against ISO/IEC 42001 demonstrates Darktrace’s commitment to delivering industry-leading Self-Learning AI in the name of cybersecurity resilience. Our stakeholders, customers and partners can be confident that Darktrace is responsibly, ethically and securely developing its AI systems, and is managing the use of AI in our day-to-day operations in a compliant, secure and ethical manner. It means:

‍You can trust our AI: We can demonstrate our AI is developed responsibly, in a transparent manner and in accordance with ethical rules. For more information and to learn about Darktrace's responsible AI in cybersecurity approach, please see here.‍
Our products are backed by innovation and integrity: Darktrace drives cutting edge AI innovation with ethical governance and customer trust at its core. ‍
You are partnering with an organization which stays ahead of regulatory changes: In an evolving AI landscape, partnering with Darktrace helps you to stay prepared for emerging compliance and regulatory demands in your supply chain.

Achieving ISO/IEC 42001:2023 certification is not just a checkpoint for us. It represents our unwavering commitment to setting a higher standard for AI in cybersecurity. It reaffirms our leadership in building and implementing responsible AI and underscores our mission to continuously innovate and lead the way in the industry.

Why ISO/IEC 42001 matters for every AI vendor you trust

In a market where “AI” can mean anything from a true, production-grade system to a thin marketing layer, ISO/IEC 42001 acts as a critical differentiator. Vendors who have earned this certification aren’t just claiming they build responsible AI, they’ve proven it through an independent, rigorous audit of how they design, deploy, and manage their systems.

For you as a customer, that means:

You know their AI is real: Certified vendors have dedicated, skilled AI teams building and maintaining systems that meet measurable standards, not just repackaging off-the-shelf tools with an “AI” label.

Your data is safeguarded: Compliance with ISO/IEC 42001 includes stringent governance over data use, bias, transparency, and risk management.

You’re partnering with innovators: The certification process encourages continuous improvement, meaning your vendor is actively advancing AI capabilities while keeping ethics and security in focus.

In short, ISO/IEC 42001 is quickly becoming the global badge of credible AI development. If your vendor can’t show it, it’s worth asking how they manage AI risk, whether their governance is mature enough, and how they ensure innovation doesn’t outpace accountability.

Annex A: The Structure of ISO/IEC 42001

ISO/IEC 42001 has requirements for which seven adherence is required for an organization seeking to obtain or maintain its certification:

‍Context of the organization – organizations need to demonstrate an understanding of the internal and external factors influencing the organization’s AI Management System.
‍Leadership – senior leadership teams need to be committed to implementing AI governance within their organizations, providing direction and support across all aspects AI Management System lifecycle.‍
Planning – organizations need to put meaningful and manageable processes in place to identify risks and opportunities related to the AI Management System to achieve responsible AI objectives and mitigate identified risks.‍
Support – demonstrating a commitment to provisioning of adequate resources, information, competencies, awareness and communication for the AI Management System is a must to ensure that proper oversight and management of the system and its risks can be achieved.‍
Operation – establishing processes necessary to support the organization’s AI system development and usage, in conformance with the organization’s AI policy, objectives and requirements of the standard. Correcting the course of any deviations within good time is paramount.‍
Performance evaluation – the organization must be able to demonstrate that it has the capability and willingness to regularly monitor and evaluate the performance of the AI Management System effectively, including actioning any corrections and introducing new processes where relevant.‍
Improvement – relying on an existing process will not be sufficient to ensure compliance with the AI Standard. Organizations must commit to monitoring of existing systems and processes to ensure that the AI Management System is continually enhanced and improved.

To assist organizations in seeking the above, four annexes are included within the AI Standard’s rubric, which outline the objectives and measures an organization may wish to implement to address risks related to the design and operation of their AI Management System through the introduction of normative controls. Whilst they are not prescriptive, Darktrace has implemented the requirements of these Annexes to enable it to appropriately demonstrate the effectiveness of its AI Management System. We have placed a heavy emphasis on Annex A which contains these normative controls which we, and other organizations seeking to achieve certification, can align with to address the objectives and measures, such as:

Enforcement of policies related to AI.
Setting responsibilities within the organization, and expectation of roles and responsibilities.
Creating processes and guidelines for escalating and handling AI concerns.
Making resources for AI systems available to users.
Assessing impacts of AI systems internally and externally.
Implementing processes across the entire AI system life cycle.
Understanding treatment of Data for AI systems.
Defining what information is, and should be available, for AI systems.
Considering and defining use cases for the AI systems.
Considering the impact of the AI System on third-party and customer relationships.

The remaining annexes provide guidance on implementing Annex A’s controls, objectives and primary risk sources of AI implementation, and considering how the AI Management System can be used across domains or sectors responsibly.

[related-resource]

About the author

Blog

August 12, 2025

Minimizing Permissions for Cloud Forensics: A Practical Guide to Tightening Access in the Cloud

Most cloud environments are over-permissioned and under-prepared for incident response.

Security teams need access to logs, snapshots, and configuration data to understand how an attack unfolded, but giving blanket access opens the door to insider threats, misconfigurations, and lateral movement.

So, how do you enable forensics without compromising your security posture?

The dilemma: balancing access and security

There is a tension between two crucial aspects of cloud security that create a challenge for cloud forensics.

One aspect is the need for Security Operations Center (SOC) and Incident Response (IR) teams to access comprehensive data for investigating and resolving security incidents.

The other conflicting aspect is the principle of least privilege and minimal manual access advocated by cloud security best practices.

This conflict is particularly pronounced in modern cloud environments, where traditional physical access controls no longer apply, and infrastructure-as-code and containerization have transformed the landscape.

There are several common but less-than-ideal approaches to this challenge:

Accepting limited data access, potentially leaving incidents unresolved
Granting root-level access during major incidents, risking further compromise

Relying on cloud or DevOps teams to retrieve data, causing delays and potential miscommunication

[related-resource]

Challenges in container forensics

Containers present unique challenges for forensic investigations due to their ephemeral and dynamic nature. The orchestration and management of containers, whether on private clusters or using services like AWS Elastic Kubernetes Service (EKS), introduce complexities in capturing and analyzing forensic data.

To effectively investigate containers, it's often necessary to acquire the underlying volume of a node or perform memory captures. However, these actions require specific Identity and Access Management (IAM) and network access to the node, as well as familiarity with the container environment, which may not always be straightforward.

An alternative method of collection in containerized environments is to utilize automated tools to collect this evidence. Since they can detect malicious activity and collect relevant data without needing human input, they can act immediately, securing evidence that might be lost by the time a human analyst is available to collect it manually.

Additionally, automation can help significantly with access and permissions. Instead of analysts needing the correct permissions for the account, service, and node, as well as deep knowledge of the container service itself, for any container from which they wish to collect logs. They can instead collect them, and have them all presented in one place, at the click of a button.

A better approach: practical strategies for cloud forensics

It's crucial to implement strategies that strike a balance between necessary access and stringent security controls.

Here are several key approaches:

1. Dedicated cloud forensics accounts

Establishing a separate cloud account or subscription specifically for forensic activities is foundational. This approach isolates forensic activities from regular operations, preventing potential contamination from compromised environments. Dedicated accounts also enable tighter control over access policies, ensuring that forensic operations do not inadvertently expose sensitive data to unauthorized users.

A separate account allows for:

Isolation: The forensic investigation environment is isolated from potentially compromised environments, reducing the risk of cross-contamination.
Tighter access controls: Policies and controls can be more strictly enforced in a dedicated account, reducing the likelihood of unauthorized access.
Simplified governance: A clear and simplified chain of custody for digital evidence is easier to maintain, ensuring that forensic activities meet legal and regulatory requirements.

For more specifics:

2. Cross-account roles with least privilege

Using cross-account IAM roles, the forensics account can access other accounts, but only with permissions that are strictly necessary for the investigation. This ensures that the principle of least privilege is upheld, reducing the risk of unauthorized access or data exposure during the forensic process.

3. Temporary credentials for just-in-time access

Leveraging temporary credentials, such as AWS STS tokens, allows for just-in-time access during an investigation. These credentials are short-lived and scoped to specific resources, ensuring that access is granted only when absolutely necessary and is automatically revoked after the investigation is completed. This reduces the window of opportunity for potential attackers to exploit elevated permissions.

For AWS, you can use commands such as:

aws sts get-session-token --duration-seconds 43200

aws sts assume-role --role-arn role-to-assume --role-session-name "sts-session-1" --duration-seconds 43200

For Azure, you can use commands such as:

az ad app credential reset --id <appId> --password <sp_password> --end-date 2024-01-01

For more details for Google Cloud environments, see “Create short-lived credentials for a service account” and the request.time parameter.

4. Tag-based access control

Pre-deploying access control based on resource tags is another effective strategy. By tagging resources with identifiers like "Forensics," access can be dynamically granted only to those resources that are relevant to the investigation. This targeted approach minimizes the risk of overexposure and ensures that forensic teams can quickly and efficiently access the data they need.

For example, in AWS:

Condition: StringLike: aws:ResourceTag/Name: ForensicsEnabled

Condition: StringLike: ssm:resourceTag/SSMEnabled: True

For example, in Azure:

"Condition": "StringLike(Resource[Microsoft.Resources/tags.example_key], '*')"

For example, in Google Cloud:

expression: > resource.matchTag('tagKeys/ForensicsEnabled', '*')

Tighten access, enhance security

The shift to cloud environments demands a rethinking of how we approach forensic investigations. By implementing strategies like dedicated cloud forensic accounts, cross-account roles, temporary credentials, and tag-based access control, organizations can strike the right balance between access and security. These practices not only enhance the effectiveness of forensic investigations but also ensure that access is tightly controlled, reducing the risk of exacerbating an incident or compromising the investigation.

Find the right tools for your cloud security

Darktrace delivers a proactive approach to cyber resilience in a single cybersecurity platform, including cloud coverage.

Darktrace’s cloud offerings have been bolstered with the acquisition of Cado Security Ltd., which enables security teams to gain immediate access to forensic-level data in multi-cloud, container, serverless, SaaS, and on-premises environments.

In addition to having these forensics capabilities, Darktrace / CLOUD is a real-time Cloud Detection and Response (CDR) solution built with advanced AI to make cloud security accessible to all security teams and SOCs. By using multiple machine learning techniques, Darktrace brings unprecedented visibility, threat detection, investigation, and incident response to hybrid and multi-cloud environments.

About the author

Your data. Our AI.

Elevate your network security with Darktrace AI

Get a demo

Check out this article by Darktrace: Understanding Qakbot Infections and Attack Paths

Understanding Qakbot Infections and Attack Paths

Qakbot and The Recent Weaponization of OneNote

Observed Activity Chains

Delivery Phase

Command and Control Phase

Cobalt Strike and VNC Phase

Lateral Movement Phase

Darktrace Coverage of QakNote Activity

Conclusion

Appendices

MITRE ATT&CK Mapping

List of IOCs

References

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

ISO/IEC 42001: 2023: A milestone in AI standards at Darktrace

Enjoying the blog?

More in this series

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

2025 Cyber Threat Landscape: Darktrace’s Mid-Year Review

Auto-Color Backdoor: How Darktrace Thwarted a Stealthy Linux Intrusion

Blog

August 13, 2025

ISO/IEC 42001: 2023: A milestone in AI standards at Darktrace

Darktrace announces ISO/IEC 42001 accreditation

What is ISO/IEC 42001:2023?

What is the ISO/IEC 42001:2023 accreditation process?

What are the benefits of an AI Management System?

What are the key components of ISO/IEC 42001?

What it means for Darktrace’s customers

Why ISO/IEC 42001 matters for every AI vendor you trust

Annex A: The Structure of ISO/IEC 42001

Blog

August 12, 2025

Minimizing Permissions for Cloud Forensics: A Practical Guide to Tightening Access in the Cloud

Most cloud environments are over-permissioned and under-prepared for incident response.

The dilemma: balancing access and security

Challenges in container forensics

A better approach: practical strategies for cloud forensics

1. Dedicated cloud forensics accounts

2. Cross-account roles with least privilege

3. Temporary credentials for just-in-time access

4. Tag-based access control

Tighten access, enhance security

Find the right tools for your cloud security