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July 26, 2022

Self-Learning AI for Zero-Day and N-Day Attack Defense

Explore the differences between zero-day and n-day attacks on different customer servers to learn how Darktrace detects and prevents cyber threats effectively.
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
Lewis Morgan
Cyber Analyst
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26
Jul 2022

Key Terms:

Zero-day | A recently discovered security vulnerability in computer software that has no currently available fix or patch. Its name come from the reality that vendors have “zero days” to act and respond.

N-day | A vulnerability that emerges in computer software in which a vendor is aware and may have already issued (or are currently working on) a patch or fix. Active exploits often already exist and await abuse by nefarious actors.

Traditional security solutions often apply signature-based-detection when identifying cyber threats, helping to defend against legacy attacks but consequently missing novel ones. Therefore, security teams often lend a lot of focus to ensuring that the risk of zero-day vulnerabilities is reduced [1]. As explored in this blog, however, organizations can face just as much of a risk from n-day attacks, since they invite the most attention from malicious actors [2]. This is due in part to the reduced complexity, cost and time invested in researching and finding new exploits compared with that found when attackers exploit zero-days. 

This blog will examine both a zero-day and n-day attack that two different Darktrace customers faced in the fall of 2021. This will include the activity Darktrace detected, along with the steps taken by Darktrace/Network to intervene. It will then compare the incidents, discuss the possible dangers of third-party integrations, and assess the deprecation of legacy security tools.

Revisiting zero-day attacks 

Zero-days are among the greatest concerns security teams face in the era of modern technology and networking. Defending critical systems from zero-day compromises is a task most legacy security solutions are often unable to handle. Due to the complexity of uncovering new security flaws and developing elaborate code that can exploit them, these attacks are often carried out by funded or experienced groups such as nation-state actors and APTs. One of history’s most prolific zero-days, ‘Stuxnet’, sent security teams worldwide into a global panic in 2010. This involved a widespread attack on Iranian nuclear infrastructure and was widely accepted to be a result of nation-state actors [3]. The Stuxnet worm took advantage of four zero-day exploits, compromising over 200,000 devices and physically damaging around 10% of the 9,000 critical centrifuges at the Natanz nuclear site. 

More recently, 2021 saw the emergence of several critical zero-day vulnerabilities within SonicWall’s product suite [4]. SonicWall is a security hardware manufacturer that provides hardware firewall devices, unified threat management, VPN gateways and network security solutions. Some of these vulnerabilities lie within their Secure Mobile Access (SMA) 100 series (for example, CVE-2019-7481, CVE-2021-20016 and CVE-2021-20038 to name a few). These directly affected VPN devices and often allowed attackers easy remote access to company devices. CVE-2021-20016 in particular incorporates an SQL-Injection vulnerability within SonicWall’s SSL VPN SMA 100 product line [5]. If exploited, this defect would allow an unauthenticated remote attacker to perform their own malicious SQL query in order to access usernames, passwords and other session related information. 

The N-day underdog

The shadow cast by zero-day attacks often shrouds that of n-day attacks. N-days, however, often pose an equal - if not greater - risk to the majority of organizations, particularly those in industrial sectors. Since these vulnerabilities have fixes available, all of the hard work around research is already done; malicious actors only need to view proof of concepts (POCs) or, if proficient in coding, reverse-engineer software to reveal code-changes (binary diffing) in order to exploit these security flaws in the wild. These vulnerabilities are typically attributed to opportunistic hackers and script-kiddies, where little research or heavy lifting is required.  

August 2021 gave rise to a critical vulnerability in Atlassian Confluence servers, namely CVE-2021-26084 [6]. Confluence is a widely used collaboration wiki tool and knowledge-sharing platform. As introduced and discussed a few months ago in a previous Darktrace blog (Explore Internet-Facing System Vulnerabilities), this vulnerability allows attackers to remotely execute code on internet-facing servers after exploiting injection vulnerabilities in Object-Graph Navigation Language (OGNL). Whilst Confluence had patches and fixes available to users, attackers still jumped on this opportunity and began scanning the internet for signs of critical devices serving this outdated software [7]. Once identified, they would  exploit the vulnerability, often installing crypto mining software onto the device. More recently, Darktrace explored a new vulnerability (CVE-2022-26134), disclosed midway through 2022, that affected Confluence servers and data centers using similar techniques to that found in CVE-2021-26084 [8]. 

SonicWall in the wild – 1. Zero-day attack

At the beginning of August 2021, Darktrace prevented an attack from taking place within a European automotive customer’s environment (Figure 1). The attack targeted a vulnerable internet-facing SonicWall VPN server, and while the attacker’s motive remains unclear, similar historic events suggest that they intended to perform ransomware encryption or data exfiltration. 

Figure 1: Timeline of the SonicWall attack 

Darktrace was unable to confirm the definite tactics, techniques and procedures (TTPs) used by the attacker to compromise the customer’s environment, as the device was compromised before Darktrace installation and coverage. However, from looking at recently disclosed SonicWall VPN vulnerabilities and patterns of behaviour, it is likely CVE-2021-20016 played a part. At some point after this initial infection, it is also believed the device was able to move laterally to a domain controller (DC) using administrative credentials; it was this server that then initiated the anomalous activity that Darktrace detected and alerted on. 

On August 5th 2021 , Darktrace observed this compromised domain controller engaging in unusual ICMP scanning - a protocol used to discover active devices within an environment and create a map of an organization’s network topology. Shortly after, the infected server began scanning devices for open RDP ports and enumerating SMB shares using unorthodox methods. SMB delete and HTTP requests (over port 445 and 80 respectively) were made for files named delete.me in the root directory of numerous network shares using the user agent Microsoft WebDAV. However, no such files appeared to exist within the environment. This may have been the result of an attacker probing devices in the network in an effort to see their responses and gather information on properties and vulnerabilities they could later exploit. 

Soon the infected DC began establishing RDP tunnels back to the VPN server and making requests to an internal DNS server for multiple endpoints relating to exploit kits, likely in an effort to strengthen the attacker’s foothold within the environment. Some of the endpoints requested relate to:

-       EternalBlue vulnerability 

-       Petit Potam NTLM hash attack tool

-       Unusual GitHub repositories

-       Unusual Python repositories  

The DC made outgoing NTLM requests to other internal devices, implying the successful installation of Petit Potam exploitation tools. The server then began performing NTLM reconnaissance, making over 1,000 successful logins under ‘Administrator’ to several other internal devices. Around the same time, the device was also seen making anonymous SMBv1 logins to numerous internal devices, (possibly symptomatic of the attacker probing machines for EternalBlue vulnerabilities). 

Interestingly, the device also made numerous failed authentication attempts using a spoofed credential for one of the organization’s security managers. This was likely in an attempt to hide themselves using ‘Living off the Land’ (LotL) techniques. However, whilst the attacker clearly did their research on the company, they failed to acknowledge the typical naming convention used for credentials within the environment. This ultimately backfired and made the compromise more obvious and unusual. 

In the morning of the following day, the initially compromised VPN server began conducting further reconnaissance, engaging in similar activity to that observed by the domain controller. Until now, the customer had set Darktrace RESPOND to run in human confirmation mode, meaning interventions were not made autonomously but required confirmation by a member of the internal security team. However, thanks to Proactive Threat Notifications (PTNs) delivered by Darktrace’s dedicated SOC team, the customer was made immediately aware of this unusual behaviour, allowing them to apply manual Darktrace RESPOND blocks to all outgoing connections (Figure 2). This gave the security team enough time to respond and remediate before serious damage could be done.

Figure 2: Darktrace RESPOND model breach showing the manually applied “Quarantine Device” action taken against the compromised VPN server. This screenshot displays the UI from Darktrace version 5.1

Confluence in the wild – 2. N-day attack

Towards the end of 2021, Darktrace saw a European broadcasting customer leave an Atlassian Confluence internet-facing server unpatched and vulnerable to crypto-mining malware using CVE-2021-26084. Thanks to Darktrace, this attack was entirely immobilized within only a few hours of the initial infection, protecting the organization from damage (Figure 3). 

Figure 3: Timeline of the Confluence attack

On midday on September 1st 2021, an unpatched Confluence server was seen receiving SSL connections over port 443 from a suspicious new endpoint, 178.238.226[.]127.  The connections were encrypted, meaning Darktrace was unable to view the contents and ascertain what requests were being made. However, with the disclosure of CVE-2021-26084 just 7 days prior to this activity, it is likely that the TTPs used involved injecting OGNL expressions to Confluence server memory; allowing the attacker to remotely execute code on the vulnerable server.

Immediately after successful exploitation of the Confluence server, the infected device was observed making outgoing HTTP GET requests to several external endpoints using a new user agent (curl/7.61.1). Curl was used to silently download and configure multiple suspicious files relating to XMRig cryptocurrency miner, including ld.sh, XMRig and config.json. Subsequent outgoing connections were then made to europe.randomx-hub.miningpoolhub[.]com · 172.105.210[.]117 using the JSON-RPC protocol, seen alongside the mining credential maillocal.confluence (Figure 4). Only 3 seconds after initial compromise, the infected device began attempting to mine cryptocurrency using the Minergate protocol but was instantly and autonomously blocked by Darktrace RESPOND. This prevented the server from abusing system resources and generating profits for the attacker.

Figure 4: A graph showing the frequency of external connections using the JSON-RPC protocol made by the breach device over a 48-hour window. The orange-red dots represent models that breached as a result of this activity, demonstrating the “waterfall” effect commonly seen when a device suffers a compromise. This screenshot displays the UI from Darktrace version 5.1

In the afternoon, the malware persisted with its infection. The compromised server began making successive HTTP GET requests to a new rare endpoint 195.19.192[.]28 using the same curl user agent (Figures 5 & 6). These requests were for executable and dynamic library files associated with Kinsing malware (but fortunately were also blocked by Darktrace RESPOND). Kinsing is a malware strain found in numerous attack campaigns which is often associated with crypto-jacking, and has appeared in previous Darktrace blogs [9].

Figure 5: Cyber AI Analyst summarising the unusual download of Kinsing software using the new curl user agent. This screenshot displays the UI from Darktrace version 5.1

The attacker then began making HTTP POST requests to an IP 185.154.53[.]140, using the same curl user agent; likely a method for the attacker to maintain persistence within the network and establish a foothold using its C2 infrastructure. The Confluence server was then again seen attempting to mine cryptocurrency using the Minergate protocol. It made outgoing JSON-RPC connections to a different new endpoint, 45.129.2[.]107, using the following mining credential: ‘42J8CF9sQoP9pMbvtcLgTxdA2KN4ZMUVWJk6HJDWzixDLmU2Ar47PUNS5XHv4Kmfdh8aA9fbZmKHwfmFo8Wup8YtS5Kdqh2’. This was once again blocked by Darktrace RESPOND (Figure 7). 

Figure 6: VirusTotal showing the unusualness of one of these external IPs [10]
Figure 7: Log data showing the action taken by Darktrace RESPOND in response to the device breaching the “Crypto Currency Mining Activity” model. This screenshot displays the UI from Darktrace version 5.1

The final activity seen from this device involved the download of additional shell scripts over HTTP associated with Kinsing, namely spre.sh and unk.sh, from 194.38.20[.]199 and 195.3.146[.]118 respectively (Figure 8). A new user agent (Wget/1.19.5 (linux-gnu)) was used when connecting to the latter endpoint, which also began concurrently initiating repeated connections indicative of C2 beaconing. These scripts help to spread the Kinsing malware laterally within the environment and may have been the attacker's last ditch efforts at furthering their compromise before Darktrace RESPOND blocked all connections from the infected Confluence server [11]. With Darktrace RESPOND's successful actions, the customer’s security team were then able to perform their own response and remediation. 

Figure 8: Cyber AI Analyst revealing the last ditch efforts made by the threat actor to download further malicious software. This screenshot displays the UI from Darktrace version 5.1

Darktrace Coverage: N- vs Zero-days

In the SonicWall case the attacker was unable to achieve their actions on objectives (thanks to Darktrace's intervention). However, this incident displayed tactics of a more stealthy and sophisticated attacker - they had an exploited machine but waited for the right moment to execute their malicious code and initiate a full compromise. Due to the lack of visibility over attacker motive, it is difficult to deduce what type of actor led to this intrusion. However, with the disclosure of a zero-day vulnerability (CVE-2021-20016) not long before this attack, along with a seemingly dormant initially compromised device, it is highly possible that it was carried out by a sophisticated cyber criminal or gang. 

On the other hand, the Confluence case engaged in a slightly more noisy approach; it dropped crypto mining malware on vulnerable devices in the hope that the target’s security team did not maintain visibility over their network or would merely turn a blind eye. The files downloaded and credentials observed alongside the mining activity heavily imply the use of Kinsing malware [11]. Since this vulnerability (CVE-2021-26084) emerged as an n-day attack with likely easily accessible POCs, as well as there being a lack of LotL techniques and the motive being long term monetary gain, it is possible this attack was conducted by a less sophisticated or amateur actor (script-kiddie); one that opportunistically exploits known vulnerabilities in internet-facing devices in order to make a quick profit [12].

Whilst Darktrace RESPOND was enabled in human confirmation mode only during the start of the SonicWall attack, Darktrace’s Cyber AI Analyst still offered invaluable insight into the unusual activity associated with the infected machines during both the Confluence and SonicWall compromises. SOC analysts were able to see these uncharacteristic behaviours and escalate the incident through Darktrace’s PTN and ATE services. Analysts then worked through these tickets with the customers, providing support and guidance and, in the SonicWall case, quickly helping to configure Darktrace RESPOND. In both scenarios, Darktrace RESPOND was able to block abnormal connections and enforce a device’s pattern of life, affording the security team enough time to isolate the infected machines and prevent further threats such as ransomware detonation or data exfiltration. 

Concluding thoughts and dangers of third-party integrations 

Organizations with internet-facing devices will inevitably suffer opportunistic zero-day and n-day attacks. While little can be done to remove the risk of zero-days entirely, ensuring that organizations keep their systems up to date will at the very least help prevent opportunistic and script-kiddies from exploiting n-day vulnerabilities.  

However, it is often not always possible for organizations to keep their systems up to date, especially for those who require continuous availability. This may also pose issues for organizations that rely on, and put their trust in, third party integrations such as those explored in this blog (Confluence and SonicWall), as enforcing secure software is almost entirely out of their hands. Moreover, with the rising prevalence of remote working, it is essential now more than ever that organizations ensure their VPN devices are shielded from external threats, guidance on which has been released by the NSA/CISA [13].

These two case studies have shown that whilst organizations can configure their networks and firewalls to help identify known indicators of compromise (IoC), this ‘rearview mirror’ approach will not account for, or protect against, any new and undisclosed IoCs. With the aid of Self-Learning AI and anomaly detection, Darktrace can detect the slightest deviation from a device’s normal pattern of life and respond autonomously without the need for rules and signatures. This allows for the disruption and prevention of known and novel attacks before irreparable damage is caused- reassuring security teams that their digital estates are secure. 

Thanks to Paul Jennings for his contributions to this blog.

Appendices: SonicWall (Zero-day)

Darktrace model detections

·      AIA / Suspicious Chain of Administrative Credentials

·      Anomalous Connection / Active Remote Desktop Tunnel

·      Anomalous Connection / SMB Enumeration

·      Anomalous Connection / Unusual Internal Remote Desktop

·      Compliance / High Priority Compliance Model Breach

·      Compliance / Outgoing NTLM Request from DC

·      Device / Anomalous RDP Followed By Multiple Model Breaches

·      Device / Anomalous SMB Followed By Multiple Model Breaches

·      Device / ICMP Address Scan

·      Device / Large Number of Model Breaches

·      Device / Large Number of Model Breaches from Critical Network Device

·      Device / Multiple Lateral Movement Model Breaches (PTN/Enhanced Monitoring model)

·      Device / Network Scan

·      Device / Possible SMB/NTLM Reconnaissance

·      Device / RDP Scan

·      Device / Reverse DNS Sweep

·      Device / SMB Session Bruteforce

·      Device / Suspicious Network Scan Activity (PTN/Enhanced Monitoring model)

·      Unusual Activity / Possible RPC Recon Activity

Darktrace RESPOND (Antigena) actions (as displayed in example)

·      Antigena / Network / Manual / Quarantine Device

MITRE ATT&CK Techniques Observed
IoCs

Appendices: Confluence (N-day)

Darktrace model detections

·      Anomalous Connection / New User Agent to IP Without Hostname

·      Anomalous Connection / Posting HTTP to IP Without Hostname

·      Anomalous File / EXE from Rare External Location

·      Anomalous File / Script from Rare Location

·      Compliance / Crypto Currency Mining Activity

·      Compromise / High Priority Crypto Currency Mining (PTN/Enhanced Monitoring model)

·      Device / Initial Breach Chain Compromise (PTN/Enhanced Monitoring model)

·      Device / Internet Facing Device with High Priority Alert

·      Device / New User Agent

Darktrace RESPOND (Antigena) actions (displayed in example)

·      Antigena / Network / Compliance / Antigena Crypto Currency Mining Block

·      Antigena / Network / External Threat / Antigena File then New Outbound Block

·      Antigena / Network / External Threat / Antigena Suspicious Activity Block

·      Antigena / Network / External Threat / Antigena Suspicious File Block

·      Antigena / Network / Significant Anomaly / Antigena Block Enhanced Monitoring

MITRE ATT&CK Techniques Observed
IOCs

References:

[1] https://securitybrief.asia/story/why-preventing-zero-day-attacks-is-crucial-for-businesses

[2] https://electricenergyonline.com/energy/magazine/1150/article/Security-Sessions-More-Dangerous-Than-Zero-Days-The-N-Day-Threat.htm

[3] https://www.wired.com/2014/11/countdown-to-zero-day-stuxnet/

[4] https://cve.mitre.org/cgi-bin/cvekey.cgi?keyword=SonicWall+2021 

[5] https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2021-20016

[6] https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2021-26084

[7] https://www.zdnet.com/article/us-cybercom-says-mass-exploitation-of-atlassian-confluence-vulnerability-ongoing-and-expected-to-accelerate/

[8] https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-26134

[9] https://attack.mitre.org/software/S0599/

[10] https://www.virustotal.com/gui/ip-address/195.19.192.28/detection 

[11] https://sysdig.com/blog/zoom-into-kinsing-kdevtmpfsi/

[12] https://github.com/alt3kx/CVE-2021-26084_PoC

[13] https://www.nsa.gov/Press-Room/Press-Releases-Statements/Press-Release-View/Article/2791320/nsa-cisa-release-guidance-on-selecting-and-hardening-remote-access-vpns/

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
Lewis Morgan
Cyber Analyst

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October 15, 2025

How a Major Civil Engineering Company Reduced MTTR across Network, Email and the Cloud with Darktrace

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Asking more of the information security team

“What more can we be doing to secure the company?” is a great question for any cyber professional to hear from their Board of Directors. After successfully defeating a series of attacks and seeing the potential for AI tools to supercharge incoming threats, a UK-based civil engineering company’s security team had the answer: Darktrace.

“When things are coming at you at machine speed, you need machine speed to fight it off – it’s as simple as that,” said their Information Security Manager. “There were incidents where it took us a few hours to get to the bottom of what was going on. Darktrace changed that.”

Prevention was also the best cure. A peer organization in the same sector was still in business continuity measures 18 months after an attack, and the security team did not want to risk that level of business disruption.

Legacy tools were not meeting the team’s desired speed or accuracy

The company’s native SaaS email platform took between two and 14 days to alert on suspicious emails, with another email security tool flagging malicious emails after up to 24 days. After receiving an alert, responses often took a couple of days to coordinate. The team was losing precious time.

Beyond long detection and response times, the old email security platform was no longer performing: 19% of incoming spam was missed. Of even more concern: 6% of phishing emails reached users’ inboxes, and malware and ransomware email was also still getting through, with 0.3% of such email-borne payloads reaching user inboxes.

Choosing Darktrace

“When evaluating tools in 2023, only Darktrace had what I was looking for: an existing, mature, AI-based cybersecurity solution. ChatGPT had just come out and a lot of companies were saying ‘AI this’ and ‘AI that’. Then you’d take a look, and it was all rules- and cases-based, not AI at all,” their Information Security Manager.

The team knew that, with AI-enabled attacks on the horizon, a cybersecurity company that had already built, fielded, and matured an AI-powered cyber defense would give the security team the ability to fend off machine-speed attacks at the same pace as the attackers.

Darktrace accomplishes this with multi-layered AI that learns each organization’s normal business operations. With this detailed level of understanding, Darktrace’s Self-Learning AI can recognize unusual activity that may indicate a cyber-attack, and works to neutralize the threat with precise response actions. And it does this all at machine speed and with minimal disruption.

On the morning the team was due to present its findings, the session was cancelled – for a good reason. The Board didn’t feel further discussion was necessary because the case for Darktrace was so conclusive. The CEO described the Darktrace option as ‘an insurance policy we can’t do without’.

Saving time with Darktrace / EMAIL

Darktrace / EMAIL reduced the discovery, alert, and response process from days or weeks to seconds .

Darktrace / EMAIL automates what was originally a time-consuming and repetitive process. The team has recovered between eight and 10 working hours a week by automating much of this process using / EMAIL.

Today, Darktrace / EMAIL prevents phishing emails from reaching employees’ inboxes. The volume of hostile and unsolicited email fell to a third of its original level after Darktrace / EMAIL was set up.

Further savings with Darktrace / NETWORK and Darktrace / IDENTITY

Since its success with Darktrace / EMAIL, the company adopted two more products from the Darktrace ActiveAI Security Platform – Darktrace / NETWORK and Darktrace / IDENTITY.

These have further contributed to cost savings. An initial plan to build a 24/7 SOC would have required hiring and retaining six additional analysts, rather than the two that currently use Darktrace, costing an additional £220,000 per year in salary. With Darktrace, the existing analysts have the tools needed to become more effective and impactful.

An additional benefit: Darktrace adoption has lowered the company’s cyber insurance premiums. The security team can reallocate this budget to proactive projects.

Detection of novel threats provides reassurance

Darktrace’s unique approach to cybersecurity added a key benefit. The team’s previous tool took a rules-based approach – which was only good if the next attack featured the same characteristics as the ones on which the tool was trained.

“Darktrace looks for anomalous behavior, and we needed something that detected and responded based on use cases, not rules that might be out of date or too prescriptive,” their Information Security Manager. “Our existing provider could take a couple of days to update rules and signatures, and in this game, speed is of the essence. Darktrace just does everything we need - without delay.”

Where rules-based tools must wait for a threat to emerge before beginning to detect and respond to it, Darktrace identifies and protects against unknown and novel threats, speeding identification, response, and recovery, minimizing business disruption as a result.

Looking to the future

With Darktrace in place, the UK-based civil engineering company team has reallocated time and resources usually spent on detection and alerting to now tackle more sophisticated, strategic challenges. Darktrace has also equipped the team with far better and more regularly updated visibility into potential vulnerabilities.

“One thing that frustrates me a little is penetration testing; our ISO accreditation mandates a penetration test at least once a year, but the results could be out of date the next day,” their Information Security Manager. “Darktrace / Proactive Exposure Management will give me that view in real time – we can run it daily if needed - and that’s going to be a really effective workbench for my team.”

As the company looks to further develop its security posture, Darktrace remains poised to evolve alongside its partner.

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October 14, 2025

Inside Akira’s SonicWall Campaign: Darktrace’s Detection and Response

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Introduction: Background on Akira SonicWall campaign

Between July and August 2025, security teams worldwide observed a surge in Akira ransomware incidents involving SonicWall SSL VPN devices [1]. Initially believed to be the result of an unknown zero-day vulnerability, SonicWall later released an advisory announcing that the activity was strongly linked to a previously disclosed vulnerability, CVE-2024-40766, first identified over a year earlier [2].

On August 20, 2025, Darktrace observed unusual activity on the network of a customer in the US. Darktrace detected a range of suspicious activity, including network scanning and reconnaissance, lateral movement, privilege escalation, and data exfiltration. One of the compromised devices was later identified as a SonicWall virtual private network (VPN) server, suggesting that the incident was part of the broader Akira ransomware campaign targeting SonicWall technology.

As the customer was subscribed to the Managed Detection and Response (MDR) service, Darktrace’s Security Operations Centre (SOC) team was able to rapidly triage critical alerts, restrict the activity of affected devices, and notify the customer of the threat. As a result, the impact of the attack was limited - approximately 2 GiB of data had been observed leaving the network, but any further escalation of malicious activity was stopped.

Threat Overview

CVE-2024-40766 and other misconfigurations

CVE-2024-40766 is an improper access control vulnerability in SonicWall’s SonicOS, affecting Gen 5, Gen 6, and Gen 7 devices running SonicOS version 7.0.1 5035 and earlier [3]. The vulnerability was disclosed on August 23, 2024, with a patch released the same day. Shortly after, it was reported to be exploited in the wild by Akira ransomware affiliates and others [4].

Almost a year later, the same vulnerability is being actively targeted again by the Akira ransomware group. In addition to exploiting unpatched devices affected by CVE-2024-40766, security researchers have identified three other risks potentially being leveraged by the group [5]:

*The Virtual Office Portal can be used to initially set up MFA/TOTP configurations for SSLVPN users.

Thus, even if SonicWall devices were patched, threat actors could still target them for initial access by reusing previously stolen credentials and exploiting other misconfigurations.

Akira Ransomware

Akira ransomware was first observed in the wild in March 2023 and has since become one of the most prolific ransomware strains across the threat landscape [6]. The group operates under a Ransomware-as-a-Service (RaaS) model and frequently uses double extortion tactics, pressuring victims to pay not only to decrypt files but also to prevent the public release of sensitive exfiltrated data.

The ransomware initially targeted Windows systems, but a Linux variant was later observed targeting VMware ESXi virtual machines [7]. In 2024, it was assessed that Akira would continue to target ESXi hypervisors, making attacks highly disruptive due to the central role of virtualisation in large-scale cloud deployments. Encrypting the ESXi file system enables rapid and widespread encryption with minimal lateral movement or credential theft. The lack of comprehensive security protections on many ESXi hypervisors also makes them an attractive target for ransomware operators [8].

Victimology

Akira is known to target organizations across multiple sectors, most notably those in manufacturing, education, and healthcare. These targets span multiple geographic regions, including North America, Latin America, Europe and Asia-Pacific [9].

Geographical distribution of organization’s affected by Akira ransomware in 2025 [9].
Figure 1: Geographical distribution of organization’s affected by Akira ransomware in 2025 [9].

Common Tactics, Techniques and Procedures (TTPs) [7][10]

Initial Access
Targets remote access services such as RDP and VPN through vulnerability exploitation or stolen credentials.

Reconnaissance
Uses network scanning tools like SoftPerfect and Advanced IP Scanner to map the environment and identify targets.

Lateral Movement
Moves laterally using legitimate administrative tools, typically via RDP.

Persistence
Employs techniques such as Kerberoasting and pass-the-hash, and tools like Mimikatz to extract credentials. Known to create new domain accounts to maintain access.

Command and Control
Utilizes remote access tools including AnyDesk, RustDesk, Ngrok, and Cloudflare Tunnel.

Exfiltration
Uses tools such as FileZilla, WinRAR, WinSCP, and Rclone. Data is exfiltrated via protocols like FTP and SFTP, or through cloud storage services such as Mega.

Darktrace’s Coverage of Akira ransomware

Reconnaissance

Darktrace first detected of unusual network activity around 05:10 UTC, when a desktop device was observed performing a network scan and making an unusual number of DCE-RPC requests to the endpoint mapper (epmapper) service. Network scans are typically used to identify open ports, while querying the epmapper service can reveal exposed RPC services on the network.

Multiple other devices were also later seen with similar reconnaissance activity, and use of the Advanced IP Scanner tool, indicated by connections to the domain advanced-ip-scanner[.]com.

Lateral movement

Shortly after the initial reconnaissance, the same desktop device exhibited unusual use of administrative tools. Darktrace observed the user agent “Ruby WinRM Client” and the URI “/wsman” as the device initiated a rare outbound Windows Remote Management (WinRM) connection to two domain controllers (REDACTED-dc1 and REDACTED-dc2). WinRM is a Microsoft service that uses the WS-Management (WSMan) protocol to enable remote management and control of network devices.

Darktrace also observed the desktop device connecting to an ESXi device (REDACTED-esxi1) via RDP using an LDAP service credential, likely with administrative privileges.

Credential access

At around 06:26 UTC, the desktop device was seen fetching an Active Directory certificate from the domain controller (REDACTED-dc1) by making a DCE-RPC request to the ICertPassage service. Shortly after, the device made a Kerberos login using the administrative credential.

Figure 3: Darktrace’s detection of the of anomalous certificate download and subsequent Kerberos login.

Further investigation into the device’s event logs revealed a chain of connections that Darktrace’s researchers believe demonstrates a credential access technique known as “UnPAC the hash.”

This method begins with pre-authentication using Kerberos’ Public Key Cryptography for Initial Authentication (PKINIT), allowing the client to use an X.509 certificate to obtain a Ticket Granting Ticket (TGT) from the Key Distribution Center (KDC) instead of a password.

The next stage involves User-to-User (U2U) authentication when requesting a Service Ticket (ST) from the KDC. Within Darktrace's visibility of this traffic, U2U was indicated by the client and service principal names within the ST request being identical. Because PKINIT was used earlier, the returned ST contains the NTLM hash of the credential, which can then be extracted and abused for lateral movement or privilege escalation [11].

Flowchart of Kerberos PKINIT pre-authentication and U2U authentication [12].
Figure 4: Flowchart of Kerberos PKINIT pre-authentication and U2U authentication [12]
Figure 5: Device event log showing the Kerberos Login and Kerberos Ticket events

Analysis of the desktop device’s event logs revealed a repeated sequence of suspicious activity across multiple credentials. Each sequence included a DCE-RPC ICertPassage request to download a certificate, followed by a Kerberos login event indicating PKINIT pre-authentication, and then a Kerberos ticket event consistent with User-to-User (U2U) authentication.

Darktrace identified this pattern as highly unusual. Cyber AI Analyst determined that the device used at least 15 different credentials for Kerberos logins over the course of the attack.

By compromising multiple credentials, the threat actor likely aimed to escalate privileges and facilitate further malicious activity, including lateral movement. One of the credentials obtained via the “UnPAC the hash” technique was later observed being used in an RDP session to the domain controller (REDACTED-dc2).

C2 / Additional tooling

At 06:44 UTC, the domain controller (REDACTED-dc2) was observed initiating a connection to temp[.]sh, a temporary cloud hosting service. Open-source intelligence (OSINT) reporting indicates that this service is commonly used by threat actors to host and distribute malicious payloads, including ransomware [13].

Shortly afterward, the ESXi device was observed downloading an executable named “vmwaretools” from the rare external endpoint 137.184.243[.]69, using the user agent “Wget.” The repeated outbound connections to this IP suggest potential command-and-control (C2) activity.

Cyber AI Analyst investigation into the suspicious file download and suspected C2 activity between the ESXI device and the external endpoint 137.184.243[.]69.
Figure 6: Cyber AI Analyst investigation into the suspicious file download and suspected C2 activity between the ESXI device and the external endpoint 137.184.243[.]69.
Packet capture (PCAP) of connections between the ESXi device and 137.184.243[.]69.
Figure 7: Packet capture (PCAP) of connections between the ESXi device and 137.184.243[.]69.

Data exfiltration

The first signs of data exfiltration were observed at around 7:00 UTC. Both the domain controller (REDACTED-dc2) and a likely SonicWall VPN device were seen uploading approximately 2 GB of data via SSH to the rare external endpoint 66.165.243[.]39 (AS29802 HVC-AS). OSINT sources have since identified this IP as an indicator of compromise (IoC) associated with the Akira ransomware group, known to use it for data exfiltration [14].

Cyber AI Analyst incident view highlighting multiple unusual events across several devices on August 20. Notably, it includes the “Unusual External Data Transfer” event, which corresponds to the anomalous 2 GB data upload to the known Akira-associated endpoint 66.165.243[.]39.
Figure 8: Cyber AI Analyst incident view highlighting multiple unusual events across several devices on August 20. Notably, it includes the “Unusual External Data Transfer” event, which corresponds to the anomalous 2 GB data upload to the known Akira-associated endpoint 66.165.243[.]39.

Cyber AI Analyst

Throughout the course of the attack, Darktrace’s Cyber AI Analyst autonomously investigated the anomalous activity as it unfolded and correlated related events into a single, cohesive incident. Rather than treating each alert as isolated, Cyber AI Analyst linked them together to reveal the broader narrative of compromise. This holistic view enabled the customer to understand the full scope of the attack, including all associated activities and affected assets that might otherwise have been dismissed as unrelated.

Overview of Cyber AI Analyst’s investigation, correlating all related internal and external security events across affected devices into a single pane of glass.
Figure 9: Overview of Cyber AI Analyst’s investigation, correlating all related internal and external security events across affected devices into a single pane of glass.

Containing the attack

In response to the multiple anomalous activities observed across the network, Darktrace's Autonomous Response initiated targeted mitigation actions to contain the attack. These included:

  • Blocking connections to known malicious or rare external endpoints, such as 137.184.243[.]69, 66.165.243[.]39, and advanced-ip-scanner[.]com.
  • Blocking internal traffic to sensitive ports, including 88 (Kerberos), 3389 (RDP), and 49339 (DCE-RPC), to disrupt lateral movement and credential abuse.
  • Enforcing a block on all outgoing connections from affected devices to contain potential data exfiltration and C2 activity.
Autonomous Response actions taken by Darktrace on an affected device, including the blocking of malicious external endpoints and internal service ports.
Figure 10: Autonomous Response actions taken by Darktrace on an affected device, including the blocking of malicious external endpoints and internal service ports.

Managed Detection and Response

As this customer was an MDR subscriber, multiple Enhanced Monitoring alerts—high-fidelity models designed to detect activity indicative of compromise—were triggered across the network. These alerts prompted immediate investigation by Darktrace’s SOC team.

Upon determining that the activity was likely linked to an Akira ransomware attack, Darktrace analysts swiftly acted to contain the threat. At around 08:05 UTC, devices suspected of being compromised were quarantined, and the customer was promptly notified, enabling them to begin their own remediation procedures without delay.

A wider campaign?

Darktrace’s SOC and Threat Research teams identified at least three additional incidents likely linked to the same campaign. All targeted organizations were based in the US, spanning various industries, and each have indications of using SonicWall VPN, indicating it had likely been targeted for initial access.

Across these incidents, similar patterns emerged. In each case, a suspicious executable named “vmwaretools” was downloaded from the endpoint 85.239.52[.]96 using the user agent “Wget”, bearing some resemblance to the file downloads seen in the incident described here. Data exfiltration was also observed via SSH to the endpoints 107.155.69[.]42 and 107.155.93[.]154, both of which belong to the same ASN also seen in the incident described in this blog: S29802 HVC-AS. Notably, 107.155.93[.]154 has been reported in OSINT as an indicator associated with Akira ransomware activity [15]. Further recent Akira ransomware cases have been observed involving SonicWall VPN, where no similar executable file downloads were observed, but SSH exfiltration to the same ASN was. These overlapping and non-overlapping TTPs may reflect the blurring lines between different affiliates operating under the same RaaS.

Lessons from the campaign

This campaign by Akira ransomware actors underscores the critical importance of maintaining up-to-date patching practices. Threat actors continue to exploit previously disclosed vulnerabilities, not just zero-days, highlighting the need for ongoing vigilance even after patches are released. It also demonstrates how misconfigurations and overlooked weaknesses can be leveraged for initial access or privilege escalation, even in otherwise well-maintained environments.

Darktrace’s observations further reveal that ransomware actors are increasingly relying on legitimate administrative tools, such as WinRM, to blend in with normal network activity and evade detection. In addition to previously documented Kerberos-based credential access techniques like Kerberoasting and pass-the-hash, this campaign featured the use of UnPAC the hash to extract NTLM hashes via PKINIT and U2U authentication for lateral movement or privilege escalation.

Credit to Emily Megan Lim (Senior Cyber Analyst), Vivek Rajan (Senior Cyber Analyst), Ryan Traill (Analyst Content Lead), and Sam Lister (Specialist Security Researcher)

Appendices

Darktrace Model Detections

Anomalous Connection / Active Remote Desktop Tunnel

Anomalous Connection / Data Sent to Rare Domain

Anomalous Connection / New User Agent to IP Without Hostname

Anomalous Connection / Possible Data Staging and External Upload

Anomalous Connection / Rare WinRM Incoming

Anomalous Connection / Rare WinRM Outgoing

Anomalous Connection / Uncommon 1 GiB Outbound

Anomalous Connection / Unusual Admin RDP Session

Anomalous Connection / Unusual Incoming Long Remote Desktop Session

Anomalous Connection / Unusual Incoming Long SSH Session

Anomalous Connection / Unusual Long SSH Session

Anomalous File / EXE from Rare External Location

Anomalous Server Activity / Anomalous External Activity from Critical Network Device

Anomalous Server Activity / Outgoing from Server

Anomalous Server Activity / Rare External from Server

Compliance / Default Credential Usage

Compliance / High Priority Compliance Model Alert

Compliance / Outgoing NTLM Request from DC

Compliance / SSH to Rare External Destination

Compromise / Large Number of Suspicious Successful Connections

Compromise / Sustained TCP Beaconing Activity To Rare Endpoint

Device / Anomalous Certificate Download Activity

Device / Anomalous SSH Followed By Multiple Model Alerts

Device / Anonymous NTLM Logins

Device / Attack and Recon Tools

Device / ICMP Address Scan

Device / Large Number of Model Alerts

Device / Network Range Scan

Device / Network Scan

Device / New User Agent To Internal Server

Device / Possible SMB/NTLM Brute Force

Device / Possible SMB/NTLM Reconnaissance

Device / RDP Scan

Device / Reverse DNS Sweep

Device / Suspicious SMB Scanning Activity

Device / UDP Enumeration

Unusual Activity / Unusual External Data to New Endpoint

Unusual Activity / Unusual External Data Transfer

User / Multiple Uncommon New Credentials on Device

User / New Admin Credentials on Client

User / New Admin Credentials on Server

Enhanced Monitoring Models

Compromise / Anomalous Certificate Download and Kerberos Login

Device / Initial Attack Chain Activity

Device / Large Number of Model Alerts from Critical Network Device

Device / Multiple Lateral Movement Model Alerts

Device / Suspicious Network Scan Activity

Unusual Activity / Enhanced Unusual External Data Transfer

Antigena/Autonomous Response Models

Antigena / Network / External Threat / Antigena File then New Outbound Block

Antigena / Network / External Threat / Antigena Suspicious Activity Block

Antigena / Network / External Threat / Antigena Suspicious File Block

Antigena / Network / Insider Threat / Antigena Large Data Volume Outbound Block

Antigena / Network / Insider Threat / Antigena Network Scan Block

Antigena / Network / Insider Threat / Antigena Unusual Privileged User Activities Block

Antigena / Network / Manual / Quarantine Device

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

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

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

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

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

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

Antigena / Network / Significant Anomaly / Repeated Antigena Alerts

List of Indicators of Compromise (IoCs)

·      66.165.243[.]39 – IP Address – Data exfiltration endpoint

·      107.155.69[.]42 – IP Address – Probable data exfiltration endpoint

·      107.155.93[.]154 – IP Address – Likely Data exfiltration endpoint

·      137.184.126[.]86 – IP Address – Possible C2 endpoint

·      85.239.52[.]96 – IP Address – Likely C2 endpoint

·      hxxp://85.239.52[.]96:8000/vmwarecli  – URL – File download

·      hxxp://137.184.126[.]86:8080/vmwaretools – URL – File download

MITRE ATT&CK Mapping

Initial Access – T1190 – Exploit Public-Facing Application

Reconnaissance – T1590.002 – Gather Victim Network Information: DNS

Reconnaissance – T1590.005 – Gather Victim Network Information: IP Addresses

Reconnaissance – T1592.004 – Gather Victim Host Information: Client Configurations

Reconnaissance – T1595 – Active Scanning

Discovery – T1018 – Remote System Discovery

Discovery – T1046 – Network Service Discovery

Discovery – T1083 – File and Directory Discovery

Discovery – T1135 – Network Share Discovery

Lateral Movement – T1021.001 – Remote Services: Remote Desktop Protocol

Lateral Movement – T1021.004 – Remote Services: SSH

Lateral Movement – T1021.006 – Remote Services: Windows Remote Management

Lateral Movement – T1550.002 – Use Alternate Authentication Material: Pass the Hash

Lateral Movement – T1550.003 – Use Alternate Authentication Material: Pass the Ticket

Credential Access – T1110.001 – Brute Force: Password Guessing

Credential Access – T1649 – Steal or Forge Authentication Certificates

Persistence, Privilege Escalation – T1078 – Valid Accounts

Resource Development – T1588.001 – Obtain Capabilities: Malware

Command and Control – T1071.001 – Application Layer Protocol: Web Protocols

Command and Control – T1105 – Ingress Tool Transfer

Command and Control – T1573 – Encrypted Channel

Collection – T1074 – Data Staged

Exfiltration – T1041 – Exfiltration Over C2 Channel

Exfiltration – T1048 – Exfiltration Over Alternative Protocol

References

[1] https://thehackernews.com/2025/08/sonicwall-investigating-potential-ssl.html

[2] https://www.sonicwall.com/support/notices/gen-7-and-newer-sonicwall-firewalls-sslvpn-recent-threat-activity/250804095336430

[3] https://psirt.global.sonicwall.com/vuln-detail/SNWLID-2024-0015

[4] https://arcticwolf.com/resources/blog/arctic-wolf-observes-akira-ransomware-campaign-targeting-sonicwall-sslvpn-accounts/

[5] https://www.rapid7.com/blog/post/dr-akira-ransomware-group-utilizing-sonicwall-devices-for-initial-access/

[6] https://www.ic3.gov/AnnualReport/Reports/2024_IC3Report.pdf

[7] https://www.cisa.gov/news-events/cybersecurity-advisories/aa24-109a

[8] https://blog.talosintelligence.com/akira-ransomware-continues-to-evolve/

[9] https://www.ransomware.live/map?year=2025&q=akira

[10] https://attack.mitre.org/groups/G1024/
[11] https://labs.lares.com/fear-kerberos-pt2/#UNPAC

[12] https://www.thehacker.recipes/ad/movement/kerberos/unpac-the-hash

[13] https://www.s-rminform.com/latest-thinking/derailing-akira-cyber-threat-intelligence)

[14] https://fieldeffect.com/blog/update-akira-ransomware-group-targets-sonicwall-vpn-appliances

[15] https://arcticwolf.com/resources/blog/arctic-wolf-observes-july-2025-uptick-in-akira-ransomware-activity-targeting-sonicwall-ssl-vpn/

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About the author
Emily Megan Lim
Cyber Analyst
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