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
Justin Fier
SVP, Red Team Operations
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12
Jan 2022
In 2020, the financial services sector was the industry that experienced the most cyber-attacks. For years, attackers targeted these organizations because they were expectedly lucrative targets.
But in 2021, the financial services sector was no longer the most targeted. Instead, the IT and communications sector, including telecommunications providers, software developers, managed security service providers, and others faced the most attempted cyber-attacks.
This shift in priority target is not surprising for industry experts given the numerous high-profile software supply chain attacks in 2021, including those on SolarWinds, Kaseya and GitLab. Bad actors increasingly see software and developer infrastructure, platforms, and providers as entry vectors into governments, corporations, and critical infrastructure.
Darktrace’s researchers observed that its artificial intelligence (AI) autonomously interrupted around 150,000 threats each week against the sector in 2021. These research findings are developed based on Darktrace data generated by ‘early indicator analysis’ that looks at the breadcrumbs of potential cyber-attacks at several stages before attributing them to any actor and before they escalate into a full-blown crisis.
From this analysis, Darktrace predicts that, in 2022, we will see threat actors embed malicious software throughout the software supply chain, including proprietary source code, developer repositories, open-source libraries, and more. We will likely see further supply chain attacks against software platforms and additional publicized vulnerabilities.
Explaining the shift
This increase in attacks on this sector is likely because more companies rely on third-party trusted suppliers to handle their data while it’s in motion and at rest. This cyber-attack vector has proven substantially profitable for attackers who focused their efforts on related organizations to get to a target’s crown jewels. This shift means that small- and medium-sized companies are now more likely to experience an attack, even if they are not the end target.
Most recently, the uncovered vulnerability ‘Log4Shell’ embedded in a widely used software library left billions of devices exposed and prompted the Cybersecurity and Infrastructure Security Agency to provide formal guidance.
Unfortunately, many of these libraries are only updated and supported by volunteers, making it easy for vulnerabilities and intentional corruptions to slip through. DevSecOps will be a significant discussion point in 2022 as organizations begin to understand the importance of baking security into applications much earlier in the development process. Risks presented by the dependence on open source will put dev teams front and center.
Email phishing persists as a reliable method for attackers
Despite this relevant shift in targets, Darktrace found that the most widely used attack method on the IT sector continues to be phishing. Darktrace found that organizations in the industry faced an average of 600 unique email phishing campaigns a month in 2021. These campaigns also matured in sophistication, as most no longer contain a malicious link or attachment as in the typical ill-intended email.
In 2022, attackers will continue to advance their email attacks to hijack the communications chain more directly. We will see attackers hijack trusted supplier accounts to send spear phishing emails from genuine, trusted accounts, as we saw in the November 2021 FBI account takeover.
Top cyber-criminals will use ‘clean’ emails containing normal text, with messages carefully crafted to impersonate a trusted third party to induce recipients to reply and reveal sensitive information.
Facing the increase in attacks head-on
As the global software supply chain becomes increasingly interconnected, governments, corporations, and critical infrastructure organizations are all at risk of breach not only through their software and communications suppliers but via any security flaw in the extensive global software supply chain.
In the face of this cyber threat, organizations must focus on not only their own cyber resilience but also ensure they can hold their trusted suppliers accountable to best cyber practices. There is no magic solution to finding attacks embedded in your software suppliers, so the real challenge for organizations will be to operate while accepting this risk. This year, like 2021, it is increasingly unrealistic for these companies to hope to avoid breaches via their supply chains. Instead, they must have the ability to detect the presence of attackers after a breach and stop this malicious activity in the early stages.
If attackers can embed themselves at the beginning of the development process, organizations will have to detect and stop the attacker after they have gotten through. This problem calls for cyber defense technology that can spot vulnerabilities as threat actors exploit them.
This threat reinforces the need for security to be integrated earlier in the development process and the importance of quickly containing attacks to prevent business disruption. Since these are multi-stage attacks, organizations can use AI at every step to contain and remediate the threat.
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.
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Beyond MFA: Detecting Adversary-in-the-Middle Attacks and Phishing with Darktrace
What is an Adversary-in-the-middle (AiTM) attack?
Adversary-in-the-Middle (AiTM) attacks are a sophisticated technique often paired with phishing campaigns to steal user credentials. Unlike traditional phishing, which multi-factor authentication (MFA) increasingly mitigates, AiTM attacks leverage reverse proxy servers to intercept authentication tokens and session cookies. This allows attackers to bypass MFA entirely and hijack active sessions, stealthily maintaining access without repeated logins.
This blog examines a real-world incident detected during a Darktrace customer trial, highlighting how Darktrace / EMAILTM and Darktrace / IDENTITYTMidentified the emerging compromise in a customer’s email and software-as-a-service (SaaS) environment, tracked its progression, and could have intervened at critical moments to contain the threat had Darktrace’s Autonomous Response capability been enabled.
What does an AiTM attack look like?
Inbound phishing email
Attacks typically begin with a phishing email, often originating from the compromised account of a known contact like a vendor or business partner. These emails will often contain malicious links or attachments leading to fake login pages designed to spoof legitimate login platforms, like Microsoft 365, designed to harvest user credentials.
Proxy-based credential theft and session hijacking
When a user clicks on a malicious link, they are redirected through an attacker-controlled proxy that impersonates legitimate services. This proxy forwards login requests to Microsoft, making the login page appear legitimate. After the user successfully completes MFA, the attacker captures credentials and session tokens, enabling full account takeover without the need for reauthentication.
Follow-on attacks
Once inside, attackers will typically establish persistence through the creation of email rules or registering OAuth applications. From there, they often act on their objectives, exfiltrating sensitive data and launching additional business email compromise (BEC) campaigns. These campaigns can include fraudulent payment requests to external contacts or internal phishing designed to compromise more accounts and enable lateral movement across the organization.
Darktrace’s detection of an AiTM attack
At the end of September 2025, Darktrace detected one such example of an AiTM attack on the network of a customer trialling Darktrace / EMAIL and Darktrace / IDENTITY.
In this instance, the first indicator of compromise observed by Darktrace was the creation of a malicious email rule on one of the customer’s Office 365 accounts, suggesting the account had likely already been compromised before Darktrace was deployed for the trial.
Darktrace / IDENTITY observed the account creating a new email rule with a randomly generated name, likely to hide its presence from the legitimate account owner. The rule marked all inbound emails as read and deleted them, while ignoring any existing mail rules on the account. This rule was likely intended to conceal any replies to malicious emails the attacker had sent from the legitimate account owner and to facilitate further phishing attempts.
Figure 1: Darktrace’s detection of the anomalous email rule creation.
Internal and external phishing
Following the creation of the email rule, Darktrace / EMAIL observed a surge of suspicious activity on the user’s account. The account sent emails with subject lines referencing payment information to over 9,000 different external recipients within just one hour. Darktrace also identified that these emails contained a link to an unusual Google Drive endpoint, embedded in the text “download order and invoice”.
Figure 2: Darkrace’s detection of an unusual surge in outbound emails containing suspicious content, shortly following the creation of a new email rule.
Figure 3: Darktrace / EMAIL’s detection of the compromised account sending over 9,000 external phishing emails, containing an unusual Google Drive link.
As Darktrace / EMAIL flagged the message with the ‘Compromise Indicators’ tag (Figure 2), it would have been held automatically if the customer had enabled default Data Loss Prevention (DLP) Action Flows in their email environment, preventing any external phishing attempts.
Figure 4: Darktrace / EMAIL’s preview of the email sent by the offending account.
Darktrace analysis revealed that, after clicking the malicious link in the email, recipients would be redirected to a convincing landing page that closely mimicked the customer’s legitimate branding, including authentic imagery and logos, where prompted to download with a PDF named “invoice”.
Figure 5: Download and login prompts presented to recipients after following the malicious email link, shown here in safe view.
After clicking the “Download” button, users would be prompted to enter their company credentials on a page that was likely a credential-harvesting tool, designed to steal corporate login details and enable further compromise of SaaS and email accounts.
Darktrace’s Response
In this case, Darktrace’s Autonomous Response was not fully enabled across the customer’s email or SaaS environments, allowing the compromise to progress, as observed by Darktrace here.
Despite this, Darktrace / EMAIL’s successful detection of the malicious Google Drive link in the internal phishing emails prompted it to suggest ‘Lock Link’, as a recommended action for the customer’s security team to manually apply. This action would have automatically placed the malicious link behind a warning or screening page blocking users from visiting it.
Figure 6: Autonomous Response suggesting locking the malicious Google Drive link sent in internal phishing emails.
Furthermore, if active in the customer’s SaaS environment, Darktrace would likely have been able to mitigate the threat even earlier, at the point of the first unusual activity: the creation of a new email rule. Mitigative actions would have included forcing the user to log out, terminating any active sessions, and disabling the account.
Conclusion
AiTM attacks represent a significant evolution in credential theft techniques, enabling attackers to bypass MFA and hijack active sessions through reverse proxy infrastructure. In the real-world case we explored, Darktrace’s AI-driven detection identified multiple stages of the attack, from anomalous email rule creation to suspicious internal email activity, demonstrating how Autonomous Response could have contained the threat before escalation.
MFA is a critical security measure, but it is no longer a silver bullet. Attackers are increasingly targeting session tokens rather than passwords, exploiting trusted SaaS environments and internal communications to remain undetected. Behavioral AI provides a vital layer of defense by spotting subtle anomalies that traditional tools often miss
Security teams must move beyond static defenses and embrace adaptive, AI-driven solutions that can detect and respond in real time. Regularly review SaaS configurations, enforce conditional access policies, and deploy technologies that understand “normal” behavior to stop attackers before they succeed.
Credit to David Ison (Cyber Analyst), Bertille Pierron (Solutions Engineer), Ryan Traill (Analyst Content Lead)
React2Shell: How Opportunist Attackers Exploited CVE-2025-55182 Within Hours
What is React2Shell?
CVE-2025-55182, also known as React2Shell is a vulnerability within React server components that allows for an unauthenticated attacker to gain remote code execution with a single request. The severity of this vulnerability and ease of exploitability has led to threat actors opportunistically exploiting it within a matter of days of its public disclosure.
Darktrace security researchers rapidly deployed a new honeypot using the Cloudypots system, allowing for the monitoring of exploitation of the vulnerability in the wild.
Cloudypots is a system that enables virtual instances of vulnerable applications to be deployed in the cloud and monitored for attack. This approach allows for Darktrace to deploy high-interaction, realistic honeypots, that appear as genuine deployments of vulnerable software to attackers.
This blog will explore one such campaign, nicknamed “Nuts & Bolts” based on the naming used in payloads.
Analysis of the React2Shell exploit
The React2Shell exploit relies on an insecure deserialization vulnerability within React Server Components’ “Flight” protocol. This protocol uses a custom serialization scheme that security researchers discovered could be abused to run arbitrary JavaScript by crafting the serialized data in a specific way. This is possible because the framework did not perform proper type checking, allowing an attacker to reference types that can be abused to craft a chain that resolves to an anonymous function, and then invoke it with the desired JavaScript as a promise chain.
This code execution can then be used to load the ‘child_process’ node module and execute any command on the target server.
The vulnerability was discovered on December 3, 2025, with a patch made available on the same day [1]. Within 30 hours of the patch, a publicly available proof of concept emerged that could be used to exploit any vulnerable server. This rapid timeline left many servers remaining unpatched by the time attackers began actively exploiting the vulnerability.
Initial access
The threat actor behind the “Nuts & Bolts” campaign uses a spreader server with IP 95.214.52[.]170 to infect victims. The IP appears to be located in Poland and is associated with a hosting provided known as MEVSPACE. The spreader is highly aggressive, launching exploitation attempts, roughly every hour.
When scanning, the spreader primarily targets port 3000, which is the default port for a NEXT.js server in a default or development configuration. It is possible the attacker is avoiding port 80 and 443, as these are more likely to have reverse proxies or WAFs in front of the server, which could disrupt exploitation attempts.
When the spreader finds a new host with port 3000 open, it begins by testing if it is vulnerable to React2Shell by sending a crafted request to run the ‘whoami’ command and store the output in an error digest that is returned to the attacker.
The above snippet is the core part of the crafted request that performs the execution. This allows the attacker to confirm that the server is vulnerable and fetch the user account under which the NEXT.js process is running, which is useful information for determining if a target is worth attacking.
From here, the attacker then sends an additional request to run the actual payload on the victim server.
This snippet attempts to deploy several payloads by using wget (or curl if wget fails) into the /dev directory and execute them. The x86 binary is a Mirai variant that does not appear to have any major alterations to regular Mirai. The ‘nuts/bolts’ endpoint returns a bash script, which is then executed. The script includes several log statements throughout its execution to provide visibility into which parts ran successfully. Similar to the ‘whoami’ request, the output is placed in an error digest for the attacker to review.
In this case, the command-and-control (C2) IP, 89[.]144.31.18, is hosted on a different server operated by a German hosting provider named myPrepaidServer, which offers virtual private server (VPS) services and accepts cryptocurrency payments [2].
Figure 1: Logs observed in the NEXT.JS console as a result of exploitation. In this case, the honeypot was attacked just two minutes after being deployed.
Nuts & Bolts script
This script’s primary purpose is to prepare the box for a cryptocurrency miner.
The script starts by attempting to terminate any competing cryptocurrency miner processes using ‘pkill’ that match on a specific name. It will check for and terminate:
xmrig
softirq (this also matches a system process, which it will fail to kill each invocation)
watcher
/tmp/a.sh
health.sh
Following this, the script will checks for a process named “fghgf”. If it is not running, it will retrieve hxxp://89[.]144.31.18/nuts/lc and write it to /dev/ijnegrrinje.json, as well as retrieving hxxp://89[.]144.31.18/nuts/x and writing it to /dev/fghgf. The script will the executes /dev/fghgf -c /dev/ijnegrrinje.json -B in the background, which is an XMRig miner.
Figure 2: The XMRig deployment script.
The miner is configured to connect to two private pools at 37[.]114.37.94 and 37[.]114.37.82, using “poop” as both the username and password. The use of a private pool conceals the associated wallet address. From here, a short bash script is dropped to /dev/stink.sh. This script continuously crawls all running processes on the system and reads their /proc/pid/exe path, which contains a copy of the original executable that was run. The ‘strings’ utility is run to output all valid ASCII strings found within the data and checks to see if contains either “xmrig”, “rondo” or “UPX 5”. If so, it sends a SIGKILL to the process to terminate it.
Additionally, it will run ‘ls –l’ on the exe path in case it is symlinked to a specific path or has been deleted. If the output contains any of the following strings, the script sends a SIGKILL to terminate the program:
(deleted) - Indicates that the original executable was deleted from the disk, a common tactic used by malware to evade detection.
xmrig
hash
watcher
/dev/a
softirq
rondo
UPX 5.02
Figure 3: The killer loop and the dropper. In this case ${R}/${K} resolves to /dev/stink.sh.
Darktrace observations in customer environments
Following the public disclosure of CVE‑2025‑55182 on December, Darktrace observed multiple exploitation attempts across customer environments beginning around December 4. Darktrace triage identified a series of consistent indicators of compromise (IoCs). By consolidating indicators across multiple deployments and repeat infrastructure clusters, Darktrace identified a consistent kill chain involving shell‑script downloads and HTTP beaconing.
In one example, on December 5, Darktrace observed external connections to malicious IoC endpoints (172.245.5[.]61:38085, 5.255.121[.]141, 193.34.213[.]15), followed by additional connections to other potentially malicious endpoint. These appeared related to the IoCs detailed above, as one suspicious IP address shared the same ASN. After this suspicious external connectivity, Darktrace observed cryptomining-related activity. A few hours later, the device initiated potential lateral movement activity, attempting SMB and RDP sessions with other internal devices on the network. These chain of events appear to identify this activity to be related to the malicious campaign of the exploitation of React2Shell vulnerability.
Generally, outbound HTTP traffic was observed to ports in the range of 3000–3011, most notably port 3001. Requests frequently originated from scripted tools, with user agents such as curl/7.76.1, curl/8.5.0, Wget/1.21.4, and other generic HTTP signatures. The URIs associated with these requests included paths like /nuts/x86 and /n2/x86, as well as long, randomized shell script names such as /gfdsgsdfhfsd_ghsfdgsfdgsdfg.sh. In some cases, parameterized loaders were observed, using query strings like: /?h=<ip>&p=<port>&t=<proto>&a=l64&stage=true.
Infrastructure analysis revealed repeated callbacks to IP-only hosts linked to ASN AS200593 (Prospero OOO), a well-known “bulletproof” hosting provider often utilized by cyber criminals [3], including addresses such as 193.24.123[.]68:3001 and 91.215.85[.]42:3000, alongside other nodes hosting payloads and staging content.
Darktrace model coverage
Darktrace model coverage consistently highlighted behaviors indicative of exploitation. Among the most frequent detections were anomalous server activity on new, non-standard ports and HTTP requests posted to IP addresses without hostnames, often using uncommon application protocols. Models also flagged the appearance of new user agents such as curl and wget originating from internet-facing systems, representing an unusual deviation from baseline behavior.
Additionally, observed activity included the download of scripts and executable files from rare external sources, with Darktrace’s Autonomous Response capability intervening to block suspicious transfers, when enabled. Beaconing patterns were another strong signal, with detections for HTTP beaconing to new or rare IP addresses, sustained SSL or HTTP increases, and long-running compromise indicators such as “Beacon for 4 Days” and “Slow Beaconing.”
Conclusion
While this opportunistic campaign to exploit the React2Shell exploit is not particularly sophisticated, it demonstrates that attackers can rapidly prototyping new methods to take advantage of novel vulnerabilities before widespread patching occurs. With a time to infection of only two minutes from the initial deployment of the honeypot, this serves as a clear reminder that patching vulnerabilities as soon as they are released is paramount.
Credit to Nathaniel Bill (Malware Research Engineer), George Kim (Analyst Consulting Lead – AMS), Calum Hall (Technical Content Researcher), Tara Gould (Malware Research Lead, and Signe Zaharka (Principal Cyber Analyst).
