September 11, 2025

SEO Poisoning and Fake PuTTY sites: Darktrace’s Investigation into the Oyster backdoor

SEO poisoning is a malicious tactic where threat actors manipulate search engine rankings to promote deceptive websites. These sites often mimic legitimate software downloads, delivering malware like the Oyster backdoor. Learn about Darktrace’s investigation into the tactics used to deliver Oyster via fake PuTTY sites and manipulate search visibility.

Written by

Christina Kreza

Cyber Analyst

Inside the SOC

Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.

Written by

Christina Kreza

Cyber Analyst

Sep 2025

What is SEO poisoning?

Search Engine Optimization (SEO) is the legitimate marketing technique of improving the visibility of websites in organic search engine results. Businesses, publishers, and organizations use SEO to ensure their content is easily discoverable by users. Techniques may include optimizing keywords, creating backlinks, or even ensuring mobile compatibility.

SEO poisoning occurs when attackers use these same techniques for malicious purposes. Instead of improving the visibility of legitimate content, threat actors use SEO to push harmful or deceptive websites to the top of search results. This method exploits the common assumption that top-ranking results are trustworthy, leading users to click on URLs without carefully inspecting them.

As part of SEO poisoning, the attacker will first register a typo-squatted domain, slightly misspelled or otherwise deceptive versions of real software sites, such as putty[.]run or puttyy[.]org. These sites are optimized for SEO and often even backed by malicious Google ads, increasing the visibility when users search for download links. To achieve that, threat actors may embed pages with strategically chosen, high-value keywords or replicate content from reputable sources to elevate the domain’s perceived authority in search engine algorithms [4]. In more advanced operations, these tactics are reinforced with paid promotion, such as Google ads, enabling malicious domains to appear above organic search results as sponsored links. This placement not only accelerates visibility but also impacts an unwarranted sense of legitimacy to unsuspected users.

Once a user lands on one of these fake pages, they are presented with what looks like a legitimate software download option. Upon clicking the download indicator, the user will be redirected to another separate domain that actually hosts the payload. This hosting domain is usually unrelated to the nominally referenced software. These third-party sites can involve recently registered domains but may also include legitimate websites that have been recently compromised. By hosting malware on a variety of infrastructure, attackers can prolong the availability of distribution methods for these malicious files before they are taken down.

What is the Oyster backdoor?

Oyster, also known as Broomstick or CleanUpLoader, is a C++ based backdoor malware first identified in July 2023. It enables remote access to infected systems, offering features such as command-line interaction and file transfers.

Oyster has been widely adopted by various threat actors, often as an entry point for ransomware attacks. Notable examples include Vanilla Tempest and Rhysida ransomware groups, both of which have been observed leveraging the Oyster backdoor to enhance their attack capabilities. Vanilla Tempest is known for using Oyster’s stealth persistence to maintain long-term access within targeted networks, often aligning their operations with ransomware deployment [5]. Rhysida has taken this further by deploying Oyster as an initial access tool in ransomware campaigns, using it to conduct reconnaissance and move laterally before executing encryption activities [6].

Once installed, the backdoor gathers basic system information before communicating with a command-and-control (C2) server. The malware largely relies on a ‘cmd.exe’ instance to execute commands and launch other files [1].

In previous SEO poisoning cases, the file downloaded from the fake pages is not just PuTTY, but a trojanized version that includes the stealthy Oyster backdoor. PuTTY is a free and open-source terminal emulator for Windows that allows users to connect to remote servers and devices using protocols like SSH and Telnet. In the recent campaign, once a user visits the fake software download site, ranked highly through SEO poisoning, the malicious payload is downloaded through direct user interaction and subsequently installed on the local device, initiating the compromise. The malware then performs two actions simultaneously: it installs a fully functional version of PuTTY to avoid user suspicion, while silently deploying the Oyster backdoor. Given PuTTY’s nature, it is prominently used by IT administrators with highly privileged account as opposed to standard users in a business, possibly narrowing the scope of the targets.

Oyster’s persistence mechanism involves creating a Windows Scheduled Task that runs every few minutes. Notably, the infection uses Dynamic Link Library (DLL) side loading, where a malicious DLL, often named ‘twain_96.dll’, is executed via the legitimate Windows utility ‘rundll32.exe’, which is commonly used to run DLLs [2]. This technique is frequently used by malicious actors to blend their activity with normal system operations.

Darktrace’s Coverage of the Oyster Backdoor

In June 2025, security analysts at Darktrace identified a campaign leveraging search engine manipulation to deliver malware masquerading as the popular SSH client, PuTTY. Darktrace / NETWORK’s anomaly-based detection identified signs of malicious activity, and when properly configured, its Autonomous Response capability swiftly shut down the threat before it could escalate into a more disruptive attack. Subsequent analysis by Darktrace’s Threat Research team revealed that the payload was a variant of the Oyster backdoor.

The first indicators of an emerging Oyster SEO campaign typically appeared when user devices navigated to a typosquatted domain, such as putty[.]run or putty app[.]naymin[.]com, via a TLS/SSL connection.

*Figure 1: Darktrace’s detection of a device connecting to the typosquatted domain putty[.]run.*

The device would then initiate a connection to a secondary domain that hosts the malicious installer, likely triggered by user interaction with redirect elements on the landing page. This secondary site may not have any immediate connection to PuTTY itself but is instead a hijacked blog, a file-sharing service, or a legitimate-looking content delivery subdomain.

*Figure 2: Darktrace’s detection of the device making subsequent connections to the payload domain.*

Following installation, multiple affected devices were observed attempting outbound connectivity to rare external IP addresses, specifically requesting the ‘/secure’ endpoint as noted within the declared URIs. After the initial callback, the malware continued communicating with additional infrastructure, maintaining its foothold and likely waiting for tasking instructions. Communication patterns included:

· Endpoints with URIs /api/kcehc and /api/jgfnsfnuefcnegfnehjbfncejfh

· Endpoints with URI /reg and user agent “WordPressAgent”, “FingerPrint” or “FingerPrintpersistent”

This tactic has been consistently linked to the Oyster backdoor, which has shown similar URI patterns across multiple campaigns [3].

Darktrace analysts also noted the sophisticated use of spoofed user agent strings across multiple investigated customer networks. These headers, which are typically used to identify the application making an HTTP request, are carefully crafted to appear benign or mimic legitimate software. One common example seen in the campaign is the user agent string “WordPressAgent”. While this string references a legitimate web application or plugin, it does not appear to correspond to any known WordPress services or APIs. Its inclusion is most likely designed to mimic background web traffic commonly associated with WordPress-based content management systems.

*Figure 3: Cyber AI Analyst investigation linking the HTTP C2 activity.*

Case-Specific Observations

While the previous section focused on tactics and techniques common across observed Oyster infections, a closer examination reveals notable variations and unique elements in specific cases. These distinct features offer valuable insights into the diverse operational approaches employed by threat actors. These distinct features, from unusual user agent strings to atypical network behavior, offer valuable insights into the diverse operational approaches employed by the threat actors. Crucially, the divergence in post-exploitation activity reflects a broader trend in the use of widely available malware families like Oyster as flexible entry points, rather than fixed tools with a single purpose. This modular use of the backdoor reflects the growing Malware-as-a-Service (MaaS) ecosystem, where a single initial infection can be repurposed depending on the operator’s goals.

From Infection to Data Egress

In one observed incident, Darktrace observed an infected device downloading a ZIP file named ‘host[.]zip’ via curl from the URI path /333/host[.]zip, following the standard payload delivery chain. This file likely contained additional tools or payloads intended to expand the attacker’s capabilities within the compromised environment. Shortly afterwards, the device exhibited indicators of probable data exfiltration, with outbound HTTP POST requests featuring the URI pattern: /upload?dir=NAME_FOLDER/KEY_KEY_KEY/redacted/c/users/public.

This format suggests the malware was actively engaged in local host data staging and attempting to transmit files from the target machine. The affected device, identified as a laptop, aligns with the expected target profile in SEO poisoning scenarios, where unsuspecting end users download and execute trojanized software.

Irregular RDP Activity and Scanning Behavior

Several instances within the campaign revealed anomalous or unexpected Remote Desktop Protocol (RDP) sessions occurring shortly after DNS requests to fake PuTTY domains. Unusual RDP connections frequently followed communication with Oyster backdoor C2 servers. Additionally, Darktrace detected patterns of RDP scanning, suggesting the attackers were actively probing for accessible systems within the network. This behavior indicates a move beyond initial compromise toward lateral movement and privilege escalation, common objectives once persistence is established.

The presence of unauthorized and administrative RDP sessions following Oyster infections aligns with the malware’s historical role as a gateway for broader impact. In previous campaigns, Oyster has often been leveraged to enable credential theft, lateral movement, and ultimately ransomware deployment. The observed RDP activity in this case suggests a similar progression, where the backdoor is not the final objective but rather a means to expand access and establish control over the target environment.

Cryptic User Agent Strings?

In multiple investigated cases, the user agent string identified in these connections featured formatting that appeared nonsensical or cryptic. One such string containing seemingly random Chinese-language characters translated into an unusual phrase: “Weihe river is where the water and river flow.” Legitimate software would not typically use such wording, suggesting that the string was intended as a symbolic marker rather than a technical necessity. Whether meant as a calling card or deliberately crafted to frame attribution, its presence highlights how subtle linguistic cues can complicate analysis.

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Figure 4: Darktrace’s detection of malicious connections using a user agent with randomized Chinese-language formatting.

Strategic Implications

What makes this campaign particularly noteworthy is not simply the use of Oyster, but its delivery mechanism. SEO poisoning has traditionally been associated with cybercriminal operations focused on opportunistic gains, such as credential theft and fraud. Its strength lies in casting a wide net, luring unsuspecting users searching for popular software and tricking them into downloading malicious binaries. Unlike other campaigns, SEO poisoning is inherently indiscriminate, given that the attacker cannot control exactly who lands on their poisoned search results. However, in this case, the use of PuTTY as the luring mechanism possibly indicates a narrowed scope - targeting IT administrators and accounts with high privileges due to the nature of PuTTY’s functionalities.

This raises important implications when considered alongside Oyster. As a backdoor often linked to ransomware operations and persistent access frameworks, Oyster is far more valuable as an entry point into corporate or government networks than small-scale cybercrime. The presence of this malware in an SEO-driven delivery chain suggests a potential convergence between traditional cybercriminal delivery tactics and objectives often associated with more sophisticated attackers. If actors with state-sponsored or strategic objectives are indeed experimenting with SEO poisoning, it could signal a broadening of their targeting approaches. This trend aligns with the growing prominence of MaaS and the role of initial access brokers in today’s cybercrime ecosystem.

Whether the operators seek financial extortion through ransomware or longer-term espionage campaigns, the use of such techniques blurs the traditional distinctions. What looks like a mass-market infection vector might, in practice, be seeding footholds for high-value strategic intrusions.

Credit to Christina Kreza (Cyber Analyst) and Adam Potter (Senior Cyber Analyst)

Appendices

MITRE ATT&CK Mapping

· T1071.001 – Command and Control – Web Protocols

· T1008 – Command and Control – Fallback Channels

· T0885 – Command and Control – Commonly Used Port

· T1571 – Command and Control – Non-Standard Port

· T1176 – Persistence – Browser Extensions

· T1189 – Initial Access – Drive-by Compromise

· T1566.002 – Initial Access – Spearphishing Link

· T1574.001 – Persistence – DLL

Indicators of Compromise (IoCs)

· 85.239.52[.]99 – IP address

· 194.213.18[.]89/reg – IP address / URI

· 185.28.119[.]113/secure – IP address / URI

· 185.196.8[.]217 – IP address

· 185.208.158[.]119 – IP address

· putty[.]run – Endpoint

· putty-app[.]naymin[.]com – Endpoint

· /api/jgfnsfnuefcnegfnehjbfncejfh

· /api/kcehc

Darktrace Model Detections

· Anomalous Connection / New User Agent to IP Without Hostname

· Anomalous Connection / Posting HTTP to IP Without Hostname

· Compromise / HTTP Beaconing to Rare Destination

· Compromise / Large Number of Suspicious Failed Connections

· Compromise / Beaconing Activity to External Rare

· Compromise / Quick and Regular Windows HTTP Beaconing

· Device / Large Number of Model Alerts

· Device / Initial Attack Chain Activity

· Device / Suspicious Domain

· Device / New User Agent

· Antigena / Network / Significant Anomaly / Antigena Breaches Over Time Block

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

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

References

[1] https://malpedia.caad.fkie.fraunhofer.de/details/win.broomstick

[2] https://arcticwolf.com/resources/blog/malvertising-campaign-delivers-oyster-broomstick-backdoor-via-seo-poisoning-trojanized-tools/

[3] https://hunt.io/blog/oysters-trail-resurgence-infrastructure-ransomware-cybercrime

[4] https://www.crowdstrike.com/en-us/cybersecurity-101/social-engineering/seo-poisoning/

[5] https://blackpointcyber.com/blog/vanilla-tempest-oyster-backdoor-netsupport-unknown-infostealers-soc-incidents-blackpoint-apg/

[6] https://areteir.com/article/rhysida-using-oyster-backdoor-in-attacks/

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Written by

Christina Kreza

Cyber Analyst

Inside the SOC

Written by

Christina Kreza

Cyber Analyst

Cyber Security AI Technical Instructor

Watch the NIS2 Webinar

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AI

December 5, 2025

Simplifying Cross Domain Investigations

Cross-domain gaps mean cross-domain attacks

Organizations are built on increasingly complex digital estates. Nowadays, the average IT ecosystem spans across a large web of interconnected domains like identity, network, cloud, and email.

While these domain-specific technologies may boost business efficiency and scalability, they also provide blind spots where attackers can shelter undetected. Threat actors can slip past defenses because security teams often use different detection tools in each realm of their digital infrastructure. Adversaries will purposefully execute different stages of an attack across different domains, ensuring no single tool picks up too many traces of their malicious activity. Identifying and investigating this type of threat, known as a cross-domain attack, requires mastery in event correlation.

For example, one isolated network scan detected on your network may seem harmless at first glance. Only when it is stitched together with a rare O365 login, a new email rule and anomalous remote connections to an S3 bucket in AWS does it begin to manifest as an actual intrusion.

However, there are a whole host of other challenges that arise with detecting this type of attack. Accessing those alerts in the respective on-premise network, SaaS and IaaS environments, understanding them and identifying which ones are related to each other takes significant experience, skill and time. And time favours no one but the threat actor.

Figure 1: Anatomy of a cross domain attack

Diverse domains and empty grocery shelves

In April 2025, the UK faced a throwback to pandemic-era shortages when the supermarket giant Marks & Spencer (M&S) was crippled by a cyberattack, leaving empty shelves across its stores and massive disruptions to its online service.

The threat actors, a group called Scattered Spider, exploited multiple layers of the organization’s digital infrastructure. Notably, the group were able to bypass the perimeter not by exploiting a technical vulnerability, but an identity. They used social engineering tactics to impersonate an M&S employee and successfully request a password reset.

Once authenticated on the network, they accessed the Windows domain controller and exfiltrated the NTDS.dit file – a critical file containing hashed passwords for all users in the domain. After cracking those hashes offline, they returned to the network with escalated privileges and set their sights on the M&S cloud infrastructure. They then launched the encryption payload on the company’s ESXi virtual machines.

To wrap up, the threat actors used a compromised employee’s email account to send an “abuse-filled” email to the M&S CEO, bragging about the hack and demanding payment. This was possibly more of a psychological attack on the CEO than a technically integral part of the cyber kill chain. However, it revealed yet another one of M&S’s domains had been compromised.

In summary, the group’s attack spanned four different domains:

Identity: Social engineering user impersonation

Network: Exfiltration of NTDS.dit file

Cloud: Ransomware deployed on ESXI VMs

Email: Compromise of user account to contact the CEO

Adept at exploiting nuance

This year alone, several high-profile cyber-attacks have been attributed to the same group, Scattered Spider, including the hacks on Victoria’s Secret, Adidas, Hawaiian Airlines, WestJet, the Co-op and Harrods. It begs the question, what has made this group so successful?

In the M&S attack, they showcased their advanced proficiency in social engineering, which they use to bypass identity controls and gain initial access. They demonstrated deep knowledge of cloud environments by deploying ransomware onto virtualised infrastructure. However, this does not exemplify a cookie-cutter template of attack methods that brings them success every time.

According to CISA, Scattered Spider typically use a remarkable variety of TTPs (tactics, techniques and procedures) across multiple domains to carry out their campaigns. From leveraging legitimate remote access tools in the network, to manipulating AWS EC2 cloud instances or spoofing email domains, the list of TTPs used by the group is eye-wateringly long. Additionally, the group reportedly evades detection by “frequently modifying their TTPs”.

If only they had better intentions. Any security director would be proud of a red team who not only has this depth and breadth of domain-centric knowledge but is also consistently upskilling.

Yet, staying ahead of adversaries who seamlessly move across domains and fluently exploit every system they encounter is just one of many hurdles security teams face when investigating cross-domain attacks.

Resource-heavy investigations

There was a significant delay in time to detection of the M&S intrusion. News outlet BleepingComputer reported that attackers infiltrated the M&S network as early as February 2025. They maintained persistence for weeks before launching the attack in late April 2025, indicating that early signs of compromise were missed or not correlated across domains.

While it’s unclear exactly why M&S missed the initial intrusion, one can speculate about the unique challenges investigating cross-domain attacks present.

Challenges of cross-domain investigation

First and foremost, correlation work is arduous because the string of malicious behaviour doesn’t always stem from the same device.

A hypothetical attack could begin with an O365 credential creating a new email rule. Weeks later, that same credential authenticates anomalously on two different devices. One device downloads an .exe file from a strange website, while the other starts beaconing every minute to a rare external IP address that no one else in the organisation has ever connected to. A month later, a third device downloads 1.3 GiB of data from a recently spun up S3 bucket and gradually transfers a similar amount of data to that same rare IP.

Amid a sea of alerts and false positives, connecting the dots of a malicious attack like this takes time and meticulous correlation. Factor in the nuanced telemetry data related to each domain and things get even more complex.

An analyst who specialises in network security may not understand the unique logging formats or API calls in the cloud environment. Perhaps they are proficient in protecting the Windows Active Directory but are unfamiliar with cloud IAM.

Cloud is also an inherently more difficult domain to investigate. With 89% of organizations now operating in multi-cloud environments time must be spent collecting logs, snapshots and access records. Coupled with the threat of an ephemeral asset disappearing, the risk of missing a threat is high. These are some of the reasons why research shows that 65% of organisations spend 3-5 extra days investigating cloud incidents.

Helpdesk teams handling user requests over the phone require a different set of skills altogether. Imagine a threat actor posing as an employee and articulately requesting an urgent password reset or a temporary MFA deactivation. The junior Helpdesk agent— unfamiliar with the exception criteria, eager to help and feeling pressure from the persuasive manipulator at the end of the phoneline—could easily fall victim to this type of social engineering.

Empowering analysts through intelligent automation

Even the most skilled analysts can’t manually piece together every strand of malicious activity stretching across domains. But skill alone isn’t enough. The biggest hurdle in investigating these attacks often comes down to whether the team have the time, context, and connected visibility needed to see the full picture.

Many organizations attempt to bridge the gap by stitching together a patchwork of security tools. One platform for email, another for endpoint, another for cloud, and so on. But this fragmentation reinforces the very silos that cross-domain attacks exploit. Logs must be exported, normalized, and parsed across tools a process that is not only error-prone but slow. By the time indicators are correlated, the intrusion has often already deepened.

That’s why automation and AI are becoming indispensable. The future of cross-domain investigation lies in systems that can:

Automatically correlate activity across domains and data sources, turning disjointed alerts into a single, interpretable incident.
Generate and test hypotheses autonomously, identifying likely chains of malicious behaviour without waiting for human triage.
Explain findings in human terms, reducing the knowledge gap between junior and senior analysts.
Operate within and across hybrid environments, from on-premise networks to SaaS, IaaS, and identity systems.

This is where Darktrace transforms alerting and investigations. Darktrace’s Cyber AI Analyst automates the process of correlation, hypothesis testing, and narrative building, not just within one domain, but across many. An anomalous O365 login, a new S3 bucket, and a suspicious beaconing host are stitched together automatically, surfacing the story behind the alerts rather than leaving it buried in telemetry.

Figure 2: How threat activity is correlated in Cyber AI Analyst

By analyzing events from disparate tools and sources, AI Analyst constructs a unified timeline of activity showing what happened, how it spread, and where to focus next. For analysts, it means investigation time is measured in minutes, not days. For security leaders, it means every member of the SOC, regardless of experience, can contribute meaningfully to a cross-domain response.

Figure 3: Correlation showcasing cross domains (SaaS and IaaS) in Cyber AI Analyst

Until now, forensic investigations were slow, manual, and reserved for only the largest organizations with specialized DFIR expertise. Darktrace / Forensic Acquisition & Investigation changes that by leveraging the scale and elasticity of the cloud itself to automate the entire investigation process. From capturing full disk and memory at detection to reconstructing attacker timelines in minutes, the solution turns fragmented workflows into streamlined investigations available to every team.

What once took days now takes minutes. Now, forensic investigations in the cloud are faster, more scalable, and finally accessible to every security team, no matter their size or expertise.

About the author

Benjamin Druttman

Cyber Security AI Technical Instructor

Blog

Network

December 5, 2025

Atomic Stealer: Darktrace’s Investigation of a Growing macOS Threat

The Rise of Infostealers Targeting Apple Users

In a threat landscape historically dominated by Windows-based threats, the growing prevalence of macOS information stealers targeting Apple users is becoming an increasing concern for organizations. Infostealers are a type of malware designed to steal sensitive data from target devices, often enabling attackers to extract credentials and financial data for resale or further exploitation. Recent research identified infostealers as the largest category of new macOS malware, with an alarming 101% increase in the last two quarters of 2024 [1].

What is Atomic Stealer?

Among the most notorious is Atomic macOS Stealer (or AMOS), first observed in 2023. Known for its sophisticated build, Atomic Stealer can exfiltrate a wide range of sensitive information including keychain passwords, cookies, browser data and cryptocurrency wallets.

Originally marketed on Telegram as a Malware-as-a-Service (MaaS), Atomic Stealer has become a popular malware due to its ability to target macOS. Like other MaaS offerings, it includes services like a web panel for managing victims, with reports indicating a monthly subscription cost between $1,000 and $3,000 [2]. Although Atomic Stealer’s original intent was as a standalone MaaS product, its unique capability to target macOS has led to new variants emerging at an unprecedented rate

Even more concerning, the most recent variant has now added a backdoor for persistent access [3]. This backdoor presents a significant threat, as Atomic Stealer campaigns are believed to have reached an around 120 countries. The addition of a backdoor elevates Atomic Stealer to the rare category of backdoor deployments potentially at a global scale, something only previously attributed to nation-state threat actors [4].

This level of sophistication is also evident in the wide range of distribution methods observed since its first appearance; including fake application installers, malvertising and terminal command execution via the ClickFix technique. The ClickFix technique is particularly noteworthy: once the malware is downloaded onto the device, users are presented with what appears to be a legitimate macOS installation prompt. In reality, however, the user unknowingly initiates the execution of the Atomic Stealer malware.

This blog will focus on activity observed across multiple Darktrace customer environments where Atomic Stealer was detected, along with several indicators of compromise (IoCs). These included devices that successfully connected to endpoints associated with Atomic Stealer, those that attempted but failed to establish connections, and instances suggesting potential data exfiltration activity.

Darktrace’s Coverage of Atomic Stealer

As this evolving threat began to spread across the internet in June 2025, Darktrace observed a surge in Atomic Stealer activity, impacting numerous customers in 24 different countries worldwide. Initially, most of the cases detected in 2025 affected Darktrace customers within the Europe, Middle East, and Africa (EMEA) region. However, later in the year, Darktrace began to observe a more even distribution of cases across EMEA, the Americas (AMS), and Asia Pacific (APAC). While multiple sectors were impacted by Atomic Stealer, Darktrace customers in the education sector were the most affected, particularly during September and October, coinciding with the return to school and universities after summer closures. This spike likely reflects increased device usage as students returned and reconnected potentially compromised devices to school and campus environments.

Starting from June, Darktrace detected multiple events of suspicious HTTP activity to external connections to IPs in the range 45.94.47.0/24. Investigation by Darktrace’s Threat Research team revealed several distinct patterns ; HTTP POST requests to the URI “/contact”, identical cURL User Agents and HTTP requests to “/api/tasks/[base64 string]” URIs.

Within one observed customer’s environment in July, Darktrace detected two devices making repeated initiated HTTP connections over port 80 to IPs within the same range. The first, Device A, was observed making GET requests to the IP 45.94.47[.]158 (AS60781 LeaseWeb Netherlands B.V.), targeting the URI “/api/tasks/[base64string]” using the “curl/8.7.2” user agent. This pattern suggested beaconing activity and triggered the ‘Beaconing Activity to External Rare' model alert in Darktrace / NETWORK, with Device A’s Model Event Log showing repeated connections. The IP associated with this endpoint has since been flagged by multiple open-source intelligence (OSINT) vendors as being associated with Atomic Stealer [5].

Figure 1: Darktrace’s detection of Device A showing repeated connections to the suspicious IP address over port 80, indicative of beaconing behavior.

Darktrace’s Cyber AI Analyst subsequently launched an investigation into the activity, uncovering that the GET requests resulted in a ‘503 Service Unavailable’ response, likely indicating that the server was temporarily unable to process the requests.

Figure 2: Cyber AI Analyst Incident showing the 503 Status Code, indicating that the server was temporarily unavailable.

This unusual activity prompted Darktrace’s Autonomous Response capability to recommend several blocking actions for the device in an attempt to stop the malicious activity. However, as the customer’s Autonomous Response configuration was set to Human Confirmation Mode, Darktrace was unable to automatically apply these actions. Had Autonomous Response been fully enabled, these connections would have been blocked, likely rendering the malware ineffective at reaching its malicious command-and-control (C2) infrastructure.

Figure 3: Autonomous Response’s suggested actions to block suspicious connectivity on Device A in the first customer environment.

In another customer environment in August, Darktrace detected similar IoCs, noting a device establishing a connection to the external endpoint 45.94.47[.]149 (ASN: AS57043 Hostkey B.V.). Shortly after the initial connections, the device was observed making repeated requests to the same destination IP, targeting the URI /api/tasks/[base64string] with the user agent curl/8.7.1, again suggesting beaconing activity. Further analysis of this endpoint after the fact revealed links to Atomic Stealer in OSINT reporting [6].

Figure 4: Cyber AI Analyst investigation finding a suspicious URI and user agent for the offending device within the second customer environment.

As with the customer in the first case, had Darktrace’s Autonomous Response been properly configured on the customer’s network, it would have been able to block connectivity with 45.94.47[.]149. Instead, Darktrace suggested recommended actions that the customer’s security team could manually apply to help contain the attack.

Figure 5: Autonomous Response’s suggested actions to block suspicious connectivity to IP 45.94.47[.]149 for the device within the second customer environment.

In the most recent case observed by Darktrace in October, multiple instances of Atomic Stealer activity were seen across one customer’s environment, with two devices communicating with Atomic Stealer C2 infrastructure. During this incident, one device was observed making an HTTP GET request to the IP 45.94.47[.]149 (ASN: AS60781 LeaseWeb Netherlands B.V.). These connections targeted the URI /api/tasks/[base64string, using the user agent curl/8.7.1.

Shortly afterward, the device began making repeated connections over port 80 to the same external IP, 45.94.47[.]149. This activity continued for several days until Darktrace detected the device making an HTTP POST request to a new IP, 45.94.47[.]211 (ASN: AS57043 Hostkey B.V.), this time targeting the URI /contact, again using the curl/8.7.1 user agent. Similar to the other IPs observed in beaconing activity, OSINT reporting later linked this one to information stealer C2 infrastructure [7].

Figure 6: Darktrace’s detection of suspicious beaconing connectivity with the suspicious IP 45.94.47.211.

Further investigation into this customer’s network revealed that similar activity had been occurring as far back as August, when Darktrace detected data exfiltration on a second device. Cyber AI Analyst identified this device making a single HTTP POST connection to the external IP 45.94.47[.]144, another IP with malicious links [8], using the user agent curl/8.7.1 and targeting the URI /contact.

Figure 7: Cyber AI Analyst investigation finding a successful POST request to 45.94.47[.]144 for the device within the third customer environment.

A deeper investigation into the technical details within the POST request revealed the presence of a file named “out.zip”, suggesting potential data exfiltration.

Figure 8: Advanced Search log in Darktrace / NETWORK showing “out.zip”, indicating potential data exfiltration for a device within the third customer environment.

Similarly, in another environment, Darktrace was able to collect a packet capture (PCAP) of suspected Atomic Stealer activity, which revealed potential indicators of data exfiltration. This included the presence of the “out.zip” file being exfiltrated via an HTTP POST request, along with data that appeared to contain details of an Electrum cryptocurrency wallet and possible passwords.

Read more about Darktrace’s full deep dive into a similar case where this tactic was leveraged by malware as part of an elaborate cryptocurrency scam.

Figure 9: PCAP of an HTTP POST request showing the file “out.zip” and details of Electrum Cryptocurrency wallet.

Although recent research attributes the “out.zip” file to a new variant named SHAMOS [9], it has also been linked more broadly to Atomic Stealer [10]. Indeed, this is not the first instance where Darktrace has seen the “out.zip” file in cases involving Atomic Stealer either. In a previous blog detailing a social engineering campaign that targeted cryptocurrency users with the Realst Stealer, the macOS version of Realst contained a binary that was found to be Atomic Stealer, and similar IoCs were identified, including artifacts of data exfiltration such as the “out.zip” file.

Conclusion‍

The rapid rise of Atomic Stealer and its ability to target macOS marks a significant shift in the threat landscape and should serve as a clear warning to Apple users who were traditionally perceived as more secure in a malware ecosystem historically dominated by Windows-based threats.

Atomic Stealer’s growing popularity is now challenging that perception, expanding its reach and accessibility to a broader range of victims. Even more concerning is the emergence of a variant embedded with a backdoor, which is likely to increase its appeal among a diverse range of threat actors. Darktrace’s ability to adapt and detect new tactics and IoCs in real time delivers the proactive defense organizations need to protect themselves against emerging threats before they can gain momentum.

Credit to Isabel Evans (Cyber Analyst), Dylan Hinz (Associate Principal Cyber Analyst)
Edited by Ryan Traill (Analyst Content Lead)

Appendices

References

1. https://www.scworld.com/news/infostealers-targeting-macos-jumped-by-101-in-second-half-of-2024

2. https://www.kandji.io/blog/amos-macos-stealer-analysis

3. https://www.broadcom.com/support/security-center/protection-bulletin/amos-stealer-adds-backdoor

4. https://moonlock.com/amos-backdoor-persistent-access

5. https://www.virustotal.com/gui/ip-address/45.94.47.158/detection

6. https://www.trendmicro.com/en_us/research/25/i/an-mdr-analysis-of-the-amos-stealer-campaign.html

7. https://www.virustotal.com/gui/ip-address/45.94.47.211/detection

8. https://www.virustotal.com/gui/ip-address/45.94.47.144/detection

9. https://securityaffairs.com/181441/malware/over-300-entities-hit-by-a-variant-of-atomic-macos-stealer-in-recent-campaign.html

10. https://binhex.ninja/malware-analysis-blogs/amos-stealer-atomic-stealer-malware.html

Darktrace Model Detections

Darktrace / NETWORK

Compromise / Beaconing Activity To External Rare
Compromise / HTTP Beaconing to New IP
Compromise / HTTP Beaconing to Rare Destination
Anomalous Connection / New User Agent to IP Without Hostname
Device / New User Agent
Compromise / Sustained TCP Beaconing Activity To Rare Endpoint
Compromise / Slow Beaconing Activity To External Rare
Anomalous Connection / Posting HTTP to IP Without Hostname
Compromise / Quick and Regular Windows HTTP Beaconing

Autonomous Response

Antigena / Network / Significant Anomaly::Antigena Alerts Over Time Block
Antigena / Network / Significant Anomaly::Antigena Significant Anomaly from Client Block
Antigena / Network / External Threat::Antigena Suspicious Activity Block

List of IoCs

45.94.47[.]149 – IP – Atomic C2 Endpoint
45.94.47[.]144 – IP – Atomic C2 Endpoint
45.94.47[.]158 – IP – Atomic C2 Endpoint
45.94.47[.]211 – IP – Atomic C2 Endpoint
out.zip - File Output – Possible ZIP file for Data Exfiltration

MITRE ATT&CK Mapping:

Tactic –Technique – Sub-Technique

Execution - T1204.002 - User Execution: Malicious File

Credential Access - T1555.001 - Credentials from Password Stores: Keychain

Credential Access - T1555.003 - Credentials from Web Browsers

Command & Control - T1071 - Application Layer Protocol

Exfiltration - T1041 - Exfiltration Over C2 Channel

About the author

Isabel Evans

Cyber Analyst

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