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July 26, 2022

Identifying PrivateLoader Network Threats

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Jul 2022
Learn how Darktrace identifies network-based indicators of compromise for the PrivateLoader malware. Gain insights into advanced threat detection.

Instead of delivering their malicious payloads themselves, threat actors can pay certain cybercriminals (known as pay-per-install (PPI) providers) to deliver their payloads for them. Since January 2022, Darktrace’s SOC has observed several cases of PPI providers delivering their clients’ payloads using a modular malware downloader known as ‘PrivateLoader’.

This blog will explore how these PPI providers installed PrivateLoader onto systems and outline the steps which the infected PrivateLoader bots took to install further malicious payloads. The details provided here are intended to provide insight into the operations of PrivateLoader and to assist security teams in identifying PrivateLoader bots within their own networks.  

Threat Summary 

Between January and June 2022, Darktrace identified the following sequence of network behaviours within the environments of several Darktrace clients. Patterns of activity involving these steps are paradigmatic examples of PrivateLoader activity:

1. A victim’s device is redirected to a page which instructs them to download a password-protected archive file from a file storage service — typically Discord Content Delivery Network (CDN)

2. The device contacts a file storage service (typically Discord CDN) via SSL connections

3. The device either contacts Pastebin via SSL connections, makes an HTTP GET request with the URI string ‘/server.txt’ or ‘server_p.txt’ to 45.144.225[.]57, or makes an HTTP GET request with the URI string ‘/proxies.txt’ to 212.193.30[.]45

4. The device makes an HTTP GET request with the URI string ‘/base/api/statistics.php’ to either 212.193.30[.]21, 85.202.169[.]116, 2.56.56[.]126 or 2.56.59[.]42

5. The device contacts a file storage service (typically Discord CDN) via SSL connections

6. The device makes a HTTP POST request with the URI string ‘/base/api/getData.php’ to either 212.193.30[.]21, 85.202.169[.]116, 2.56.56[.]126 or 2.56.59[.]42

7. The device finally downloads malicious payloads from a variety of endpoints

The PPI Business 

Before exploring PrivateLoader in more detail, the pay-per-install (PPI) business should be contextualized. This consists of two parties:  

1. PPI clients - actors who want their malicious payloads to be installed onto a large number of target systems. PPI clients are typically entry-level threat actors who seek to widely distribute commodity malware [1]

2. PPI providers - actors who PPI clients can pay to install their malicious payloads 

As the smugglers of the cybercriminal world, PPI providers typically advertise their malware delivery services on underground web forums. In some cases, PPI services can even be accessed via Clearnet websites such as InstallBest and InstallShop [2] (Figure 1).  

Figure 1: A snapshot of the InstallBest PPI login page [2]


To utilize a PPI provider’s service, a PPI client must typically specify: 

(A)  the URLs of the payloads which they want to be installed

(B)  the number of systems onto which they want their payloads to be installed

(C)  their geographical targeting preferences. 

Payment of course, is also required. To fulfil their clients’ requests, PPI providers typically make use of downloaders - malware which instructs the devices on which it is running to download and execute further payloads. PPI providers seek to install their downloaders onto as many systems as possible. Follow-on payloads are usually determined by system information garnered and relayed back to the PPI providers’ command and control (C2) infrastructure. PPI providers may disseminate their downloaders themselves, or they may outsource the dissemination to third parties called ‘affiliates’ [3].  

Back in May 2021, Intel 471 researchers became aware of PPI providers using a novel downloader (dubbed ‘PrivateLoader’) to conduct their operations. Since Intel 471’s public disclosure of the downloader back in Feb 2022 [4], several other threat research teams, such as the Walmart Cyber Intel Team [5], Zscaler ThreatLabz [6], and Trend Micro Research [7] have all provided valuable insights into the downloader’s behaviour. 

Anatomy of a PrivateLoader Infection

The PrivateLoader downloader, which is written in C++, was originally monolithic (i.e, consisted of only one module). At some point, however, the downloader became modular (i.e, consisting of multiple modules). The modules communicate via HTTP and employ various anti-analysis methods. PrivateLoader currently consists of the following three modules [8]: 

  • The loader module: Instructs the system on which it is running to retrieve the IP address of the main C2 server and to download and execute the PrivateLoader core module
  • The core module: Instructs the system on which it is running to send system information to the main C2 server, to download and execute further malicious payloads, and to relay information regarding installed payloads back to the main C2 server
  • The service module: Instructs the system on which it is running to keep the PrivateLoader modules running

Kill Chain Deep-Dive 

The chain of activity starts with the user’s browser being redirected to a webpage which instructs them to download a password-protected archive file from a file storage service such as Discord CDN. Discord is a popular VoIP and instant messaging service, and Discord CDN is the service’s CDN infrastructure. In several cases, the webpages to which users’ browsers were redirected were hosted on ‘hero-files[.]com’ (Figure 2), ‘qd-files[.]com’, and ‘pu-file[.]com’ (Figure 3). 

Figure 2: An image of a page hosted on hero-files[.]com - an endpoint which Darktrace observed systems contacting before downloading PrivateLoader from Discord CDN
Figure 3: An image of a page hosted on pu-file[.]com- an endpoint which Darktrace observed systems contacting before downloading PrivateLoader from Discord CDN


On attempting to download cracked/pirated software, users’ browsers were typically redirected to download instruction pages. In one case however, a user’s device showed signs of being infected with the malicious Chrome extension, ChromeBack [9], immediately before it contacted a webpage providing download instructions (Figure 4). This may suggest that cracked software downloads are not the only cause of users’ browsers being redirected to these download instruction pages (Figure 5). 

Figure 4: The event log for this device (taken from the Darktrace Threat Visualiser interface) shows that the device contacted endpoints associated with ChromeBack ('freychang[.]fun') prior to visiting a page ('qd-file[.]com') which instructed the device’s user to download an archive file from Discord CDN
 Figure 5: An image of the website 'crackright[.]com'- a provider of cracked software. Systems which attempted to download software from this website were subsequently led to pages providing instructions to download a password-protected archive from Discord CDN


After users’ devices were redirected to pages instructing them to download a password-protected archive, they subsequently contacted cdn.discordapp[.]com over SSL. The archive files which users downloaded over these SSL connections likely contained the PrivateLoader loader module. Immediately after contacting the file storage endpoint, users’ devices were observed either contacting Pastebin over SSL, making an HTTP GET request with the URI string ‘/server.txt’ or ‘server_p.txt’ to 45.144.225[.]57, or making an HTTP GET request with the URI string ‘/proxies.txt’ to 212.193.30[.]45 (Figure 6).

Distinctive user-agent strings such as those containing question marks (e.g. ‘????ll’) and strings referencing outdated Chrome browser versions were consistently seen in these HTTP requests. The following chrome agent was repeatedly observed: ‘Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/74.0.3729.169 Safari/537.36’.

In some cases, devices also displayed signs of infection with other strains of malware such as the RedLine infostealer and the BeamWinHTTP malware downloader. This may suggest that the password-protected archives embedded several payloads.

Figure 6: This figure, obtained from Darktrace's Advanced Search interface, represents the post-infection behaviour displayed by a PrivateLoader bot. After visiting hero-files[.]com and downloading the PrivateLoader loader module from Discord CDN, the device can be seen making HTTP GET requests for ‘/proxies.txt’ and ‘/server.txt’ and contacting pastebin[.]com

It seems that PrivateLoader bots contact Pastebin, 45.144.225[.]57, and 212.193.30[.]45 in order to retrieve the IP address of PrivateLoader’s main C2 server - the server which provides PrivateLoader bots with payload URLs. This technique used by the operators of PrivateLoader closely mirrors the well-known espionage tactic known as ‘dead drop’.

The dead drop is a method of espionage tradecraft in which an individual leaves a physical object such as papers, cash, or weapons in an agreed hiding spot so that the intended recipient can retrieve the object later on without having to come in to contact with the source. When threat actors host information about core C2 infrastructure on intermediary endpoints, the hosted information is analogously called a ‘Dead Drop Resolver’ or ‘DDR’. Example URLs of DDRs used by PrivateLoader:

  • https://pastebin[.]com/...
  • http://212.193.30[.]45/proxies.txt
  • http://45.144.225[.]57/server.txt
  • http://45.144.255[.]57/server_p.txt

The ‘proxies.txt’ DDR hosted on 212.193.40[.]45 contains a list of 132 IP address / port pairs. The 119th line of this list includes a scrambled version of the IP address of PrivateLoader’s main C2 server (Figures 7 & 8). Prior to June, it seems that the main C2 IP address was ‘212.193.30[.]21’, however, the IP address appears to have recently changed to ‘85.202.169[.]116’. In a limited set of cases, Darktrace also observed PrivateLoader bots retrieving payload URLs from 2.56.56[.]126 and 2.56.59[.]42 (rather than from 212.193.30[.]21 or 85.202.169[.]116). These IP addresses may be hardcoded secondary C2 address which PrivateLoader bots use in cases where they are unable to retrieve the primary C2 address from Pastebin, 212.193.30[.]45 or 45.144.255[.]57 [10]. 

Figure 7: Before June, the 119th entry of the ‘proxies.txt’ file lists '30.212.21.193' -  a scrambling of the ‘212.193.30[.]21’ main C2 IP address
Figure 8: Since June, the 119th entry of the ‘proxies.txt’ file lists '169.85.116.202' - a scrambling of the '85.202.169[.]116' main C2 IP address

Once PrivateLoader bots had retrieved C2 information from either Pastebin, 45.144.225[.]57, or 212.193.30[.]45, they went on to make HTTP GET requests for ‘/base/api/statistics.php’ to either 212.193.30[.]21, 85.202.169[.]116, 2.56.56[.]126, or 2.56.59[.]42 (Figure 9). The server responded to these requests with an XOR encrypted string. The strings were encrypted using a 1-byte key [11], such as 0001101 (Figure 10). Decrypting the string revealed a URL for a BMP file hosted on Discord CDN, such as ‘hxxps://cdn.discordapp[.]com/attachments/978284851323088960/986671030670078012/PL_Client.bmp’. These encrypted URLs appear to be file download paths for the PrivateLoader core module. 

Figure 9: HTTP response from server to an HTTP GET request for '/base/api/statistics.php'
Figure 10: XOR decrypting the string with the one-byte key, 00011101, outputs a URL in CyberChef

After PrivateLoader bots retrieved the 'cdn.discordapp[.]com’ URL from 212.193.30[.]21, 85.202.169[.]116, 2.56.56[.]126, or 2.56.59[.]42, they immediately contacted Discord CDN via SSL connections in order to obtain the PrivateLoader core module. Execution of this module resulted in the bots making HTTP POST requests (with the URI string ‘/base/api/getData.php’) to the main C2 address (Figures 11 & 12). Both the data which the PrivateLoader bots sent over these HTTP POST requests and the data returned via the C2 server’s HTTP responses were heavily encrypted using a combination of password-based key derivation, base64 encoding, AES encryption, and HMAC validation [12]. 

Figure 11: The above image, taken from Darktrace's Advanced Search interface, shows a PrivateLoader bot carrying out the following steps: contact ‘hero-files[.]com’ --> contact ‘cdn.discordapp[.]com’ --> retrieve ‘/proxies.txt’ from 212.193.30[.]45 --> retrieve ‘/base/api/statistics.php’ from 212.193.30[.]21 --> contact ‘cdn.discordapp[.]com --> make HTTP POST request with the URI ‘base/api/getData.php’ to 212.193.30[.]21
Figure 12: A PCAP of the data sent via the HTTP POST (in red), and the data returned by the C2 endpoint (in blue)

These ‘/base/api/getData.php’ POST requests contain a command, a campaign name and a JSON object. The response may either contain a simple status message (such as “success”) or a JSON object containing URLs of payloads. After making these HTTP connections, PrivateLoader bots were observed downloading and executing large volumes of payloads (Figure 13), ranging from crypto-miners to infostealers (such as Mars stealer), and even to other malware downloaders (such as SmokeLoader). In some cases, bots were also seen downloading files with ‘.bmp’ extensions, such as ‘Service.bmp’, ‘Cube_WW14.bmp’, and ‘NiceProcessX64.bmp’, from 45.144.225[.]57 - the same DDR endpoint from which PrivateLoader bots retrieved main C2 information. These ‘.bmp’ payloads are likely related to the PrivateLoader service module [13]. Certain bots made follow-up HTTP POST requests (with the URI string ‘/service/communication.php’) to either 212.193.30[.]21 or 85.202.169[.]116, indicating the presence of the PrivateLoader service module, which has the purpose of establishing persistence on the device (Figure 14). 

Figure 13: The above image, taken from Darktrace's Advanced Search interface, outlines the plethora of malware payloads downloaded by a PrivateLoader bot after it made an HTTP POST request to the ‘/base/api/getData.php’ endpoint. The PrivateLoader service module is highlighted in red
Figure 14: The event log for a PrivateLoader bot, obtained from the Threat Visualiser interface, shows a device making HTTP POST requests to ‘/service/communication.php’ and connecting to the NanoPool mining pool, indicating successful execution of downloaded payloads

In several observed cases, PrivateLoader bots downloaded another malware downloader called ‘SmokeLoader’ (payloads named ‘toolspab2.exe’ and ‘toolspab3.exe’) from “Privacy Tools” endpoints [14], such as ‘privacy-tools-for-you-802[.]com’ and ‘privacy-tools-for-you-783[.]com’. These “Privacy Tools” domains are likely impersonation attempts of the legitimate ‘privacytools[.]io’ website - a website run by volunteers who advocate for data privacy [15]. 

After downloading and executing malicious payloads, PrivateLoader bots were typically seen contacting crypto-mining pools, such as NanoPool, and making HTTP POST requests to external hosts associated with SmokeLoader, such as hosts named ‘host-data-coin-11[.]com’ and ‘file-coin-host-12[.]com’ [16]. In one case, a PrivateLoader bot went on to exfiltrate data over HTTP to an external host named ‘cheapf[.]link’, which was registered on the 14th March 2022 [17]. The name of the file which the PrivateLoader bot used to exfiltrate data was ‘NOP8QIMGV3W47Y.zip’, indicating information stealing activities by Mars Stealer (Figure 15) [18]. By saving the HTTP stream as raw data and utilizing a hex editor to remove the HTTP header portions, the hex data of the ZIP file was obtained. Saving the hex data using a ‘.zip’ extension and extracting the contents, a file directory consisting of system information and Chrome and Edge browsers’ Autofill data in cleartext .txt file format could be seen (Figure 16).

Figure 15: A PCAP of a PrivateLoader bot’s HTTP POST request to cheapf[.]link, with data sent by the bot appearing to include Chrome and Edge autofill data, as well as system information
Figure 16: File directory structure and files of the ZIP archive 

When left unattended, PrivateLoader bots continued to contact C2 infrastructure in order to relay details of executed payloads and to retrieve URLs of further payloads. 

Figure 17: Timeline of the attack

Darktrace Coverage 

Most of the incidents surveyed for this article belonged to prospective customers who were trialling Darktrace with RESPOND in passive mode, and thus without the ability for autonomous intervention. However in all observed cases, Darktrace DETECT was able to provide visibility into the actions taken by PrivateLoader bots. In one case, despite the infected bot being disconnected from the client’s network, Darktrace was still able to provide visibility into the device’s network behaviour due to the client’s usage of Darktrace/Endpoint. 

If a system within an organization’s network becomes infected with PrivateLoader, it will display a range of anomalous network behaviours before it downloads and executes malicious payloads. For example, it will contact Pastebin or make HTTP requests with new and unusual user-agent strings to rare external endpoints. These network behaviours will generate some of the following alerts on the Darktrace UI:

  • Compliance / Pastebin 
  • Device / New User Agent and New IP
  • Device / New User Agent
  • Device / Three or More New User Agents
  • Anomalous Connection / New User Agent to IP Without Hostname
  • Anomalous Connection / POST to PHP on New External Host
  • Anomalous Connection / Posting HTTP to IP Without Hostname

Once the infected host obtains URLs for malware payloads from a C2 endpoint, it will likely start to download and execute large volumes of malicious files. These file downloads will usually cause Darktrace to generate some of the following alerts:

  • Anomalous File / EXE from Rare External Location
  • Anomalous File / Numeric Exe Download
  • Anomalous File / Masqueraded File Transfer
  • Anomalous File / Multiple EXE from Rare External Locations
  • Device / Initial Breach Chain Compromise

If RESPOND is deployed in active mode, Darktrace will be able to autonomously block the download of additional malware payloads onto the target machine and the subsequent beaconing or crypto-mining activities through network inhibitors such as ‘Block matching connections’, ‘Enforce pattern of life’ and ‘Block all outgoing traffic’. The ‘Enforce pattern of life’ action results in a device only being able to make connections and data transfers which Darktrace considers normal for that device. The ‘Block all outgoing traffic’ action will cause all traffic originating from the device to be blocked. If the customer has Darktrace’s Proactive Threat Notification (PTN) service, then a breach of an Enhanced Monitoring model such as ‘Device / Initial Breach Chain Compromise’ will result in a Darktrace SOC analyst proactively notifying the customer of the suspicious activity. Below is a list of Darktrace RESPOND (Antigena) models which would be expected to breach due to PrivateLoader activity. Such models can seriously hamper attempts made by PrivateLoader bots to download malicious payloads. 

  • Antigena / Network / External Threat / Antigena Suspicious File Block
  • Antigena / Network / Significant Anomaly / Antigena Controlled and Model Breach
  • Antigena / Network / External Threat / Antigena File then New Outbound Block
  • Antigena / Network / Significant Anomaly / Antigena Significant Anomaly from Client Block 
  • Antigena / Network / Significant Anomaly / Antigena Breaches Over Time Block

In one observed case, the infected bot began to download malicious payloads within one minute of becoming infected with PrivateLoader. Since RESPOND was correctly configured, it was able to immediately intervene by autonomously enforcing the device’s pattern of life for 2 hours and blocking all of the device’s outgoing traffic for 10 minutes (Figure 17). When malware moves at such a fast pace, the availability of autonomous response technology, which can respond immediately to detected threats, is key for the prevention of further damage.  

Figure 18: The event log for a Darktrace RESPOND (Antigena) model breach shows Darktrace RESPOND performing inhibitive actions once the PrivateLoader bot begins to download payloads

Conclusion

By investigating PrivateLoader infections over the past couple of months, Darktrace has observed PrivateLoader operators making changes to the downloader’s main C2 IP address and to the user-agent strings which the downloader uses in its C2 communications. It is relatively easy for the operators of PrivateLoader to change these superficial network-based features of the malware in order to evade detection [19]. However, once a system becomes infected with PrivateLoader, it will inevitably start to display anomalous patterns of network behaviour characteristic of the Tactics, Techniques and Procedures (TTPs) discussed in this blog.

Throughout 2022, Darktrace observed overlapping patterns of network activity within the environments of several customers, which reveal the archetypal steps of a PrivateLoader infection. Despite the changes made to PrivateLoader’s network-based features, Darktrace’s Self-Learning AI was able to continually identify infected bots, detecting every stage of an infection without relying on known indicators of compromise. When configured, RESPOND was able to immediately respond to such infections, preventing further advancement in the cyber kill chain and ultimately preventing the delivery of floods of payloads onto infected devices.

IoCs

MITRE ATT&CK Techniques Observed

References

[1], [8],[13] https://www.youtube.com/watch?v=Ldp7eESQotM  

[2] https://news.sophos.com/en-us/2021/09/01/fake-pirated-software-sites-serve-up-malware-droppers-as-a-service/

[3] https://www.researchgate.net/publication/228873118_Measuring_Pay-per Install_The_Commoditization_of_Malware_Distribution 

[4], [15] https://intel471.com/blog/privateloader-malware

[5] https://medium.com/walmartglobaltech/privateloader-to-anubis-loader-55d066a2653e 

[6], [10],[11], [12] https://www.zscaler.com/blogs/security-research/peeking-privateloader 

[7] https://www.trendmicro.com/en_us/research/22/e/netdooka-framework-distributed-via-privateloader-ppi.html

[9] https://www.gosecure.net/blog/2022/02/10/malicious-chrome-browser-extension-exposed-chromeback-leverages-silent-extension-loading/

[14] https://www.proofpoint.com/us/blog/threat-insight/malware-masquerades-privacy-tool 

[16] https://asec.ahnlab.com/en/30513/ 

[17]https://twitter.com/0xrb/status/1515956690642161669

[18] https://isc.sans.edu/forums/diary/Arkei+Variants+From+Vidar+to+Mars+Stealer/28468

[19] http://detect-respond.blogspot.com/2013/03/the-pyramid-of-pain.html

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.
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Sam Lister
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Shuh Chin Goh
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January 2, 2025

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Inside the SOC

A Snake in the Net: Defending Against AiTM Phishing Threats and Mamba 2FA

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What are Adversary-in-the-Middle (AiTM) phishing kits?

Phishing-as-a-Service (PhaaS) platforms have significantly lowered the barriers to entry for cybercriminals, enabling a new wave of sophisticated phishing attacks. Among the most concerning developments in this landscape is the emergence of Adversary-in-the-Middle (AiTM) phishing kits, which enhance traditional phishing tactics by allowing attackers to intercept and manipulate communications in real-time. The PhaaS marketplace offers a wide variety of innovative capabilities, with basic services starting around USD 120 and more advanced services costing around USD 250 monthly [1].

These AiTM kits are designed to create convincing decoy pages that mimic legitimate login interfaces, often pre-filling user information to increase credibility. By acting as a man-in-the-middle, attackers can harvest sensitive data such as usernames, passwords, and even multi-factor authentication (MFA) tokens without raising immediate suspicion. This capability not only makes AiTM attacks more effective but also poses a significant challenge for cybersecurity defenses [2].

Mamba 2FA is one such example of a PhaaS strain with AiTM capabilities that has emerged as a significant threat to users of Microsoft 365 and other enterprise systems. Discovered in May 2024, Mamba 2FA employs advanced AiTM tactics to bypass MFA, making it particularly dangerous for organizations relying on these security measures.

What is Mamba 2FA?

Phishing Mechanism

Mamba 2FA employs highly convincing phishing pages that closely mimic legitimate Microsoft services like OneDrive and SharePoint. These phishing URLs are crafted with a specific structure, incorporating Base64-encoded parameters. This technique allows attackers to tailor the phishing experience to the targeted organization, making the deception more effective. If an invalid parameter is detected, users are redirected to a benign error page, which helps evade automated detection systems [5].

Figure 1: Phishing page mimicking the Microsoft OneDrive service.

Real-Time Communication

A standout feature of Mamba 2FA is its use of the Socket.IO JavaScript library. This library facilitates real-time communication between the phishing page and the attackers' backend servers. As users input sensitive information, such as usernames, passwords, and MFA tokens on the phishing site, this data is immediately relayed to the attackers, enabling swift unauthorized access [5].

Multi-Factor Authentication Bypass

Mamba 2FA specifically targets MFA methods that are not resistant to phishing, such as one-time passwords (OTPs) and push notifications. When a user enters their MFA token, it is captured in real-time by the attackers, who can then use it to access the victim's account immediately. This capability significantly undermines traditional security measures that rely on MFA for account protection.

Infrastructure and Distribution

The platform's infrastructure consists of two main components: link domains and relay servers. Link domains handle initial phishing attempts, while relay servers are responsible for stealing credentials and completing login processes on behalf of the attacker. The relay servers are designed to mask their IP addresses by using proxy services, making it more difficult for security systems to block them [3].

Evasion Techniques

To evade detection by security tools, Mamba 2FA employs several strategies:

  • Sandbox Detection: The platform can detect if it is being analyzed in a sandbox environment and will redirect users to harmless pages like Google’s 404 error page.
  • Dynamic URL Generation: The URLs used in phishing attempts are frequently rotated and often short-lived to avoid being blacklisted by security solutions.
  • HTML Attachments: Phishing emails often include HTML attachments that appear benign but contain hidden JavaScript that redirects users to the phishing page [5].

Darktrace’s Coverage of Mamba 2FA

Starting in July 2024, the Darktrace Threat Research team detected a sudden rise in Microsoft 365 customer accounts logging in from unusual external sources. These accounts were accessed from an anomalous endpoint, 2607:5500:3000:fea[::]2, and exhibited unusual behaviors upon logging into Software-as-a-Service (SaaS) accounts. This activity strongly correlates with a phishing campaign using Mamba 2FA, first documented in late June 2024 and tracked as Mamba 2FA by Sekoia [2][3].

Darktrace / IDENTITY  was able to identify the initial stages of the Mamba 2FA campaign by correlating subtle anomalies, such as unusual SaaS login locations. Using AI based on peer group analysis, it detected unusual behavior associated with these attacks. By leveraging Autonomous Response actions, Darktrace was able to neutralize these threats in every instance of the campaign detected.

On July 23, a SaaS user was observed logging in from a rare ASN and IP address, 2607:5500:3000:fea::2, originating from the US and successfully passed through MFA authentication.

Figure 2: Model Alert Event Log showing Darktrace’s detection of a SaaS user mailbox logging in from an unusual source it correlates with Mamba 2FA relay server.

Almost an hour later, the SaaS user was observed logging in from another suspicious IP address, 45.133.172[.]86, linked to ASN AS174 COGENT-174. This IP, originating from the UK, successfully passed through MFA validation.

Following this unusual access, the SaaS user was notably observed reading emails and files that could contain sensitive payment and contract information. This behavior suggests that the attacker may have been leveraging contextual information about the target to craft further malicious phishing emails or fraudulent invoices. Subsequently, the user was detected creating a new mailbox rule titled 'fdsdf'. This rule was configured to redirect emails from a specific domain to the 'Deleted Items' folder and automatically mark them as read.

Implications of Unusual Email Rules

Such unusual email rule configurations are a common tactic employed by attackers. They often use these rules to automatically forward emails containing sensitive keywords—such as "invoice”, "payment", or "confidential"—to an external address. Additionally, these rules help conceal malicious activities, keeping them hidden from the target and allowing the attacker to operate undetected.

Figure 3: The model alert “SaaS / Compliance / Anomalous New Email Rule,” pertaining to the unusual email rule created by the SaaS user named ‘fdsdf’.

Blocking the action

A few minutes later, the SaaS user from the unusual IP address 45.133.172[.]86 was observed attempting to send an email with the subject “RE: Payments.” Subsequently, Darktrace detected the user engaging in activities that could potentially establish persistence in the compromised account, such as registering a new authenticator app. Recognizing this sequence of anomalous behaviors, Darktrace implemented an Autonomous Response inhibitor, disabling the SaaS user for two hours. This action effectively contained potential malicious activities, such as the distribution of phishing emails and fraudulent invoices, and gave the customer’s security team the necessary time to conduct a thorough investigation and implement appropriate security measures.

Figure 4: Device Event Log displaying Darktrace’s Autonomous Response taking action by blocking the SaaS account.
Figure 5: Darktrace / IDENTITY highlighting the 16 model alerts that triggered during the observed compromise.

In another example from mid-July, similar activities related to the campaign were observed on another customer network. A SaaS user was initially detected logging in from the unusual external endpoint 2607:5500:3000:fea[::]2.

Figure 6: The SaaS / Compromise / SaaS Anomaly Following Anomalous Login model alert was triggered by an unusual login from a suspicious IP address linked to Mamba 2FA.

A few minutes later, in the same manner as demonstrated in the previous case, the actor was observed logging in from another rare endpoint, 102.68.111[.]240. However, this time it was from a source IP located in Lagos, Nigeria, which no other user on the network had been observed connecting from. Once logged in, the SaaS user updated the settings to "User registered Authenticator App with Notification and Code," a possible attempt to maintain persistence in the SaaS account.

Figure 7: Darktrace / IDENTITY highlighted the regular locations for the SaaS user. The rarity scores associated with the Mamba 2FA IP location and another IP located in Nigeria were classified as having very low regularity scores for this user.

Based on unusual patterns of user behavior, a Cyber AI Analyst Incident was also generated, detailing all potential account hijacking activities. Darktrace also applied an Autonomous Response action, disabling the user for over five hours. This swift action was crucial in preventing further unauthorized access, potential data breaches and further implications.

Figure 8: Cyber AI Analyst Incident detailing the unusual activities related to the SaaS account hijacking.

Since the customer had subscribed to Darktrace Security Operations Centre (SOC) services, Darktrace analysts conducted an additional human investigation confirming the account compromise.

How Darktrace Combats Phishing Threats

The initial entry point for Mamba 2FA account compromises primarily involves phishing campaigns using HTML attachments and deceptive links. These phishing attempts are designed to mimic legitimate Microsoft services, such as OneDrive and SharePoint, making them appear authentic to unsuspecting users. Darktrace / EMAIL leverages multiple capabilities to analyze email content for known indicators of phishing. This includes looking for suspicious URLs, unusual attachments (like HTML files with embedded JavaScript), and signs of social engineering tactics commonly used in phishing campaigns like Mamba 2FA. With these capabilities, Darktrace successfully detected Mamba 2FA phishing emails in networks where this tool is integrated into the security layers, consequently preventing further implications and account hijacks of their users.

Mamba 2FA URL Structure and Domain Names

The URL structure used in Mamba 2FA phishing attempts is specifically designed to facilitate the capture of user credentials and MFA tokens while evading detection. These phishing URLs typically follow a pattern that incorporates Base64-encoded parameters, which play a crucial role in the operation of the phishing kit.

The URLs associated with Mamba 2FA phishing pages generally follow this structure [6]:

https://{domain}/{m,n,o}/?{Base64 string}

Below are some potential Mamba 2FA phishing emails, with the Base64 strings already decoded, that were classified as certain threats by Darktrace / EMAIL. This classification was based on identifying multiple suspicious characteristics, such as HTML attachments containing JavaScript code, emails from senders with no previous association with the recipients, analysis of redirect links, among others. These emails were autonomously blocked from being delivered to users' inboxes.

Figure 9: Darktrace / EMAIL highlighted a possible phishing email from Mamba 2FA, which was classified as a 100% anomaly.
Figure 10: Darktrace / EMAIL highlighted a URL that resembles the characteristics associated with Mamba 2FA.

Conclusion

The rise of PhaaS platforms and the advent of AiTM phishing kits represent a concerning evolution in cyber threats, pushing the boundaries of traditional phishing tactics and exposing significant vulnerabilities in current cybersecurity defenses. The ability of these attacks to effortlessly bypass traditional security measures like MFA underscores the need for more sophisticated, adaptive strategies to combat these evolving threats.

By identifying and responding to anomalous activities within Microsoft 365 accounts, Darktrace not only highlights the importance of comprehensive monitoring but also sets a new standard for proactive threat detection. Furthermore, the autonomous threat response capabilities and the exceptional proficiency of Darktrace / EMAIL in intercepting and neutralizing sophisticated phishing attacks illustrate a robust defense mechanism that can effectively safeguard users and maintain the integrity of digital ecosystems.

Credit to Patrick Anjos (Senior Cyber Analyst) and Nahisha Nobregas (Senior Cyber Analyst)

Appendices

Darktrace Model Detections

  • SaaS / Access / M365 High Risk Level Login
  • SaaS / Access / Unusual External Source for SaaS Credential Use
  • SaaS / Compromise / Login From Rare Endpoint While User Is Active
  • SaaS / Compliance / M365 Security Information Modified
  • SaaS / Compromise / Unusual Login and New Email Rule
  • SaaS / Email Nexus / Suspicious Internal Exchange Activity
  • SaaS / Compliance / Anomalous New Email Rule
  • SaaS / Email Nexus / Possible Outbound Email Spam
  • SaaS / Compromise / Unusual Login and Account Update
  • SaaS / Compromise / SaaS Anomaly Following Anomalous Login
  • SaaS / Compliance / M365 Security Information Modified
  • SaaS / Compromise / Login From Rare Endpoint While User Is Active
  • SaaS / Compromise / Unusual Login, Sent Mail, Deleted Sent
  • SaaS / Unusual Activity / Multiple Unusual SaaS Activities
  • SaaS / Email Nexus / Unusual Login Location Following Link to File Storage
  • SaaS / Unusual Activity / Multiple Unusual External Sources For SaaS Credential
  • IaaS / Compliance / Uncommon Azure External User Invite
  • SaaS / Compliance / M365 External User Added to Group
  • SaaS / Access / M365 High Risk Level Login
  • SaaS / Compliance / M365 Security Information Modified
  • SaaS/ Unusual Activity / Unusual MFA Auth and SaaS Activity
  • SaaS / Compromise / Unusual Login and Account Update

Cyber AI Analyst Incidents:

  • Possible Hijack of Office365 Account
  • Possible Hijack of AzureActiveDirectory Account
  • Possible Unsecured Office365 Resource

List of Indicators of Compromise (IoCs)

IoC       Type    Description + Confidence

2607:5500:3000:fea[::]2 - IPv6 - Possible Mamba 2FA relay server

2607:5500:3000:1cab:[:]2 - IPv6 - Possible Mamba 2FA relay server

References

1.     https://securityaffairs.com/136953/cyber-crime/caffeine-phishing-platform.html

2.     https://any.run/cybersecurity-blog/analysis-of-the-phishing-campaign/

3.     https://www.bleepingcomputer.com/news/security/new-mamba-2fa-bypass-service-targets-microsoft-365-accounts/

4.     https://cyberinsider.com/microsoft-365-accounts-targeted-by-new-mamba-2fa-aitm-phishing-threat/

5.     https://blog.sekoia.io/mamba-2fa-a-new-contender-in-the-aitm-phishing-ecosystem/

MITRE ATT&CK Mapping

Tactic – Technique

DEFENSE EVASION, PERSISTENCE, PRIVILEGE ESCALATION, INITIAL ACCESS - Cloud Accounts

DISCOVERY - Cloud Service Dashboard

RESOURCE DEVELOPMENT - Compromise Accounts

CREDENTIAL ACCESS - Steal Web Session Cookie

PERSISTENCE - Account Manipulation

PERSISTENCE - Outlook Rules

RESOURCE DEVELOPMENT - Email Accounts

INITIAL ACCESS - Phishing

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About the author
Patrick Anjos
Senior Cyber Analyst

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January 8, 2025

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Darktrace Recognized in the Gartner® Magic Quadrant™ for Email Security Platforms

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Darktrace has been recognized in the first ever Gartner Magic Quadrant for Email Security Platforms (ESP).  As a Challenger, we have been recognized based on our Ability to Execute and Completeness of Vision.

The Gartner Magic Quadrant for Email Security is designed to help organizations evaluate which email security solutions might be the best fit for their needs by providing a visual representation of the market vendors and the strengths and cautions of different vendors. We encourage our customers to read the full report to get the complete picture.

Darktrace / EMAIL has a unique AI approach to identifying threats, including NLP and behavioral analysis, instead of traditional security measures like signatures and sandboxing – providing protection against advanced attacks like Business Email Compromise (BEC) and spear phishing. We believe our AI-first approach delivers high-quality solutions that our customers trust, allowing them to stay ahead of sophisticated threats that other tools miss.  

We’re proud of Darktrace’s rapid growth, geographic scale, and ability to execute effectively in the email security market, which reflect our commitment to delivering high-quality, reliable solutions that meet the evolving needs of our customers.

What do we believe makes Darktrace the fastest growing email security solution on the market?

An AI-first approach to innovation: Catching the threats others miss

As one of the founders of the ICES category, Darktrace has a long history of innovation, backed by over 200 patents. While other email security solutions are only just starting to apply machine learning (ML) techniques to outdated methods like signature analysis, reputation lists, and sandboxing, Darktrace has redefined the approach to email threat detection with its pioneering AI-driven anomaly detection engine.

Traditional ESPs often miss advanced threats because they rely on rules and signatures that focus on payloads and blindly trust known sources. This approach requires constant updates and frequently fails to detect threats like Business Email Compromise and Spear Phishing. In contrast, Darktrace / EMAIL uses advanced anomaly detection to identify the most sophisticated threats by focusing on unusual patterns and behaviors. This innovative approach has consistently delivered superior detection, stopping on average 58% of the threats that other solutions in the security stack miss.1

But our AI-first approach doesn’t stop at the inbox. At Darktrace, we transcend the limitations of traditional email security by leveraging a platform that unifies insights across multiple domains, providing robust protection against multi-domain threats. Our award-winning solutions defend the most popular attack vectors, including email, messaging, network, and identity protection. By combining signals from all domains, we establish unique behavioral profiles for each device and user, significantly enhancing detection precision.  

This pioneering approach has led to introducing industry-first advancements like QR code analysis and automated incident investigations, alongside game-changing functionality including:

  • Microsoft Teams security with advanced messaging analysis: The ability to identify critical early phishing and insider threats across both email and Microsoft Teams messaging.  
  • AI analyst narratives for improved end user reporting: that reduces phishing investigations by 60% by exposing unique narratives that provide the context of each received email and give feedback to each employee as they interact with their mail.2
  • Mailbox Security Assistant: to perform advanced behavioral browser analysis and stop malicious links within webpages, detecting and remediating 70% more malicious phishing links than traditional tools.3  
  • AI based, autonomous data loss prevention: to immediately secure your organization from misdirected emails, insider threats, and data loss—both classified and unclassified- without any administrative overhead.

Customer trust that fuels exponential growth

With almost 5,000 customers in under 5 years, we've doubled the growth rate of other vendors in the email security market. Our rapid market penetration, fueled by customer satisfaction and pioneering technology, showcases our revolutionary approach and sets new industry standards. 

Darktrace’s exceptional customer retention is fueled by an unparalleled customer experience, extensive regional support, dedicated account teams, and cutting-edge scalable technology. We pride ourselves on having a global network with local expertise, consisting of 110 worldwide offices which provide local language and technical support to offer multilingual, in-house assistance to our customer base.

Check it out – Darktrace / EMAIL has the highest percentage of 5-star ratings with a 4.8 rating on Gartner® Peer Insights™.4

Supporting every stage of your email security journey

Darktrace / EMAIL supports your security maturity journey, from first time security buyers to mature security stacks looking to augment their existing ESPs – by handling advanced threats without extensive tuning. And unlike other solutions that create a siloed and parallel solution, it works harmoniously with native email providers to create a modern email security stack. That’s why Darktrace performs well with first-time email security buyers and has strong renewal rates.

Integrating with Microsoft and Google via API, we replace traditional Secure Email Gateways (SEGs) with a modern, comprehensive email security stack. By combining approaches, our solution merges attack-centric analysis, which learns attack patterns and threat intelligence, with a business-centric approach that understands user behavior and inbox activity to deliver a unified stack that defends the entire threat spectrum – leading Darktrace to be recognized as Microsoft Partner of the year UK 2024.  

Our user-friendly, self-learning AI solution requires minimal tuning and deployment, making it perfect for customers looking for a highly usable but lightly configurable solution that will accompany them throughout their lifetime as they mature their email security stack in line with the evolving threat landscape.

Learn more

Get complimentary access to the full Gartner® Magic Quadrant™ for Email Security Platforms here.

To learn more about Darktrace / EMAIL or to get a free demo, check out the product hub.

References

1 From September 1 – December 31 2023, 58% of the phishing emails analyzed by Darktrace / EMAIL had already passed through native spam filtering and email security controls. (Darktrace End of Year Threat Report 2023)

2 When customers deployed the Darktrace / EMAIL Outlook Add-in there was a 60% decrease in incorrectly reported phishing emails. Darktrace Internal Research, 2024

3 Once a user reports phishing that contains a link, an automated second level triage engages our link analysis infrastructure expanding the signals analyzed. Darktrace Internal Research, 2024

4 Based on 252 reviews as of 19th December 2024

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About the author
Carlos Gray
Product Manager
Your data. Our AI.
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