This blog post describes the currently-circulating ransomware called BadRabbit and how Darktrace’s machine learning technology detects it.
This blog post describes the currently circulating ransomware called BadRabbit and how Darktrace’s machine learning technology detects it. BadRabbit is a self-propagating piece of malware that uses SMB to spread laterally. The campaign is reminiscent of the WannaCry and NotPetya attacks seen earlier this year. Some of the functionality in BadRabbit and the modus operandi of how it infects the targets is similar to the NotPetya attack.
The attack initially hit companies in Russia and Ukraine on October 24th, 2017. Since, the ransomware has spread to other countries across the world as well.
Infection process
The initial infection vector appears to be via drive-by downloads and social engineering using fake Adobe Flash player files. Various news and media websites predominantly but not exclusively in Russia and Ukraine served their visitors with pop-up alerts asking them to download Adobe Flash player software updates. It is unclear at this point if the websites were compromised, or if the advertisement networks were leveraged to display the fake Adobe Flash downloads.
This technique of presenting users with fake updates, commonly Adobe Flash, containing ransomware, adware or other forms of malware, has gained traction in the last six months. The same approach is often applied to trick users into inadvisable actions, such as downloading malware when browsing TV streaming websites, or torrent websites.
Once downloaded, a user has to execute the fake Adobe Flash player with administrative credentials manually. No exploits are used to automatically execute the malware. The malware creates a scheduled task for another file upon execution. The ransomware then encrypts files on the compromised devices using a hard-coded list of file extensions using a RSA 2048 key. The criminals demand a Bitcoin payment for decrypting the files. Users are pointed to a .onion website, which has to be accessed via Tor, to pay the ransom.
BadRabbit can brute-force its way over SMB to other devices on the network using a hard-coded list of common credentials. The malware appears to contain a stripped-down version of the Mimikatz tool which is used to gather credentials on Windows machines. This is likely used to further enhance its lateral movement capabilities using SMB.
Update (October 30, 2017): As the investigation of BadRabbit capabilities continued over the weekend, new details about how BadRabbit spreads have been uncovered. BadRabbit appears to be using the EternalRomance exploit that targets CVE-2017-0145, patched by Microsoft in March 2017, to propagate within the internal network over SMB. As Darktrace’s AI does not rely on identifying individual exploits to detect breaches, this latest discovery does not affect Darktrace’s capability to identify BadRabbit infections. All of the previously identified detection capabilities still hold true.
Darktrace instantly detects BadRabbit
Darktrace has strong detection capabilities for this campaign without the use of any signatures. In fact, we alerted a number of our customers within seconds of the initial fake Flash Player download on their respective networks, and well before the extent of the campaign was publicly known.
The initial fake Adobe Flash Player download from 1dnscontrol[.]com is immediately detected as a suspicious download:
If the early signs of BadRabbit go undetected, the infected devices start brute-forcing access to other devices on the network using SMB - causing thousands of SMB session login attempts per endeavored lateral movement over port 445. This highly anomalous behavior marks a sharp departure from customers’ normal ‘pattern of life’, making BadRabbit very easy to detect for Darktrace’s machine learning technology. Within seconds, Darktrace alerted the affected organizations about this attack flagging it as ‘SMB Session Brute Force’. The below shows an ongoing lateral movement attempt from an infected device to another client device using SMB session brute-force.
Infected devices make connection attempts to one or two seemingly randomly generated IP addresses on the internet over port 445 and also port 139. Examples of these failed connection attempts are displayed below. Darktrace instantly recognized this as unusual behavior for the infected device:
Compromised devices will attempt to move laterally on the network in a search for other devices to infect. Darktrace’s AI algorithms can swiftly recognize this anomalous behavior, alerting the affected organization in real time about these ‘Unusual Internal Connections’, as well as potential ‘Network Scans’.
The below model breaches seen in Darktrace are expected in a BadRabbit infection. Please be aware that not all models listed below are expected to breach in every infection - this depends on the actual behavior observed by Darktrace.
The Darktrace ‘Omnisearch’ and ‘Advanced Search’ features can be used to identify any connections made to the known network Indicators of Compromise:
1dnscontrol[.]com(hosting the fake Adobe Flash player file)185.149.120[.]3(static IP observed, victims HTTP POSTing to the IP)
Conclusion
BadRabbit is a machine-speed ransomware attack that exhibits some of the functionality and infection mechanics of the WannaCry and NotPetya breaches observed earlier this year. The BadRabbit malware masks itself as an ‘Adobe Flash’ software update, tempting unsuspecting users to initiate a download. After the initial impact, the attack can spread from machine to machine without human intervention.
Darktrace’s AI algorithms are quick to detect the highly anomalous patterns of behavior that BadRabbit triggers on a network, alerting the security team in real time. We have seen BadRabbit bypass traditional security controls around the globe, demonstrating once again the futility of attempting to identify and stop threats with rules and signatures. As Darktrace’s machine learning technology doesn’t rely on any assumptions of what ‘bad’ looks like and detects unfolding attacks not by what they are but by what they do, it is very powerful at catching and stopping ransomware attacks like BadRabbit in real time.
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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.
Author
Max Heinemeyer
Global Field CISO
Max is a cyber security expert with over a decade of experience in the field, specializing in a wide range of areas such as Penetration Testing, Red-Teaming, SIEM and SOC consulting and hunting Advanced Persistent Threat (APT) groups. At Darktrace, Max is closely involved with Darktrace’s strategic customers & prospects. He works with the R&D team at Darktrace, shaping research into new AI innovations and their various defensive and offensive applications. Max’s insights are regularly featured in international media outlets such as the BBC, Forbes and WIRED. Max holds an MSc from the University of Duisburg-Essen and a BSc from the Cooperative State University Stuttgart in International Business Information Systems.
Detecting and mitigating adversary-in-the-middle phishing attacks with Darktrace Services
What is an Adversary-in-the-Middle Attack?
Threat actors are increasingly utilizing advanced phishing toolkits and techniques to carry out Adversary-in-the-Middle (AitM) attacks. These attacks involve the use of a proxy to a legitimate service, where the attacker’s webpage mimics the expected site. While the victim believes they are visiting the legitimate site, they are actually interacting with the attacker’s device, allowing the malicious actor to monitor all interactions and control the authenticated session, ultimately gaining access to the user’s account [1][2].
In these types of AitM BEC attacks, recipients are often targeted with Dropbox-related emails, featuring subject headings like ‘FirstLast shared "Filename" with you,’ which suggest an individual is sharing an invoice-related attachment. These email subjects are common in such attacks, as threat actors attempt to encourage victims to access Dropbox links by masquerading them as legitimate files.
While higher priority users are, of course, targeted, the scope of these attacks remains broad. For instance, if a lower priority user is targeted by a phishing attack or their token is stolen, an attacker can still attempt BEC for further malicious intent and financial gain.
In October 2024, a Darktrace customer received a phishing email from a seemingly legitimate Dropbox address. This email originated from the IP, 54.240.39[.]219 and contained multiple link payloads to Dropbox-related hostnames were observed, inviting the user to access a file. Based on anomaly indicators and detection by Darktrace / EMAIL, Darktrace recognized that one of the payloads was attempting to abuse a legitimate cloud platform to share files or other unwanted material with the recipient.
Figure 1: Overview of the malicious email in the Darktrace / EMAIL console, highlighting Dropbox associated content/link payloads.
Following the recipient’s engagement with this email, Darktrace / IDENTITY identified a series of suspicious activities within the customer’s environment.
AitM attacks allow threat actors to bypass multi-factor authentication (MFA). Initially, when a user is phished, the malicious infrastructure captures both the user’s credentials and the token. This includes replaying a token issued to user that has already completed the MFA requirement, allowing the threat actor to satisfy the validity of the requirement and gain access to sensitive organizational resources. Darktrace is able to analyze user activity and authentication patterns to determine whether MFA requirements were met. This capability helps verify and indicate token theft via AitM.
Darktrace observed the associated user account making requests over Microsoft 365 from the IP 41.90.175[.]46. Given the unusual nature and rare geolocation based in Kenya, Africa, this activity did not appear indicative of legitimate business operations.
Figure 2: Geographical location of the SaaS user in relation to the source IP 41.90.175[.]46.
Further analysis using open-source intelligence (OSINT) revealed that the endpoint was likely associated with a call-back proxy network [3]. This suggested the presence of a network device capable of re-routing traffic and harvesting information.
Darktrace also detected that the same SaaS user was logging in from two different locations around the same time. One login was from a common, expected location, while the other was from an unusual location. Additionally, the user was observed registering security information using the Microsoft Authenticator app, indicating an attempt by an attacker to maintain access to the account by establishing a new method of MFA. This new MFA method could be used to bypass future MFA requirements, allowing the attacker to access sensitive material or carry out further malicious activities.
Figure 3: External sites summary for the SaaS account in relation to the source IP 13.74.161[.]104, observed with Registering Security Information.
Ultimately, this anomalous behavior was escalated to the Darktrace Security Operations Centre (SOC) via the Managed Detection & Response service for prompt triage and investigation by Darktrace’s SOC Analysts who notified the customer of strong evidence of compromise.
Fortunately, since this customer had Darktrace enabled in Autonomous Response mode, the compromised SaaS account had already been disabled, containing the attack. Darktrace’s SOC elected to extend this action to ensure the malicious activity remained halted until the customer could take further remedial action.
Figure 4: Attack timeline of observed activity, in chronological order; This highlighted anomalous SaaS events such as, MailItemsAccessed’, ‘Use of Unusual Credentials’, ‘User Registered Security Info’ events, and a ‘Disable User’ Autonomous Response action.
Conclusion
AitM attacks can play a crucial role in BEC campaigns. These attacks are often part of multi-staged operations, where an initial AitM attack is leveraged to launch a BEC by delivering a malicious URL through a trusted vendor or service. Attackers often attempt to lay low on their target network, sometimes persisting for extended periods, as they monitor user accounts or network segments to intercept sensitive communications.
In this instance, Darktrace successfully identified and acted against AitM techniques being leveraged in a BEC attack that used Dropbox for delivery. While Dropbox is widely used for legitimate purposes, its popularity has also made it a target for exploitation by threat actors, who have used it for a variety of malicious purposes, including delivering malware and revealing sensitive information.
Darktrace’s Security Operations Support service, combined with its Autonomous Response technology, provided timely and effective mitigation. Dedicated Security Operations Support analysts triaged the incident and implemented preventative measures, ensuring the customer was promptly notified. Meanwhile, Darktrace swiftly disabled the compromised SaaS account, allowing the customer to take further necessary actions, such as resetting the user’s password.
This case highlights the capabilities of Darktrace’s solutions, enabling the customer to resume normal business operations despite the malicious activity.
Credit to Justin Torres (Senior Cyber Analyst), Stefan Rowe (Technical Director, SOC) and Ryan Traill (Analyst Content Lead)
A Snake in the Net: Defending Against AiTM Phishing Threats and Mamba 2FA
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
