The Rise of the Lumma Info-Stealer | Malware-as-a-Service
06
Sep 2023
The emergence of Lumma Stealer, an information stealer that has recently been observed across the Darktrace fleet. Learn more about this new threat!
What are Malware-as-a-Service information stealers?
The Malware-as-a-Service (MaaS) model continues provide would-be threat actors with an inexpensive and relatively straightforward way to carry out sophisticated cyber attacks and achieve their nefarious goals. One common type of MaaS are information stealers that specialize in gathering and exfiltrating sensitive data, such as login credentials and bank details, from affected devices, potentially resulting in significant financial losses for organizations and individuals alike.
What is Lumma Information Stealer?
One such information stealer, dubbed “Lumma”, has been advertised and sold on numerous dark web forums since 2022. Lumma stealer primarily targets cryptocurrency wallets, browser extensions and two-factor authentication (2FA), before ultimately stealing sensitive information from compromised machines. The number of sightings of this malware being distributed on dark web forums is on the rise [1], and thus far, more than a dozen command-and-control (C2) servers have been observed in the wild.
Between January and April 2023, Darktrace observed and investigated multiple instances of Lumma stealer activity across the customer base. Thanks to its anomaly-based approach to threat detection, Darktrace is able to successfully identify and provide visibility over activity associated with such info-stealers, from C2 activity through to the eventual exfiltration of sensitive data.
Lumma Stealer Background
Lumma stealer, previously known as LummaC2, is a subscription-based information stealer that has been observed in the wild since 2022. It is believed to have been developed by the threat actor “Shamel”, under the the alias “Lumma”. The info-stealer has been advertised on dark web forums and also a channel on the Telegram messenger server, which boasts over a thousand subscribers as of May 2023 [2], and is also available on Lumma’s official seller page for as little as USD 250 (Figure 1).
Figure 1: LummaC2’s official seller website [3].
Research on the Russian Market selling stolen credentials has shown that Lumma stealer has been an emerging since early 2023, and joins the list of info stealers that have been on the rise, including Vidar and Racoon [1].
Similar to other info-stealers, Lumma is able to obtain system and installed program data from compromised devices, alongside sensitive information such as cookies, usernames and passwords, credit card numbers, connection history, and cryptocurrency wallet data.
Between January and April 2023, Darktrace has observed Lumma malware activity across multiple customer deployments mostly in the EMEA region, but also in the US. This included data exfiltration to external endpoints related to the Lumma malware. It is likely that this activity resulted from the download of trojanized software files or users falling victim to malicious emails containing Lumma payloads.
Lumma Attack Details and Darktrace Coverage
Typically, Lumma has been distributed disguised as cracked or fake popular software like VLC or ChatGPT. Recently though, threat actors have also delivered the malware through emails containing payloads in the form of attachments or links impersonating well-known companies. For example, in February 2023, a streamer in South Korea was targeted with a spear-phishing email in which the sender impersonated the video game company Bandai Namco [4].
Lumma is known to target Windows operating systems from Windows 7 to 11 and at least 10 different browsers including Google Chrome, Microsoft Edge, and Mozilla Firefox [5]. It has also been observed targeting crypto wallets like Binance and Ethereum, as well as crypto wallet and 2FA browser extensions like Metamask and Authenticator respectively [6]. Data from applications such as AnyDesk or KeePass can also be exfiltrated by the malware [7].
An infection with Lumma can lead to the user's information being abused for fraud, for example, using stolen credentials to hijack bank accounts, which in turn could result in significant financial losses.
Once the targeted data is obtained, it is exfiltrated to a C2 server, as Darktrace has observed on multiple customer environments affected with Lumma stealer. Darktrace identified multiple infected devices exfiltrating data via HTTP POST requests to known Lumma C2 servers. During these connections, DETECT commonly observed the URI “/c2sock” and the user agent “TeslaBrowser/5.5”.
In one instance, Darktrace detected a device using the “TeslaBrowser/5.5” user agent, which it recognized as a new user agent for this device, whilst making a HTTP post request to an unusual IP address, 82.117.255[.]127 (Figure 3). Darktrace’s Self-Learning AI understood that this represented a deviation from expected behavior for this device and brought it to the attention of the customer’s security team.
Figure 2: Device Event Log on the Darktrace DETECT Threat Visualizer showing activity from a device infected with Lumma stealer and the DETECT models it breached.
Further investigation revealed that accessing the IP address using a web browser and changing the the URI to “/login”, would take a user to a Russian Lumma control panel access page (Figure 4)
Figure 3: One of Lumma stealer’s C2 servers accessed via a web browser in a secured environment.
A deep dive into the packet captures (PCAP) of the HTTP POST requests taken from one device also confirmed that browser data, including Google Chrome history files, system information in the form of a System.txt file, and other program data such as AnyDesk configuration files were being exfiltrated from the customer’s network(Figures 5 and 6).
Figure 4: HTTP objects observed during Lumma Stealer POSTing of data to another one of its C2 servers.
Figure 5: PCAP of HTTP stream showing the different types of data being exfiltrated.
Additionally, on one particular device, Darktrace observed malicious external connections related to other malware strains, like Laplas Clipper, Raccoon Stealer, Vidar, RedLine info-stealers and trojans, around the same time as the Lumma C2 connections. These info-stealers are commonly marketed as MaaS and can be bought and used for a relatively inexpensive price by even the most inexperienced threat actors. It is also likely that the developers of these info-stealers have been making efforts to integrate their strains into the activities of traffer teams [8], organized cybercrime groups who specialize in credential theft with the use of info-stealers.
Conclusion
Mirroring the general emergence and rise of information stealers across the cyber threat landscape, Lumma stealer continues to represent a significant concern to orgaizations and individuals alike.
Moreover, as yet another example of MaaS, Lumma is readily available for threat actors to launch their attacks, regardless of their level of expertise, meaning the number of incidents is only likely to rise. As such, it is essential for organizations to have security measures in place that are able to recognize unusual behavior that may be indicactive of an info-stealer compromise, while not relying on a static list of indicators of compromise (IoCs).
Darktrace's anomaly-based detection enabled it to uncover the presence of Lumma across multiple customer environments across different regions and industries. From the detection of unusual connections to C2 infrastructure to the ultimate exfiltration of customer data, Darktrace provided affected customers full visibility over Lumma infections, allowing them to identify compromised devices and take action to prevent further data loss and reduce the risk of incurring significant financial losses.
Oops! Something went wrong while submitting the form.
Newsletter
Stay ahead of threats with the Darktrace blog newsletter
Get the latest insights from the cybersecurity landscape, including threat trends, incident analysis, and the latest Darktrace product developments – delivered directly to your inbox, monthly.
Thanks, your request has been received
A member of our team will be in touch with you shortly.
Oops! Something went wrong while submitting the form.
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.
Darktrace’s view on Operation Lunar Peek: Exploitation of Palo Alto firewall devices (CVE 2024-2012 and 2024-9474)
Introduction: Spike in exploitation and post-exploitation activity affecting Palo Alto firewall devices
As the first line of defense for many organizations, perimeter devices such as firewalls are frequently targeted by threat actors. If compromised, these devices can serve as the initial point of entry to the network, providing access to vulnerable internal resources. This pattern of malicious behavior has become readily apparent within the Darktrace customer base. In 2024, Darktrace Threat Research analysts identified and investigated at least two major campaigns targeting internet-exposed perimeter devices. These included the exploitation of PAN-OS firewall exploitation via CVE 2024-3400 and FortiManager appliances via CVE 2024-47575.
More recently, at the end of November, Darktrace analysts observed a spike in exploitation and post-exploitation activity affecting, once again, Palo Alto firewall devices in the days following the disclosure of the CVE 2024-0012 and CVE-2024-9474 vulnerabilities.
Threat Research analysts had already been investigating potential exploitation of the firewalls’ management interface after Palo Alto published a security advisory (PAN-SA-2024-0015) on November 8. Subsequent analysis of data from Darktrace’s Security Operations Center (SOC) and external research uncovered multiple cases of Palo Alto firewalls being targeted via the likely exploitation of these vulnerabilities since November 13, through the end of the month. Although this spike in anomalous behavior may not be attributable to a single malicious actor, Darktrace Threat Research identified a clear increase in PAN-OS exploitation across the customer base by threat actors likely utilizing the recently disclosed vulnerabilities, resulting in broad patterns of post-exploitation activity.
How did exploitation occur?
CVE 2024-0012 is an authentication bypass vulnerability affecting unpatched versions of Palo Alto Networks Next-Generation Firewalls. The vulnerability resides in the management interface application on the firewalls specifically, which is written in PHP. When attempting to access highly privileged scripts, users are typically redirected to a login page. However, this can be bypassed by supplying an HTTP request where a Palo Alto related authentication header can be set to “off”. Users can supply this header value to the Nginx reverse proxy server fronting the application which will then send it without any prior processing [1].
CVE-2024-9474 is a privilege escalation vulnerability that allows a PAN-OS administrator with access to the management web interface to execute root-level commands, granting full control over the affected device [2]. When combined, these vulnerabilities enable unauthenticated adversaries to execute arbitrary commands on the firewall with root privileges.
Post-Exploitation Patterns of Activity
Darktrace Threat Research analysts examined potential indicators of PAN-OS software exploitation via CVE 2024-0012 and CVE-2024-9474 during November 2024. The investigation identified three main groupings of post-exploitation activity:
Exploit validation and initial payload retrieval
Command and control (C2) connectivity, potentially featuring further binary downloads
Potential reconnaissance and cryptomining activity
Exploit Validation
Across multiple investigated customers, Darktrace analysts identified likely vulnerable PAN-OS devices conducting external network connectivity to bin services. Specifically, several hosts performed DNS queries for, and HTTP requests to Out-of-Band Application Security Testing (OAST) domains, such as csv2im6eq58ujueonqs0iyq7dqpak311i.oast[.]pro. These endpoints are commonly used by network administrators to harden defenses, but they are increasingly used by threat actors to verify successful exploitation of targeted devices and assess their potential for further compromise. Although connectivity involving OAST domains were prevalent across investigated incidents, this activity was not necessarily the first indicator observed. In some cases, device behavior involving OAST domains also occurred shortly after an initial payload was downloaded.
Figure 1: Darktrace model alert logs detailing the HTTP request to an OAST domain immediately following PAN-OS device compromise.
Initial Payload Retrieval
Following successful exploitation, affected devices commonly performed behaviors indicative of initial payload download, likely in response to incoming remote command execution. Typically, the affected PAN-OS host would utilize the command line utilities curl and Wget, seen via use of user agents curl/7.61.1 and Wget/1.19.5 (linux-gnu), respectively.
In some cases, the use of these command line utilities by the infected devices was considered new behavior. Given the nature of the user agents, interaction with the host shell suggests remote command execution to achieve the outgoing payload requests.
While additional binaries and scripts were retrieved in later stages of the post-exploitation activity in some cases, this set of behaviors and payloads likely represent initial persistence and execution mechanisms that will enable additional functionality later in the kill chain. During the investigation, Darktrace analysts noted the prevalence of shell script payload requests. Devices analyzed would frequently make HTTP requests over the usual destination port 80 using the command line URL utility (curl), as seen in the user-agent field.
The observed URIs often featured requests for text files, such as “1.txt”, or shell scripts such as “y.sh”. Although packet capture (PCAP) samples were unavailable for review, external researchers have noted that the IP address hosting such “1.txt” files (46.8.226[.]75) serves malicious PHP payloads. When examining the contents of the “y.sh” shell script, Darktrace analysts noticed the execution of bash commands to upload a PHP-written web shell on the affected server.
Figure 2: PCAP showing the client request and server response associated with the download of the y.sh script from 45.76.141[.]166. The body content of the HTTP response highlights a shebang command to run subsequent code as bash script. The content is base64 encoded and details PHP script for what appears to be a webshell that will likely be written to the firewall device.
While not all investigated cases saw initial shell script retrieval, affected systems would commonly make an external HTTP connection, almost always via Wget, for the Executable and Linkable Format (ELF) file “/palofd” from the rare external IP 38.180.147[.]18.
Such requests were frequently made without prior hostname lookups, suggesting that the process or script initiating the requests already contained the external IP address. Analysts noticed a consistent SHA1 hash present for all identified instances of “/palofd” downloads (90f6890fa94b25fbf4d5c49f1ea354a023e06510). Multiple open-source intelligence (OSINT) vendors have associated this hash sample with Spectre RAT, a remote access trojan with capabilities including remote command execution, payload delivery, process manipulation, file transfers, and data theft [3][4].
Figure 3: Advanced Search log metrics highlighting details of the “/palofd” file download over HTTP.
Several targeted customer devices were observed initiating TLS/SSL connections to rare external IPs with self-signed TLS certificates following exploitation. Model data from across the Darktrace fleet indicated some overlap in JA3 fingerprints utilized by affected PAN-OS devices engaging in the suspicious TLS activity. Although JA3 hashes alone cannot be used for process attribution, this evidence suggests some correlation of source process across instances of PAN-OS exploitation.
These TLS/SSL sessions were typically established without the specification of a Server Name Indication (SNI) within the TLS extensions. The SNI extension prevents servers from supplying an incorrect certificate to the requesting client when multiple sites are hosted on the same IP. SSL connectivity without SNI specification suggests a potentially malicious running process as most software establishing TLS sessions typically supply this information during the handshake. Although the encrypted nature of the connection prevented further analysis of the payload packets, external sources note that JavaScript content is transmitted during these sessions, serving as initial payloads for the Sliver C2 platform using Wget [5].
C2 Communication and Additional Payloads
Following validation and preliminary post-compromise actions, examined hosts would commonly initiate varying forms of C2 connectivity. During this time, devices were frequently detected making further payload downloads, likely in response to directives set within C2 communications.
Palo Alto firewalls likely exploited via the newly disclosed CVEs would commonly utilize the Sliver C2 platform for external communication. Sliver’s functionality allows for different styles and formatting for communication. An open-source alternative to Cobalt Strike, this framework has been increasingly popular among threat actors, enabling the generation of dynamic payloads (“slivers”) for multiple platforms, including Windows, MacOS, Linux.
These payloads allow operators to establish persistence, spawn new shells, and exfiltrate data. URI patterns and PCAPs analysis yielded evidence of both English word type encoding within Sliverand Gzip formatting.
For example, multiple devices contacted the Sliver-linked IP address 77.221.158[.]154 using HTTP to retrieve Gzip files. The URIs present for these requests follow known Sliver Gzip formatted communication patterns [6]. Investigations yielded evidence of both English word encoding within Sliver, identified through PCAP analysis, and Gzip formatting.
Figure 4: Sample of URIs observed in Advanced Searchhighlighting HTTP requests to 77.221.158[.]154 for Gzip content suggest of Sliver communication.
Figure 5: PCAP showing English word encoding for Sliver communication observed during post-exploitation C2 activity.
External connectivity during this phase also featured TCP connection attempts over uncommon ports for common application protocols. For both Sliver and non-Sliver related IP addresses, devices utilized destination ports such as 8089, 3939, 8880, 8084, and 9999 for the HTTP protocol. The use of uncommon destination ports may represent attempts to avoid detection of connectivity to rare external endpoints. Moreover, some external beaconing within included URIs referencing the likely IP of the affected device. Such behavior can suggest the registration of compromised devices with command servers.
Targeted devices also proceeded to download additional payloads from rare external endpoints as beaconing/C2 activity was ongoing. For example, the newly registered domain repositorylinux[.]org (IP: 103.217.145[.]112) received numerous HTTP GET requests from investigated devices throughout the investigation period for script files including “linux.sh” and “cron.sh”. Young domains, especially those that present as similar to known code repositories, tend to host harmful content. Packet captures of the cron.sh file reveal commands within the HTTP body content involving crontab operations, likely to schedule future downloads. Some hosts that engaged in connectivity to the fake repository domain were later seen conducting crypto-mining connections, potentially highlighting the download of miner applications from the domain.
Additional payloads observed during this time largely featured variations of shell scripts, PHP content, and/or executables. Typically, shell scripts direct the device to retrieve additional content from external servers or repositories or contain potential configuration details for subsequent binaries to run on the device. For example, the “service.sh” retrieves a tar-compressed archive, a configuration JSON file as well as a file with the name “solr” from GitHub, potentially associated with the Apache Solr tool used for enterprise search. These could be used for further enumeration of the host and/or the network environment. PHP scripts observed may involve similar web shell functionality and were retrieved from both rare external IPs identified as well by external researchers [7]. Darktrace also detected the download of octet-stream data occurring mid-compromise from an Amazon Web Services (AWS) S3 bucket. Although no outside research confirmed the functionality, additional executable downloads for files such as “/initd”(IP: 178.215.224[.]246) and “/x6” (IP: 223.165.4[.]175) may relate to tool ingress, further Trojan/backdoor functionality, or cryptocurrency mining.
Figure 7: PCAP specifying the HTTP response headers and body content for the service.sh file request. The body content shown includes variable declarations for URLs that will eventually be called by the device shell via bash command.
Reconnaissance and Cryptomining
Darktrace analysts also noticed additional elements of kill chain operations from affected devices after periods of initial exploit activity. Several devices initiated TCP connections to endpoints affiliated with cryptomining pools such as us[.]zephyr[.]herominers[.]com and xmrig[.]com. Connectivity to these domains indicates likely successful installation of mining software during earlier stages of post-compromise activity. In a small number of instances, Darktrace observed reconnaissance and lateral movement within the time range of PAN-OS exploitation. Firewalls conducted large numbers of internal connectivity attempts across several critical ports related to privileged protocols, including SMB and SSH. Darktrace detected anonymous NTLM login attempts and new usage of potential PAN-related credentials. These behaviors likely constitute attempts at lateral movement to adjacent devices to further extend network compromise impact.
Figure 8: Model alert connection logs detailing the uncommon failed NTLM logins using an anonymous user account following PAN-OS exploitation.
Conclusion
Darktrace Threat Research and SOC analysts increasingly detect spikes in malicious activity on internet-facing devices in the days following the publication of new vulnerabilities. The latest iteration of this trend highlighted how threat actors quickly exploited Palo Alto firewall using authentication bypass and remote command execution vulnerabilities to enable device compromise. A review of the post-exploitation activity during these events reveals consistent patterns of perimeter device exploitation, but also some distinct variations.
Prior campaigns targeting perimeter devices featured activity largely confined to the exfiltration of configuration data and some initial payload retrieval. Within the current campaign, analysts identified a broader scope post-compromise activity consisting not only of payloads downloads but also extensive C2 activity, reconnaissance, and coin mining operations. While the use of command line tools like curl featured prominently in prior investigations, devices were seen retrieving a generally wider array of payloads during the latest round of activity. The use of the Sliver C2 platform further differentiates the latest round of PAN-OS compromises, with evidence of Sliver activity in about half of the investigated cases.
Several of the endpoints contacted by the infected firewall devices did not have any OSINT associated with them at the time of the attack. However, these indicators were noted as unusual for the devices according to Darktrace based on normal network traffic patterns. This reality further highlights the need for anomaly-based detection that does not rely necessarily on known indicators of compromise (IoCs) associated with CVE exploitation for detection. Darktrace’s experience in 2024 of multiple rounds of perimeter device exploitation may foreshadow future increases in these types of comprise operations.
Credit to Adam Potter (Senior Cyber Analyst), Alexandra Sentenac (Senior Cyber Analyst), Emma Foulger (Principal Cyber Analyst) and the Darktrace Threat Research team.
Cloud Security: Addressing Common CISO Challenges with Advanced Solutions
Cloud adoption is a cornerstone of modern business with its unmatched potential for scalability, cost efficiency, flexibility, and net-zero targets around sustainability. However, as organizations migrate more workloads, applications, and sensitive data to the cloud it introduces more complex challenges for CISO’s. Let’s dive into the most pressing issues keeping them up at night—and how Darktrace / CLOUD provides a solution for each.
1. Misconfigurations: The Silent Saboteur
Misconfigurations remain the leading cause of cloud-based data breaches. In 2023 alone over 80% of data breaches involved data stored in the cloud.1 Think open storage buckets or overly permissive permissions; seemingly minor errors that are easily missed and can snowball into major disasters. The fallout of breaches can be costly—both financially and reputationally.
How Darktrace / CLOUD Helps:
Darktrace / CLOUD continuously monitors your cloud asset configurations, learning your environment and using these insights to flag potential misconfigurations. New scans are triggered when changes take place, then grouped and prioritised intelligently, giving you an evolving and prioritised view of vulnerabilities, best practice and mitigation strategies.
2. Hybrid Environments: The Migration Maze
Many organizations are migrating to the cloud, but hybrid setups (where workloads span both on-premises and cloud environments) create unique challenges and visibility gaps which significantly increase complexity. More traditional and most cloud native security tooling struggles to provide adequate monitoring for these setups.
How Darktrace / CLOUD Helps:
Provides the ability to monitor runtime activity for both on-premises and cloud workloads within the same user interface. By leveraging the right AI solution across this diverse data set, we understand the behaviour of your on-premises workloads and how they interact with cloud systems, spotting unusual connectivity or data flow activity during and after the migration process.
This unified visibility enables proactive detection of anomalies, ensures seamless monitoring across hybrid environments, and provides actionable insights to mitigate risks during and after the migration process.
3. Securing Productivity Suites: The Last Mile
Cloud productivity suites like Microsoft 365 (M365) are essential for modern businesses and are often the first step for an organization on a journey to Infrastructure as a Service (IaaS) or Platform as a Service (PaaS) use cases. They also represent a prime target for attackers. Consider a scenario where an attacker gains access to an M365 account, and proceeds to; access sensitive emails, downloading files from SharePoint, and impersonating the user to send phishing emails to internal employees and external partners. Without a system to detect these behaviours, the attack may go unnoticed until significant damage is done.
How Darktrace helps:
Darktrace’s Active AI platform integrates with M365 and establishes an understanding of normal business activity, enabling the detection of abnormalities across its suite including Email, SharePoint and Teams. By identifying subtle deviations in behaviour, such as:
• Unusual file accesses
• Anomalous login attempts from unexpected locations or devices.
• Suspicious email forwarding rules created by compromised accounts.
Darktrace’s Autonomous Response can act precisely to block malicious actions, by disabling compromised accounts and containing threats before they escalate. Precise actions also ensure that critical business operations are maintained even when a response is triggered.
4. Agent Fatigue: The Visibility Struggle
To secure cloud environments, visibility is critical. If you don’t know what’s there, how can you secure it? Many solutions require agents to be deployed on every server, workload, and endpoint. But managing and deploying agents across sprawling hybrid environments can be both complex and time-consuming when following change controls, and especially as cloud resources scale dynamically.
How Darktrace / CLOUD Helps:
Darktrace reduces or eliminates the need for widespread agent deployment. Its agentless by default, integrating directly with cloud environments and providing instant visibility without the operational headache. Darktrace ensures coverage with minimal friction. By intelligently graphing the relationships between assets and logically grouping your deployed Cloud resources, you are equipped with real-time visibility to quickly understand and protect your environment.
So why Darktrace / CLOUD?
Darktrace’s Self-Learning AI redefines cloud security by adapting to your unique environment, detecting threats as they emerge, and responding in real-time. From spotting misconfigurations to protecting productivity suites and securing hybrid environments. Darktrace / CLOUD simplifies cloud security challenges without adding operational burdens.
From Chaos to Clarity
Cloud security doesn’t have to be a game of endless whack-a-mole. With Darktrace / CLOUD, CISOs can achieve the visibility, control, and proactive protection they need to navigate today’s complex cloud ecosystems confidently.
![PCAP showing the client request and server response associated with the download of the y.sh script from 45.76.141[.]166. The body content of the HTTP response highlights a shebang command to run subsequent code as bash script. The content is base64 encoded and details PHP script for what appears to be a webshell that will likely be written to the firewall device.](https://cdn.prod.website-files.com/626ff4d25aca2edf4325ff97/675700c4a98f6ccec0f1a975_6756f988e443cb72200722b4_Screenshot%25202024-12-09%2520at%252014.06.53.png)
![Sample of URIs observed in Advanced Searchhighlighting HTTP requests to 77.221.158[.]154 for Gzip content suggest of Sliver communication.](https://cdn.prod.website-files.com/626ff4d25aca2edf4325ff97/6757623084734b0dbf6418e4_675761ed5dcf48e9b0b0befb_Screenshot%25202024-12-09%2520at%25201.31.31%25E2%2580%25AFPM.png)
