The underground marketplace rarely stays quiet for long. A new information-stealing malware dubbed Remus Stealer has surfaced in the cybercrime underground, exhibiting significant similarities to the notorious Lumma malware family across its administration panel, stolen log files, and core code structure.
Despite parallels in its code and functionality, threat actors are eagerly buying into the platform. In addition to its familiar features, it provides attackers with a distinct, modern command and control (C2) and networking infrastructure designed to slip past current security perimeters.
What We Know About Remus
Flashpoint first observed Remus appearing for sale within illicit communities in March 2026. The malware listing offers similar functionality to other popular Malware-as-a-Service (MaaS) offerings, including Google OAuth cookie restoration and Telegram channel integration for logs.
Much like the Lumma malware family, the Remus subscription service operates on a three-tiered access model:
Basic: US$250
Pro: US$500
Enterprise: US$1,000
At this time, Remus has no additional channels or automated bots associated with its sale or distribution. Despite undeniable similarities to Lumma, its developer claims to not be a rebrand of the Lumma project.
Since March 2026, Remus has continued its operations mostly unhindered by negative associations associated with Lumma—particularly the doxxing of its panel in August 2025.
Similarities to Lumma
Similarities can be observed in the Remus and Lumma panels in both aesthetics and functionality. Both panels use similar assets for tab icons and have embedded advertisements for other illicit services such as packers and log clouds. Harvested logs also share extremely similar directory structures in log files, including unique identifiers.
Remus is a 64-bit compiled binary, and Lumma was a 32-bit binary. However, major similarities between the code bases of both malware can be observed.
Upon execution of an unpacked sample, both Remus and Lumma will send warning messages to the user that the build is unpacked. This was a unique phenomenon first established by Lumma several years ago. In both Remus and Lumma samples, the pack check and window message are performed before the main functionality of the malware.
In both Remus and Lumma, a function is used first to check if the sample is packed, and a second function is used to send the window error message.
Remus uses similar string obfuscation methods to Lumma, in which each string has been uniquely encoded and then decoded during runtime. Deobfuscation occurs by looping byte by byte through encoded blobs. Each encoded string is obfuscated by a unique pattern. This can be seen in the code samples below:
Of note, both samples have at least one NOP instruction between the encoded blob being moved onto the stack and the deobfuscation loop.
Another unique feature of Lumma is the presence of a plaintext identifier string used to link customers to specific build generations. In Lumma, this string was referred to as the LID (Lumma ID), and this ID method appears in Remus as well as a “tag.”
Lumma ID (Source: Flashpoint)Remus tag (Source: Flashpoint)
Like the Lumma LID string, the Remus tag could be leveraged to attribute variant builds and campaigns to single threat actors or groups.
Additionally, both Remus and Lumma exhibit similar control flow obfuscation by replacing direct jumps with indirect jumps read from offsets that have been moved onto the stack, jumps computed from a jump table, and jumps resolved by a pointer.
Differentiators of Remus
Although Remus bears remarkable similarities to Lumma, its main differences lie in its C2 beaconing.
Before performing main stealer functionality, Remus will beacon out to its C2 infrastructure. It will attempt to resolve several domain:port combinations via POST requests, and attempt a final connection to find the C2 server using EtherHiding. If it is unable to connect, the malware will terminate.
After a connection is established, the stealer sends a POST request to the C2 in order to receive an access token. Once received and decoded, this access token is used to receive encrypted config data used by Remus to target assets on the victim system. Data collected for logs is then exfiltrated as encrypted POST data.
Network traffic from Remus sample (Source: Flashpoint)
Protect Against Infostealers Using Flashpoint
Remus stealer represents a sophisticated continuation of the MaaS infostealer model left behind by Lumma’s collapse. While the developer asserts independence, the overwhelming code overlaps, matching obfuscation techniques, and administrative panels indicate that Remus is either heavily inspired by, or derived from the Lumma codebase. These traits have allowed it to thrive, providing threat actors with a familiar, robust alternative that sidesteps the reputational baggage and law enforcement scrutiny of its predecessors.
Flashpoint continuously tracks the latest developments in illicit communities, hard-to-reach adversary spaces, and malware repositories to identify emerging threats. Request a demo to learn how Flashpoint’s primary source collections and analyst insights empowers your security teams.
Unit 42's analysis of ClawHub revealed evasive malicious skills bypassing automated scanners to deploy infostealers and execute agentic financial fraud.
Identity Is the New Attack Surface: How Infostealers Are Reshaping Enterprise Risk
Our new guide explores how infostealers are fueling modern identity-based attacks and how organizations can build a proactive defense before stolen access is weaponized.
A publicly exposed database surfaced in early 2026 containing more than 149 million stolen login credentials. The records were not tied to a single breach or organization. Instead, they had been quietly collected over time from devices infected with information-stealing malware, with each record containing usernames, passwords, session data, and the context needed to use them.
Unlike traditional breach dumps, this data was structured, searchable, and immediately actionable. Credentials were mapped to specific services, session artifacts reflected active logins, and much of the information was recent enough to enable direct access without triggering traditional security controls.
This incident reflects a broader shift in the threat landscape.
More than 11.1 million devices were infected with infostealers last year, fueling a supply of over 3.3 billion stolen credentials, session cookies, cloud tokens, and other forms of identity data now circulating across illicit markets.
For security teams, the challenge is no longer simply detecting a breach after it occurs. It is understanding when access may already exist — where compromised credentials are circulating, how they are being used, and how quickly they can be weaponized.
Drawing on Flashpoint’s Primary Source Collection (PSC) and analyst-driven intelligence, this guide helps IT, Threat Intelligence, Fraud, and HUNT teams understand how infostealers operate, how stolen identity data fuels real-world attacks, and how organizations can move from reactive response to proactive defense.
The guide explores:
How today’s most active infostealers power modern attack chains
How threat actors weaponize stolen credentials, cookies, and session data
How organizations can operationalize infostealer intelligence for proactive defense
How to evaluate infostealer intelligence providers and detection capabilities
Why Identity Has Become the Preferred Attack Surface
For years, security teams focused on vulnerabilities, malware delivery, and network intrusion as the primary paths to compromise. Increasingly, however, threat actors are taking a different
Modern infostealers such as Lumma, StealC, Vidar, Acreed, and Rhadamanthys provide attackers with something more valuable than initial access: usable identity. These malware families collect credentials, browser artifacts, session cookies, application data, and host metadata that help threat actors understand how a victim authenticates and what systems they can access.
A single infected device can expose credentials, browser artifacts, session cookies, application data, host metadata, and access to enterprise SaaS platforms. Together, these artifacts create a detailed profile of how a user authenticates, what systems they access, and how those systems trust that identity.
This is what makes infostealer data so valuable.
“For years, organizations have invested heavily in detecting malware, blocking exploits, and hardening infrastructure. Meanwhile, attackers have increasingly shifted to a simpler strategy: logging in with valid identities.
Infostealers have fundamentally changed the economics of access. Threat actors no longer need to compromise a network directly when billions of credentials, session cookies, and authentication artifacts are already circulating in underground ecosystems. The challenge for defenders has risen from preventing compromise to identifying where access already exists and how quickly it can be weaponized.”
Ian Gray, Vice President of Intelligence at Flashpoint
Identity data is inherently reusable. A stolen credential can be tested across multiple services. A session cookie can potentially allow attackers to hijack authenticated sessions. Browser and host metadata can help threat actors recreate a victim’s environment and bypass security controls designed to detect suspicious logins.
What begins as a single infection can quickly evolve into access across multiple systems, applications, and organizations.
What Is an Identity-Based Attack?
Identity-based attacks occur when threat actors use legitimate credentials, session cookies, authentication tokens, or other identity artifacts to gain access to systems and applications. Rather than exploiting a vulnerability or deploying malware inside a target environment, attackers authenticate as trusted users using stolen identity data.
This shift is one of the primary reasons infostealers have become so valuable. Modern infostealer logs often contain far more than usernames and passwords. They may also include browser cookies, session information, host metadata, application data, and other artifacts that help attackers understand how a user authenticates and what systems they can access. When combined, this information enables account takeover, fraud, lateral movement, and other forms of identity-based abuse.
From Credential Theft to Identity Exploitation
The way threat actors operationalize stolen data is evolving just as rapidly as the data itself.
Historically, attackers often had to manually review stolen credentials and determine which accounts were worth pursuing. Today, that process is increasingly automated.
Infostealer logs can be aggregated, tested, and prioritized at scale, allowing threat actors to rapidly identify valid access across enterprise systems, SaaS platforms, VPNs, and cloud environments.
Flashpoint identifies this as a hybrid threat: the convergence of large-scale identity compromise and automated exploitation.
Once valid access is identified, attackers can move quickly. Credentials may be reused across services. Session data can be leveraged for account takeover. Access can be sold to ransomware operators, fraud actors, or other criminal groups. In many cases, exposure itself becomes part of the attack lifecycle rather than merely a precursor to it.
The result is a threat landscape where stolen identity data is not simply stored and sold. It is continuously tested, validated, reused, and operationalized.
Turning Exposure Into Actionable Intelligence
For defenders, prevention remains important. But prevention alone is no longer enough.
Organizations must also be able to identify when credentials, session cookies, and other identity artifacts have already been exposed and are circulating within underground ecosystems.
The earliest opportunity to intervene is often after data has been exfiltrated but before attackers have successfully operationalized it.
Achieving that visibility requires more than traditional breach feeds or aggregated datasets.
Flashpoint’s Primary Source Collection approach provides direct visibility into the forums, marketplaces, Telegram channels, malware repositories, and illicit communities where infostealer activity originates. Rather than relying solely on recycled breach data, Flashpoint continuously collects from the environments where stolen identity data is first shared, sold, and operationalized.
However, collection alone is not enough.
Raw infostealer logs are noisy, fragmented, and difficult to operationalize at scale. Flashpoint transforms these logs into structured intelligence through a multi-stage workflow that includes:
Source ingestion from underground ecosystems
Normalization and de-duplication of collected data
Automated parsing and enrichment of credentials, cookies, host metadata, and malware attribution
Structured output that supports alerts, investigations, and integrations across existing security workflows
This process helps defenders understand not only what was exposed, but who may be affected, how exposure occurred, what systems may be at risk, and how quickly action is required.
Building a Proactive Defense Across the Identity Layer
The rise of infostealers has fundamentally changed how organizations should think about attack surface management.
The attack surface is no longer limited to infrastructure, endpoints, or internet-facing applications. It now includes the digital identities of employees, partners, vendors, and customers.
Security teams need visibility into the identity layer itself — understanding where exposure exists, how attackers are leveraging stolen data, and what actions should be taken before access is exploited.
By combining direct visibility into underground ecosystems with structured, actionable intelligence, organizations can identify compromised accounts earlier, uncover infection trends, prioritize response efforts, and reduce the likelihood of downstream compromise.
More than 11.1 million devices were infected with infostealers in the last year.
Over 3.3 billion credentials, session cookies, cloud tokens, and identity artifacts are circulating across illicit markets.
Flashpoint analysts identified 30+ active infostealer strains being sold across underground ecosystems.
Flashpoint’s credential database contains 48+ billion credentials, including more than 1 billion tied to infostealer activity.
More than 4.2% of infostealer-exposed credentials include browser cookies that may support session hijacking.
Flashpoint can collect and parse some infostealer logs within one to two days of infection.
Frequently Asked Questions (FAQ)
FAQ: Infostealers and Identity-Based Threats
What is an infostealer?
An infostealer is a type of malware designed to collect sensitive information from an infected device. Depending on the strain, this can include usernames and passwords, browser cookies, session tokens, saved payment information, cryptocurrency wallets, system metadata, and other identity-related artifacts.
How do infostealers work?
Infostealers infect a victim’s device and collect information such as credentials, browser data, session cookies, autofill information, cryptocurrency wallet data, and system metadata. The stolen information is packaged into files known as infostealer logs, which can then be sold, shared, or operationalized by threat actors.
What information can infostealers steal?
Depending on the malware family, infostealers can collect usernames and passwords, session cookies, authentication tokens, browser history, saved payment information, cryptocurrency wallet data, system information, installed applications, and other identity-related artifacts. The goal is to provide attackers with enough information to access accounts and impersonate legitimate users.
What are the most common infostealers?
The infostealer ecosystem changes rapidly, but Flashpoint analysts currently track strains such as Lumma (also known as LummaC2/Remus), StealC, Vidar, Acreed, and Rhadamanthys among the most prominent malware families driving credential theft and identity-based attacks.
Why are infostealers so dangerous?
Infostealers provide attackers with more than credentials. Modern infostealer logs often contain the context needed to use stolen data, including session information, browser artifacts, and device metadata. This allows threat actors to perform account takeovers, move laterally within environments, and gain access to business-critical systems. According to Flashpoint’s 2026 Global Threat Intelligence Report, more than 11.1 million devices were infected with infostealers last year, contributing to a pool of over 3.3 billion stolen credentials, session cookies, cloud tokens, and other identity artifacts.
What is an infostealer log?
An infostealer log is a package of data collected from an infected device. Logs may contain credentials, cookies, browser data, application information, host metadata, and other artifacts that help attackers understand how a victim authenticates and what systems they can access.
Can infostealers bypass multi-factor authentication (MFA)?
In some cases, yes. While multifactor authentication remains a critical security control, stolen session cookies and authenticated session data can sometimes allow threat actors to hijack existing sessions without needing to complete the MFA process themselves. Flashpoint found that more than 4.2% of infostealer-exposed credentials in its dataset were associated with browser cookies, highlighting the growing importance of session-based risk.
How do threat actors obtain infostealer logs?
Infostealer logs are frequently bought and sold across illicit marketplaces, forums, Telegram channels, and other underground communities. Many are distributed through Malware-as-a-Service (MaaS) offerings that make infostealer capabilities accessible to a wide range of threat actors. Flashpoint analysts identified more than 30 unique infostealer strains actively offered for sale across underground ecosystems.
How can organizations detect credential exposure from infostealers?
Organizations can monitor underground sources where stolen data is shared and sold, identify exposed credentials associated with their domains, and investigate related artifacts such as cookies, host metadata, and malware attribution. The earlier exposure is identified, the greater the opportunity to remediate before attackers operationalize access. Flashpoint collects and parses some infostealer logs within one to two days of infection, helping organizations detect exposure closer to the point of compromise.
What should organizations do if employee credentials appear in an infostealer log?
Organizations should immediately assess the scope of exposure, reset affected credentials, invalidate active sessions, review authentication activity, investigate the infected device, and determine whether additional accounts or systems may have been impacted.
How is Flashpoint’s approach to infostealer intelligence different from traditional breach monitoring?
Many organizations rely on aggregated breach feeds or credential dumps that may be weeks or months old by the time they are discovered. Flashpoint’s Primary Source Collection (PSC) approach provides direct visibility into the forums, marketplaces, Telegram channels, and underground communities where stolen identity data is first shared, sold, and operationalized.
In addition to collecting raw infostealer logs, Flashpoint parses and enriches the data with context such as malware attribution, session cookies, host metadata, browser artifacts, and affected identities. Today, Flashpoint’s credential database contains more than 48 billion credentials, including over 1 billion tied to infostealer activity, providing organizations with actionable intelligence rather than raw exposure data.
Unit 42 uncovers high-risk AI browser extensions. Disguised as productivity tools, they steal data, intercept prompts, and exfiltrate passwords. Protect your browser.
Navigating 2026’s Converged Threats: Insights from Flashpoint’s Global Threat Intelligence Report
In this post, we preview the critical findings of the 2026 Global Threat Intelligence Report, highlighting how the collapse of traditional security silos and the rise of autonomous, machine-speed attacks are forcing a total reimagining of modern defense.
The cybersecurity landscape has reached a point of total convergence, where the silos that once separated malware, identity, and infrastructure have collapsed into a single, high-velocity threat engine. Simultaneously, the threat landscape is shifting from human-led attacks to machine-speed operations as a result of agentic AI, which acts as a force multiplier for the modern adversary.
Flashpoint’s 2026 Global Threat Intelligence Report
Our report uncovers several staggering metrics that illustrate the industrialization of modern cybercrime:
AI-related illicit activity skyrocketed by 1,500% in a single month at the end of 2025.
3.3 billion compromised credentials and cloud tokens have turned identity into the primary exploit vector.
From January 2025 to December 2025, ransomware incidents rose by 53%, as attackers pivot from technical encryption to “pure-play” identity extortion.
Vulnerability disclosures surged by 12% from January 2025 to December 2025, with the window between discovery and mass exploitation effectively vanishing.
These findings are derived from Flashpoint’s Primary Source Collection (PSC), a specialized operating model that collects intelligence directly from original sources, driven by an organization’s unique Priority Intelligence Requirements (PIR). The 2026 Global Threat Intelligence Report leverages this ground-truth data to provide a strategic framework for the year ahead. Download to gain:
A Clear Understanding of the New Convergence Between Identity and AI Discover how threat actors are preparing to transition from generative tools to sophisticated agentic frameworks. Learn how 3.3 billion compromised credentials are being weaponized via automated orchestration to bypass legacy defenses and exploit the connective tissue of modern corporate APIs.
Intelligence on the “Franchise Model” of Global Extortion Gain deep insight into the professionalized operations of today’s most prolific threat actors. From the industrial efficiency of RaaS groups like RansomHub and Clop to the market dominance of the next generation of infostealer malware, we break down the economics driving today’s cybercrime ecosystem.
A Blueprint for Proactive Defense and Risk Mitigation Leverage the latest trends, in-depth analysis, and data-driven insights driven by Primary Source Collection to bolster your security posture by identifying and proactively defending against rising attack vectors.
“As attackers automate exploitation of identity, vulnerabilities, and ransomware, defenders who rely on fragmented visibility will fall behind. To keep pace, organizations must ground their decisions in primary-source intelligence that is drawn from adversarial environments, so that decision-makers can get ahead of this accelerating threat cycle.”
Josh Lefkowitz, CEO & Co-Founder at Flashpoint
The Top Threats at a Glance
Our latest report identifies four driving themes shaping the 2026 threat landscape:
2026 Is the Era of Agentic-Based Cyberattacks
Flashpoint identified a 1,500% rise in AI-related illicit discussions between November and December 2025, signaling a rapid transition from criminal curiosity to the active development of malicious frameworks. Built on data pulled from criminal environments and shaped by fraud use cases, these systems scrape data, adjust messaging for specific targets, rotate infrastructure, and learn from failed attempts without the need for constant human involvement.
“2026 is the era of agentic-based cyberattacks. We’ve seen a 1,500% increase in AI-related illicit discussions in a single month, signaling increased interest in developing malicious frameworks. The discussions evolve into vibe-coded, AI-supported phishing lures, malware, and cybercrime venues. When iteration becomes cheap through automation, attackers can afford to fail repeatedly until they find a successful foothold.”
Ian Gray, Vice President of Cyber Threat Intelligence Operations at Flashpoint
Identity Is the New Exploit
Flashpoint observed over 11.1 million machines infected with infostealers in 2025, fueling a massive inventory of 3.3 billion stolen credentials and cloud tokens. The fundamental mechanics of cybercrime have shifted from breaking in to logging in, as attackers leverage stolen session cookies to behave like legitimate users.
The Patching Window Is Rapidly Closing
Vulnerability disclosures surged by 12% in 2025, with 1 in 3 (33%) vulnerabilities having publicly available exploit code. The strategic gap between discovery and weaponization is increasingly vanishing, as evidenced by mass exploitation of zero-day vulnerabilities in as little as 24 hours after discovery.
Ransomware Is Hacking the Person, Not the Code
As technical defenses against encryption harden, ransomware groups are pivoting to the path of least resistance: human trust. This approach has led to a 53% increase in ransomware, with RaaS groups being responsible for over 87% of all ransomware attacks.
Build Resilience in a Converged Landscape
The findings in the 2026 Global Threat Intelligence Report make one thing clear: incremental improvements to legacy security models are no longer sufficient. As adversaries transition to machine-speed operations, the strategic advantage shifts to organizations that can maintain visibility into the adversarial environments where these attacks are born.
Protecting organizations and communities requires an intelligence-first approach. Download Flashpoint’s 2026 Global Threat Intelligence Report to gain clarity and the data-driven insights needed to safeguard critical assets.
In this post, we analyze DarkCloud, a commercially available infostealer written in Visual Basic 6.0, examine its encryption and evasion techniques, and assess how this low-cost malware can provide threat actors with enterprise-wide access through harvested credentials.
Infostealers continue to dominate the initial access landscape in 2026, lowering the barrier to breach through scalable credential theft. DarkCloud illustrates how low-cost, commercialized malware is reshaping the initial access landscape.
First observed in 2022 and attributed to a developer known as “Darkcloud Coder” (formerly “BluCoder” on Telegram), DarkCloud is openly sold through Telegram and a clearnet storefront with subscription tiers starting at just US$30. Despite being marketed as “surveillance software,” its technical focus is unmistakable: high-volume credential harvesting and structured data exfiltration across browsers, email clients, financial data, and contact networks.
A screenshot from DarkCloud’s clearnet site calling itself “surveillance software.” (Source: DarkCloud clearnet site)
At the technical level, DarkCloud is written in Visual Basic 6.0 and compiled into a native C/C++ application. This legacy language choice is unusual in modern malware development — and likely deliberate. By leveraging outdated but still supported runtime components, DarkCloud appears to benefit from lower detection rates while maintaining full credential theft functionality.
Despite its relatively low cost, DarkCloud should not be dismissed as unsophisticated. Flashpoint assesses it as a potent entry-level threat that can provide adversaries with the keys to an entire corporate network through harvested credentials.
The Commercialization of DarkCloud
DarkCloud describes itself as a keylogger despite the original advertisement on XSS describing it as an infostealer. (Source: DarkCloud)
DarkCloud represents a mature example of commodity malware-as-a-service.
It is openly sold through Telegram and a clearnet website, where it is misleadingly labeled as a keylogger. While it does include keylogging capabilities, this is only a minor component of a much broader infostealing toolkit.
Its real value proposition is credential harvesting across browsers, email clients, file transfer applications, VPN software, and more.
This dual positioning — public-facing “surveillance software” and underground stealer — provides plausible deniability while enabling large-scale credential operations.
Why Visual Basic 6.0 Matters
One of the most notable aspects of DarkCloud is its use of Visual Basic 6.0.
The payload is written in VB6 and compiled into a native C/C++ application. Microsoft no longer supports VB6 in its modern development environment, and VB6 applications rely on legacy components such as MSVBVM60.DLL for execution.
Flashpoint assesses this legacy language choice is deliberate, both for its simplicity and its potential to evade modern detection models.
In testing, Flashpoint analysts generated equivalent payloads in C/C++ and VB6. The VB6 variant produced significantly fewer detections in VirusTotal scans.
The implication is clear: older languages are not necessarily obsolete in adversary tradecraft. In some cases, they may be strategically advantageous.
Encryption and String Obfuscation
DarkCloud employs a layered string encryption scheme that complicates static and dynamic analysis.
Most internal strings are encrypted and decrypted at runtime using Visual Basic’s Rnd() pseudo-random number generator, combined with a custom seed-generation algorithm.
The process involves:
Hex-encoded encrypted strings
Base64-encoded keys
Seed calculation through a custom algorithm
Resetting the VB pseudo-random number generator to a known state
Iterative Rnd() calls to reconstruct plaintext strings
By resetting the PRNG with a known value before applying the calculated seed, the malware ensures deterministic output during decryption.
This approach does not rely on novel cryptography, but rather on abusing legacy language behavior to frustrate reverse engineering.
Credential Theft at Scale
DarkCloud’s primary objective is credential collection.
It targets:
Email clients:
Outlook
eM Client
FoxMail
Thunderbird
163Mail
MailMaster
File transfer applications:
FileZilla
WinSCP
CoreFTP
Browsers:
Google Chrome
Microsoft Edge
Mozilla Firefox
Brave
Opera
Yandex
Vivaldi
(and many additional Chromium- and Firefox-based browsers)
Other applications:
Pidgin
NordVPN
When extracting browser data, DarkCloud steals:
Login credentials
Cookies
Credit card information
Email applications are additionally scraped for contact lists. This is likely intended to seed future phishing campaigns.
DarkCloud stores collected data locally in two directories under %APPDATA%\Microsoft\Windows\Templates. One directory (“DBS”) stores copied database files, while another (“_”) stores parsed data in unencrypted text format.
This local staging enables continuous exfiltration while maintaining structured log output.
Exfiltration Methods: Flexibility for Threat Actors
DarkCloud supports four exfiltration methods:
SMTP
FTP
Telegram
HTTP
SMTP and FTP require hardcoded credentials within each binary. Email subjects include the victim machine’s hostname and username, and stolen data is transmitted as attachments.
HTTP exfiltration appears less frequently used, though the capability is present.
This flexibility allows operators to tailor deployments depending on infrastructure preferences and operational security requirements.
From BluStealer to DarkCloud
Flashpoint analysts identified notable similarities between DarkCloud’s regular expressions for credit card parsing and those found in a publicly documented project known as “A310LoggerStealer,” also referred to as BluStealer.
The regex patterns appear in identical order and format.
Combined with the developer’s prior alias “BluCoder,” Flashpoint assesses that A310LoggerStealer likely represents an earlier iteration of what became DarkCloud.
This evolution reflects a common pattern in commodity malware development: incremental refinement rather than radical innovation.
A Potent Entry-Level Threat
Despite its relatively low cost, DarkCloud should not be dismissed as unsophisticated.
Its marketing as surveillance software attempts to normalize its presence while providing plausible deniability for buyers. Technically, however, its focus is clear: large-scale credential harvesting across browsers, email clients, financial data, and contact networks.
Flashpoint assesses DarkCloud as a potent entry-level threat that can provide adversaries with the keys to an entire corporate network through harvested credentials.
In a landscape where identity is the new perimeter, even a US$30 subscription can be operationally devastating.
Defending Against Commodity Infostealers
Commodity infostealers like DarkCloud may be commercially accessible, but defending against them requires enterprise-grade vigilance.
Organizations should:
Treat phishing-delivered ZIP/RAR attachments as high-risk initial access vectors
Monitor for abnormal data exfiltration over SMTP, FTP, and Telegram
Audit credential reuse across browser and email applications
Prioritize credential rotation and incident response playbooks following suspected compromise
Infostealers like DarkCloud are not breakthrough malware families. They do not rely on zero-days or advanced exploits.
Instead, they exploit scale, accessibility, and identity exposure.
To understand how credential harvesting campaigns are evolving and to embed real-time intelligence into your detection workflows, request a demo today and see how Flashpoint intelligence strengthens your defense posture.
As part of our commitment to sharing interesting hunts, we are launching these 'Flash Hunting Findings' to highlight active threats. Our latest investigation tracks an operation active between January 11 and January 15, 2026, which uses consistent ZIP file structures and a unique behash ("4acaac53c8340a8c236c91e68244e6cb") for identification. The campaign relies on a trusted executable to trick the operating system into loading a malicious payload, leading to the execution of secondary-stage infostealers.
Findings
The primary samples identified are ZIP files that mostly reference the MalwareBytes company and software using the filename malwarebytes-windows-github-io-X.X.X.zip. A notable feature for identification is that all of them share the same behash.
behash:"4acaac53c8340a8c236c91e68244e6cb"
The initial instance of these samples was identified on January 11, 2026, with the most recent occurrence recorded on January 14.
All of these ZIP archives share a nearly identical internal structure, containing the same set of files across the different versions identified. Of particular importance is the DLL file, which serves as the initial malicious payload, and a specific TXT file found in each archive. This text file has been observed on VirusTotal under two distinct filenames: gitconfig.com.txt and Agreement_About.txt.
The content of the TXT file holds no significant importance for the intrusion itself, as it merely contains a single string consisting of a GitHub URL.
However, this TXT is particularly valuable for pivoting and infrastructure mapping. By examining its "execution parents," analysts can identify additional ZIP archives that are likely linked to the same malicious campaign. These related files can be efficiently retrieved for further investigation using the following VirusTotal API v3 endpoint:
The primary payload of this campaign is contained within a malicious DLL named CoreMessaging.dll. Threat actors are utilizing a technique known as DLL Sideloading to execute this code. This involves placing the malicious DLL in the same directory as a legitimate, trusted executable (EXE) also found within the distributed ZIP file. When an analyst or user runs the legitimate EXE, the operating system is tricked into loading the malicious CoreMessaging.dll.
The identified DLLs exhibit distinctive metadata characteristics that are highly effective for pivoting and uncovering additional variants within the same campaign. Security analysts can utilize specific hunting queries to track down other malicious DLLs belonging to this activity. For instance, analysts can search for samples sharing the following unique signature strings found in the file metadata:
Furthermore, the exported functions within these DLLs contains unusual alphanumeric strings. These exports serve as reliable indicators for identifying related malicious components across different stages of the campaign:
Finally, another observation for behavioral analysis can be found in the relations tab of the ZIP files. These files document the full infection chain observed during sandbox execution, where the sandbox extracts the ZIP, runs the legitimate EXE, and subsequently triggers the loading of the malicious DLL. Within the Payload Files section, additional payloads are visible. These represent secondary stages dropped during the initial DLL execution, which act as the final malware samples. These final payloads are primarily identified as infostealers, designed to exfiltrate sensitive data.
Analysis of all the ZIP files behavioral relations reveals a recurring payload file consistently flagged as an infostealer. This malicious component is identified by various YARA rules, including those specifically designed to detect signatures associated with stealing cryptocurrency wallet browser extension IDs among others.
To identify and pivot through the various secondary-stage payloads dropped during this campaign, analysts can utilize a specific behash identifier. These files represent the final infection stage and are primarily designed to exfiltrate credentials and crypto-wallet information. The following behash provides a reliable pivot point for uncovering additional variants.
behash:5ddb604194329c1f182d7ba74f6f5946
IOCs
We have created a public VirusTotal Collection to share all the IOCs in an easy and free way. Below you can find the main IOCs related to the ZIP files and DLLs too.
import "pe"
rule win_dll_sideload_eosinophil_infostealer_jan26
{
meta:
author = "VirusTotal"
description = "Detects malicious DLLs (CoreMessaging.dll) from an infostealer campaign impersonating Malwarebytes, Logitech, and others via DLL sideloading."
reference = "https://blog.virustotal.com/2026/01/malicious-infostealer-january-26.html"
date = "2026-01-16"
behash = "4acaac53c8340a8c236c91e68244e6cb"
target_entity = "file"
hash = "606baa263e87d32a64a9b191fc7e96ca066708b2f003bde35391908d3311a463"
condition:
(uint16(0) == 0x5A4D and uint32(uint32(0x3C)) == 0x00004550 and pe.is_dll()) and
pe.exports("15Mmm95ml1RbfjH1VUyelYFCf") and pe.exports("2dlSKEtPzvo1mHDN4FYgv")
}
The Infostealer Gateway: Uncovering the Latest Methods in Defense Evasion
In this post, we analyze the evolving bypass tactics threat actors are using to neutralize traditional security perimeters and fuel the global surge in infostealer infections.
Infostealer-driven credential theft in 2025 has surged, with Flashpoint observing a staggering 800% increase since the start of the year. With over 1.8 billion corporate and personal accounts compromised, the threat landscape finds itself in a paradox: while technical defenses have never been more advanced, the human attack surface has never been more vulnerable.
Information-stealing malware has become the most scalable entry point for enterprise breaches, but to truly defend against them, organizations must look beyond the malware itself. As teams move into 2026 security planning, it is critical to understand the deceptive initial access vectors—the latest tactics Flashpoint is seeing in the wild—that threat actors are using to manipulate users and bypass modern security perimeters.
Here are the latest methods threat actors are leveraging to facilitate infections:
1. Neutralizing Mark of the Web (MotW) via Drag-and-Drop Lures
Mark of the Web (MotW) is a critical Windows defense feature that tags files downloaded from the internet as “untrusted” by adding a hidden NTFS Alternate Data Stream (ADS) to the file. This tag triggers “Protected View” in Microsoft Office programs and prompts Windows SmartScreen warnings when a user attempts to execute an unknown file.
Flashpoint has observed a new social engineering method to bypass these protections through a simple drag-and-drop lure. Instead of asking a user to open a suspicious attachment directly, which would trigger an immediate MotW warning, threat actors are instead instructing the victim to drag the malicious image or file from a document onto their desktop to view it. This manual interaction is highly effective for two reasons:
Contextual Evasion: By dragging the file out of the document and onto the desktop, the file is executed outside the scope of the Protected View sandbox.
Metadata Stripping: In many instances, the act of dragging and dropping an embedded object from a parent document can cause the operating system to treat the newly created file as a local creation, rather than an internet download. This effectively strips the MotW tag and allows malicious code to run without any security alerts.
2. Executing Payloads via Vulnerabilities and Trusted Processes
Flashpoint analysts uncovered an illicit thread detailing a proof of concept for a client-side remote code execution (RCE) in the Google Web Designer for Windows, which was first discovered by security researcher Bálint Magyar.
Google Web Designer is an application used for creating dynamic ads for the Google Ads platform. Leveraging this vulnerability, attackers would be able to perform remote code execution through an internal API using CSS injection by targeting a configuration file related to ads documents.
Within this thread, threat actors were specifically interested in the execution of the payload using the chrome.exe process. This is because using chrome.exe to fetch and execute a file is likely to bypass several security restrictions as Chrome is already a trusted process. By utilizing specific command-line arguments, such as the –headless flag, threat actors showed how to force a browser to initiate a remote connection in the background without spawning a visible window. This can be used in conjunction with other malicious scripts to silently download additional payloads onto a victim’s systems.
3. Targeting Alternative Softwares as a Path of Least Resistance
As widely-used software becomes more hardened and secure, threat actors are instead pivoting to targeting lesser-known alternatives. These tools often lack robust macro-protections. By targeting vulnerabilities in secondary PDF viewers or Office alternatives, attackers are seeking to trick users into making remote server connections that would otherwise be flagged as suspicious.
Understanding the Identity Attack Surface
Social engineering is one of the driving factors behind the infostealer lifecycle. Once an initial access vector is successful, the malware immediately begins harvesting the logs that fuel today’s identity-based digital attacks.
As detailed in The Proactive Defender’s Guide to Infostealers, the end goal is not just a password. Instead, attackers are prioritizing session cookies, which allow them to perform session hijacking. By importing these stolen cookies into anti-detect browsers, they bypass Multi-Factor Authentication and step directly into corporate environments, appearing as a legitimate, authenticated user.
Understanding how threat actors weaponize stolen data is the first step toward a proactive defense. For a deep dive into the most prolific stealer strains and strategies for managing the identity attack surface, download The Proactive Defender’s Guide to Infostealers today.
Beyond the Malware: Inside the Digital Empire of a North Korean Threat Actor
In this post Flashpoint reveals how an infostealer infection on a North Korean threat actor’s machine exposed their digital operational security failures and reliance on AI. Leveraging Flashpoint intelligence, we pivot from a single persona to a network of fake identities and companies targeting the Web3 and crypto industry.
Last week, Hudson Rock published a blog on “Trevor Greer,” a persona tied to a North Korean IT Worker. Flashpoint shared additional insights with our clients back in July, and we’re now making those findings public.
Trevor Greer, a North Korean operative, was identified via an infostealer infection on their own machine. Information-stealing malware, also known as Infostealers or stealers, are malware designed to scrape passwords and cookies from unsuspecting victims. Stealers (like LummaC2 or RedLine) are typically used by cybercriminals to steal login credentials from everyday users to sell on the Dark Web. It is rare to see them infect the machines of a state-sponsored advanced persistent threat group (APT).
However, when adversaries unknowingly infect themselves, they can expose valuable insights into the inner workings of their campaigns. Leveraging Flashpoint intelligence sourced from the leaked logs of “Trevor Greer,” our analysts uncovered a myriad of fake identities and companies used by DPRK APTs.
Finding Trevor Greer
Flashpoint analysts have been tracking the Trevor Greer email address since December 2024 in relation to the “Contagious Interview” campaign, in which threat actors operated as LinkedIn recruiters to target Web3 developers, resulting in the deployment of multiple stealers compromising developer Web3 wallets. Flashpoint also identified the specific persona’s involvement in a campaign in which North Korean threat actors posed as IT freelance workers and applied for jobs at legitimate companies before compromising the organizations internally.
ByBit Compromise
The ByBit compromise in late February 2025 further fueled Flashpoint’s investigations into the Trevor Greer email address. Bybit, a cryptocurrency exchange, suffered a critical incident resulting in North Korean actors extorting US $1.5 billion worth of cryptocurrency. In the aftermath, Silent Push researchers identified the persona “Trevor Greer” associated with the email address trevorgreer9312@gmail[.]com, which registered the domain “Bybit-assessment[.]com” prior to the Bybit compromise.
A later report claimed that the domain “getstockprice[.]com” was involved in the compromise. Despite these domain discrepancies, both investigations attributed the attack to North Korean advanced persistent threat (APT) nexus groups.
Tracing the Infection
Using Flashpoint’s vast intelligence collections, we performed a full investigation of compromised virtual private servers (VPS), revealing the actor’s potential involvement in several other operations, including remote IT work, several self-made blockchain and cryptocurrency exchange companies, and a potential crypto scam dating back to 2022.
Flashpoint analysts also discovered that the Trevor Greer email address was linked to domains infected with information-stealing malware.
What the Logs Revealed
Analysts extracted information about the associated infected host from Trevor Greer, revealing possible tradecraft and tools used. Analysts further identified specific indicators of compromise (IOCs) used in the campaigns mentioned above, as well as email addresses used by the actor for remote work.
The data painted a vivid picture of how these threat actors operate:
Preparation for “Contagious Interviews”
The browser history revealed the actor logging into Willo, a legitimate video interview platform. This suggests the actor was conducting reconnaissance to clone the site for the “Contagious Interview” campaign, where they lured Web3 developers into fake job interviews to deploy malware.
Reliance on AI Tools
The logs exposed the actor’s reliance on AI to bridge the language gap. The operator frequently accessed ChatGPT and Quillbot, likely using them to write convincing emails, build resumes, and generate code for their malware.
Pivoting: One Node to a Network
By analyzing the “Trevor Greer” logs, we were able to pivot to other personas and campaigns involved in the operation.
Fake Employment: The logs contained credentials for freelance platforms, such as Upwork and Freelancer, associated with other aliases, including “Kenneth Debolt” and “Fabian Klein.” This confirmed the actor was part of a broader scheme to infiltrate Western companies as remote IT workers.
Fake Companies: The data linked the actor to fake corporate entities, such as Block Bounce (blockbounce[.]xyz), a sham crypto trading firm set up to appear legitimate to potential victims.
Developer Personas: The infection data linked the actor to the GitHub account svillalobosdev, which had been active in open source projects to build credibility before the attack.
Legitimate Platforms & Tools: Analysts observed the actor using job boards such as Dice and HRapply[.]com, freelance platforms such as Upwork and Freelancer, and direct applications through company Workday sites. To improve their resume, the actor used resumeworded[.]com or cakeresume[.]com. For conversing, the threat actor likely relies on a mix of both GPT and Quilbot, as found in infected host logins, to ensure they sound human. During interviews, analysts determined that they potentially used Speechify.
Deep & Dark Web Resources: The actor also likely purchased Social Security numbers (SSNs) from SSNDOB24[.]com, a site for acquiring Social Security data.
Disrupt Threat Actors Using Flashpoint
The “Trevor Greer” case study illustrates a critical shift in modern threat intelligence. We are no longer limited to analyzing the malware adversaries deploy; sometimes, we can analyze the adversaries themselves.
Using their own tools against them, Flashpoint transformed a faceless state-sponsored entity into a tangible user with bad habits, sloppy OPSEC, and a trail of digital breadcrumbs. Behind every sophisticated APT campaign is a human operator, and sometimes, they click the wrong link too.
Request a demo today to delve deeper into the tactics, techniques, and procedures of advanced persistent threats and learn how Flashpoint’s intelligence strengthens your defenses.
From Endpoint Compromise to Enterprise Breach: Mapping the Infostealer Attack Chain
In Flashpoint’s latest webinar, we map the global infostealer attack chain step-by-step, from initial infection to enterprise-level account takeover. We analyze how the commodification of stolen identities works and demonstrate how Flashpoint intelligence provides the critical visibility necessary to disrupt this cycle.
Compromised digital identities have become one of the most valuable currencies in the cybercriminal ecosystem. The rise of information-stealing malware has created an industrial-scale supply chain for stolen credentials, session cookies, and browser fingerprints, directly fueling account takeover (ATO) campaigns that penetrate even the most mature security environments.
Flashpoint recently hosted an on-demand webinar, “From Compromise to Breach: How Infostealers Power Identity Attacks,” where our experts dissected this developing threat landscape. We exposed the exact sequence of events, providing defenders with the actionable intelligence required to disrupt the chain at multiple points. For the full technical breakdown, check out the full on-demand webinar.
Here are the main key takeaways you need to know:
Stage 1: Initial Infection and Data Harvest (The Compromise)
A full scale compromise often begins with a single event, typically a phishing lure, a malicious download, or a compromised cracked software installer. Once executed, the infostealer goes to work, quickly and stealthily, to build a “log” that grants post-MFA (multi-factor authentication) access.
Scouring now-compromised endpoints, the stealer searches for and compiles data such as:
Credentials: Saved logins, credit card details, and passwords for applications and websites.
Session Cookies/Tokens: These are the keys that allow an attacker to bypass login prompts entirely, appearing as an already-authenticated user.
Browser Fingerprints and System Metadata: Geolocation, IP address, and system language used to evade security tools by accurately mimicking the victim’s legitimate environment.
Stage 2: Commodification and the ATO Supply Chain (The Market)
Once a log is harvested, it enters the Infostealer-as-a-Service ecosystem, a critical industrialized stage of the attack chain. Here, threat actors can rent or purchase access to millions of fresh logs, effectively outsourcing the initial compromise phase and enabling mass identity exploitation for a minimal investment.
Check out the on-demand webinar for a full technical breakdown of this dark web economy and how the commodification of stealer logs drastically reduces the barrier to entry for follow-on attacks.
Stage 3: Post-MFA Account Takeover (The Breach)
This is the ultimate pivot point, where a simple endpoint infection escalates into an enterprise breach. Unlike the brute-forcing and phishing attacks of the past, attackers leverage the stolen session tokens and browser fingerprints.
Stolen log buyers leverage obfuscation tools such as anti-detect browsers. These tools ensure the attacker can seamlessly utilize the stolen cookies and digital fingerprints to appear identical to the original victim.
They inject valid, unexpired session tokens into their browser, which allows attackers to hijack the victim’s active session. This allows them to avoid fraud and anomaly detection systems, providing them access into corporate VPNs, cloud environments, and internal applications without ever needing to see a login prompt. From here, attackers can move laterally, exfiltrate sensitive data, or deploy ransomware.
Disrupting the Attack Chain Using Flashpoint’s Actionable Intelligence
Defense against this threat requires not only an understanding of the attack chain, but also comprehensive Cyber Threat Intelligence (CTI) to identify and mitigate risks at every stage:
Disruption Point in the Attack Chain
How Flashpoint Empowers Proactive Defense
Stage 1: Initial Infection/Log Creation
Gain immediate alerting on the sale of your organization’s compromised assets on the Dark Web before attackers can leverage stolen data.
Stage 2: Commodification/ATO Setup
Expose the illicit platforms and forums where threat actors discuss, buy, and sell stolen logs, allowing you to track the tooling and TTPs.
Stage 3: Post-MFA ATO/Breach
Identify and remediate the vulnerabilities within browsers or enterprise software that are most actively being targeted by infostealers.
The speed of infostealer-powered attacks demands an intelligence-driven response. Our recent webinar demonstrated how Flashpoint intelligence can empower your security teams to quickly identify and validate stolen logs, protecting your organization from compromise to breach. Watch the on-demand webinar to learn more, or request a demo today.
Flashpoint’s Top 5 Predictions for the 2026 Threat Landscape
Flashpoint’s forward-looking threat insights for security and executive teams, provides the strategic foresight needed to prepare for the convergence of AI, identity, and physical security threats in 2026.
As the global threat landscape accelerates its transformation, 2026 marks an inflection point requiring defensive strategies to fundamentally shift. The volatility observed in 2025 has paved the way for an era soon to be defined by AI-weaponized autonomy, information-stealing malware, systemic instability of public vulnerability systems, and the complete convergence of digital and physical risk.
Flashpoint offers a unique window into these complexities, providing organizations with the foresight needed to navigate what lies ahead. Drawing from Flashpoint’s leading intelligence and primary source collections, we highlight five key trends shaping the 2026 threat landscape. These insights aim to help organizations not only understand what’s next but also build the resilience needed to withstand and adapt to emerging challenges.
Prediction 1: Agentic AI Threats Will Weaponize Autonomy, Forcing a New Defensive Standard
2026 will see continued evolution of AI threats, with future attacks centering on autonomy and integration. Across the deep and dark web, Flashpoint is observing threat actors move past experimentation and into operational use of illegal AI.
As attackers train custom fraud-tuned LLMs (Large Language Models) and multilingual phishing tools directly on illicit data, these AI models will become more capable. The criminal intent shaping their misuse will also become more sophisticated. Additionally, 2026 will see a greater marketplace for paid jailbreaking communities and synthetic media kits for KYC (Know Your Customer) bypass.
These advancements are enabling criminals to move beyond simple tools and engage in scaled, autonomous fraud operations, leading to two major shifts:
Agentic AI is becoming the true flashpoint: Threat actors will be using agentic systems to automate reconnaissance, generate synthetic identities, and iterate on fraud playbooks in near real-time. In this SaaS ecosystem, AI will help attackers leverage subscription tiers and customer feedback loops at scale.
The attack surface will shift to focus on AI Integrations: Organizations are increasingly plugging LLMs into live data streams, internal tools, identity systems, and autonomous agents. This practice often lacks the same security vetting, access controls, and monitoring applied to other enterprise systems. As such, attackers will heavily target these integrations, such as APIs, plugins, and system connections, rather than the models themselves.
“The ubiquity of automation has dramatically increased attack tempo, leaving many security teams behind the curve. While automation can replace repetitive tasks across the enterprise, organizations must not make the critical mistake of substituting human judgement for AI at the intelligence level.
This is paramount because a critical threat in 2026 is Agentic AI autonomy weaponized against soft targets—API integrations and identity systems. The only winning defense will be human-led and AI-scaled, prioritizing purposeful use to keep organizations ahead of this exponential risk.”
Josh Lefkowitz, CEO at Flashpoint
These evolving AI threats will force a fundamental shift in defensive strategies. Defenders will have to shift to deploying systems around AI rather than trust them on their own.
Prediction 2: Identity Compromise via Infostealers Will Become the Foundation of Every Attack
Infostealers will become the entry point, the data broker, the reconnaissance layer, and the fuel for everything that comes after a cyberattack. This shift is already in motion and is accelerating rapidly: in just the first half of 2025, infostealers were responsible for 1.8 billion stolen credentials, an 800% spike from the start of the year. However, 2026 will redefine the malware’s role, making its most valuable output being access, rather than disruption.
Infostealers will become the upstream event that powers the rest of the attack chain. Identity and session data will be increasingly targeted, since it gives attackers immediate access into victim environments. Ransomware, fraud, data theft, and extortion will simply be downstream ways to monetize.
This upstream approach defines the new reality of the attack chain, which is already operational. Nearly every major stealer strain Flashpoint observes now exfiltrates the following:
An organization’s attack surface is no longer just composed of their own networks. It is the entire digital identity of their employees and partners. This new reality requires security teams to take a new approach. Instead of attempting to block attacks, they must proactively detect compromised credentials before they are weaponized. This will be the difference between reacting to a data breach and preventing one.
“The infostealer economy has fully industrialized the attack chain, making initial compromise a low-cost commodity. Multiple security incidents in 2025 tie back to credentials found in infostealer logs. This reality has underscored the critical importance of digital trust—specifically, verifying who can access what resources. For 2026, identity is the perimeter to watch, and security teams must proactively hunt for compromised credentials before they’re weaponized.”
Ian Gray, Vice President of Intelligence at Flashpoint
Prediction 3: CVE Volatility Will Force Redundancy in Vulnerability Intelligence
The temporary funding crisis at CVE in April 2025 and the subsequent CISA stopgap extension through March 2026 exposed the systemic fragility of a centralized vulnerability intelligence model. With the future of the CVE/NVD system hanging in the balance, 2026 will be defined by the urgent need for redundancy and diversification in vulnerability intelligence.
In today’s vulnerability intelligence ecosystem, nearly every organization’s vulnerability management framework relies on CVE and NVD—including its “alternatives” such as the EUVD (European Union Vulnerability Database). The CVE system has grown into a critical global cybersecurity utility, relied upon by nearly all vulnerability scanners, SIEM platforms, patch management tools, threat intelligence feeds, and compliance reports. A complete shutdown of CVE would result in a widespread loss of institutional infrastructure.
The next generation of security needs to be built on practices that are resilient, diversified, and intelligence-driven. It should be focused on providing insights that can be used to take action such as threat actor behavior, likelihood of exploitation in the wild, relevance to ransomware campaigns, and business context. Security teams will need to leverage a comprehensive source of vulnerability intelligence such as Flashpoint’s VulnDB that provides full coverage for CVE, while also cataloging more than 100,000 vulnerabilities missed by CVE and NVD.
Prediction 4: Executive Protection Will Remain a Critical Challenge as Cyber-Physical Threats Converge
The continued blurring of lines between cyber, physical, and geopolitical threats will elevate the risk to organizational leadership, turning executive protection into a holistic intelligence function in 2026. The rise of information warfare combined with physical world convergence means the threat to key personnel is no longer purely digital.
In the aftermath of the tragic December 2024 assassination of United Healthcare’s CEO, Flashpoint has seen the continued circulation and glorification of “wanted-style posters” of executives in extremist communities. Additionally, Flashpoint has seen nation-state actors participate, using espionage and influence to target high-value individuals. Organizations must adopt an integrated approach that connects insights from threat actor chatter and a wealth of other OSINT sources. This fusion of intelligence is essential for applying frameworks to ensure the safety of leadership and key personnel.
Prediction 5: Extortion Shifts to Identity-Based Supply Chain Risk
2025 was marked by several large-scale extortion campaigns, demonstrating how the threat landscape is rapidly evolving. Ransomware operations have shifted into a straight extortion play. Flashpoint has observed a surge in new entrants to the ransomware market, accompanied by a decline in the quality and decorum of ransomware groups.
Furthermore, vishing campaigns attributed to “Scattered Spider” have highlighted weaknesses in identity, trust, and verification. Campaigns from “Scattered LAPSUS$ Hunters” have also exposed vulnerabilities in third-party integrations. These attacks culminated in extortion, showcasing that modern attacks will target trusted users and trusted applications for initial access, and will forgo ransomware in place of data access.
As this shift continues into 2026, threat actors will increasingly focus their efforts on exploiting human behavior and identity systems. Instead of attempting to spend resources on breaking network perimeters, attackers will instead socially engineer employees to gain access to corporate systems at scale. This change in TTPs will undoubtedly greatly increase supply chain risk, especially for third parties.
Charting a Path Through an Evolving Threat Landscape with Flashpoint Intelligence
These five predictions highlight the transformative trends shaping the future of cybersecurity and threat intelligence. Staying ahead of these challenges demands more than just reactive measures—it requires actionable intelligence, strategic foresight, and cross-sector collaboration. By embracing these principles and investing in proactive security strategies, organizations can not only mitigate risks but also seize opportunities to enhance their resilience.
As the threat landscape continues to rapidly evolve, staying informed and prepared are critical components of risk mitigation. With the right tools, insights, and partnerships, security teams can navigate the complexities ahead and safeguard what matters most.
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