Updated: The NCSC is encouraging UK organisations to take immediate action to mitigate a security issue affecting PHP (CVE-2026-109618 and CVE-2026-109619).
Source: NCSC UK · 2026-10-21
Updated: The NCSC is encouraging UK organisations to take immediate action to mitigate a security issue affecting PHP (CVE-2026-109618 and CVE-2026-109619).
Source: NCSC UK · 2026-10-21
There’s a new archive of all the papers from twenty-five years of the Workshop on Economics and Information Security (WEIS).
Really nice resource. It’s fun to reread my 2002 essay on the economics of information security.
Source: Schneier on Security · 2026-10-21
A new CISA advisory warns of the threat posed by SafePay to businesses and critical infrastructure, and urges defenders to take action to mitigate the group’s tactics
Source: Infosecurity Magazine · 2026-10-21
Two critical vulnerabilities in PHP were leaked one day before their scheduled disclosure and security patches
Source: Infosecurity Magazine · 2026-10-21

To escape the chaos of her Russian childhood, Lili Infante became an American law enforcement prodigy. She pioneered the DEA’s investigations of the dark web—never suspecting who she’d find hiding there.
Source: WIRED Security · 2026-10-21


Talos recently analyzed two order notification campaigns abusing Staples and Dell transactional email pipelines. Together, these campaigns accounted for roughly 1,400 messages observed by Talos.
The malicious element was not the outer sender identity, like a simple forged sender or lookalike domain. It was the content of the legitimate order notification workflow rendered. The suspicious content appeared inside the notification itself, in fields that would normally contain shipping information. The attacker’s objective was to use a trusted retail pipeline to create urgency around a high-value purchase and push the recipient toward an attacker-controlled phone number.
In the first campaign, the message appeared as a Staples order confirmation from “support@orders.staples.com” with the subject line, “Here’s your Staples order #9939818875. Thanks for shopping with us.” The body displayed a plausible purchase for an Apple iPad, including order number, delivery timing, pricing, billing information and standard Staples footer content. The suspicious element was embedded in the order details: “Helpline 806 283 7712,” “Order Confirmed,” and the Staples corporate address appeared in fields normally associated with shipping or billing information.

The structure of the message matters. The attacker was not trying to persuade the user to click a crude phishing link. Instead, the message created the impression that an expensive order had already been placed and that the fastest way to resolve it was to call the embedded “helpline.” The desired user action was a phone call. Once the victim moved from email to voice, the attacker could continue the scam through social engineering, payment manipulation, credential theft, or remote assistance fraud.
The headers reinforced the trust problem. The Staples message showed DKIM alignment for “orders.staples.com” and DMARC passed for the visible Staples domain. The message also passed through forwarding and re-encapsulation paths, including Proton Mail, Microsoft 365, and downstream enterprise mail infrastructure. These hops complicate provenance analysis, but they do not change the core issue: Authentication helped establish that the outer message was credible, while offering no assurance that the phone number or transaction context was legitimate.
The second campaign used the same pattern in a Dell order received notification. The message was sent from “Dell | Order Received <received@order.dellcom>” with the subject line, “We have your order | Dell Purchase ID: 2009829958247.” The body presented a purchase for Microsoft Project Standard 2024, totaling $736.09. As with the Staples example, the suspicious content appeared in transaction fields. The “Ship To” and “Bill To” sections included “Confirmed Order,” “Helpline 808 232 6397,” and “Call Our Sales Team”.
The Dell message used the same psychological lever: an unexpected high-value purchase, a legitimate-looking order template, and a phone number positioned as the path to resolution. The attacker did not need the recipient to trust a new domain or unfamiliar brand. The message borrowed credibility from Dell’s order pipeline and redirected the recipient toward attacker-controlled contact information.
Authentication results showed DKIM passing for Dell-related infrastructure and DMARC passing for “order.dell.com”. As with the Staples sample, forwarding artifacts and SRS-style return paths appeared as the message moved through Microsoft and enterprise mail infrastructure. But the malicious intent did not live in an obviously forged sender. It lived inside the rendered order content.

These campaigns illustrate the same trust-boundary failure described in our earlier research on platform-as-a-proxy (PaaP) abuse. In those cases, attackers placed malicious content into SaaS fields that trusted platforms later rendered into notifications. Here, the same concept appears in commerce infrastructure, in the retailer’s order pipeline. The attacker supplies the intent, while the trusted system performs the delivery.
From a defensive perspective, sender authentication is necessary, but it is not sufficient. SPF, DKIM, and DMARC help answer whether a message came from expected infrastructure. However, they do not answer whether the transaction was legitimate, whether the rendered fields make business sense, or whether the user is being pushed toward an attacker-controlled action.
Order notifications should be treated as sensitive content. Any field reflected into a transactional message — shipping name, billing name, address line, company name, order note, support field, or fulfillment instruction — can become a delivery vehicle if it is not validated before rendering. Retailers and security teams should correlate order notification content with account history, payment state, shipping context, and known support channels. Transactional templates should reject or flag unexpected phone numbers, URLs, urgency language, and support instructions when they appear in fields where they do not belong.
In both campaigns, the wrapper was legitimate enough to inherit trust. The payload was attacker-influenced. That distinction is the center of this attack class.
The abuse of commerce pipelines is merely one manifestation of a broader, systemic vulnerability. Whether the attacker initiates a fake purchase or a fraudulent account sign-up, the root cause remains the same: Platforms are implicitly trusting data that enters their systems from untrusted sources, only to render that data into high-reputation, automated notifications. This same mechanism of reflection — where input is echoed back into an email to a third party — is the engine behind an evolution in list bombing, moving the attack from simple denial-of-service to a sophisticated vehicle for content delivery.
List bombing is an abuse technique in which attackers submit a victim’s email address to numerous legitimate registration, subscription or notification workflows, flooding the inbox with automated messages. While this vector is traditionally viewed as a denial-of-service or distraction tactic designed to bury critical alerts in a flood of junk, Talos has observed a subset of cases where this behavior is being repurposed as a delivery vehicle for malicious content. This abuse occurs when an attacker identifies public-facing registration, profile, or project-naming forms that lack sufficient input validation. By inputting a “hostile string” — such as a cryptocurrency-themed lure — into fields intended for a name, company, or title, the attacker forces the platform to treat this data as legitimate user information. When the service reflexively incorporates this input into its automated welcome, verification, or notification templates, the system acts as an unintended carrier, delivering the attacker’s content inside a high-reputation, system-generated email that can pass standard authentication checks.
The attacker’s objective in these cases is to bypass the security perimeter by laundering their malicious content through the brand reputation of a trusted service provider. While this is not yet a broad industry shift, it represents a calculated abuse of a platform’s trust boundary. By embedding their lure in an automated notification, the adversary ensures that the message arrives with the appearance of administrative legitimacy, significantly increasing the likelihood that the recipient will trust the content. The goal is to reach the target’s inbox with enough platform authority that the message may be evaluated as routine notification traffic rather than attacker-controlled content.

Beyond the risk to the individual recipient, this vector creates a significant brand liability. When a service provider’s infrastructure is used to broadcast fraudulent content, the resulting user complaints and bounce-backs can degrade the platform’s own sender reputation, potentially triggering blocklisting that impacts their legitimate business communications.
The final vector moves the abuse pattern into the mail system itself. Instead of relying on a retailer, SaaS platform, or registration workflow to generate the message, the attacker attempts to make a delivery status workflow carry attacker-controlled content.
Bounces, formally known as delivery status notifications (DSNs) or non-delivery reports (NDRs), are generated when a message cannot be delivered. Under normal conditions, a mail system sends the delivery report back to the original SMTP envelope sender. Depending on the implementation, that report may include the original headers, portions of the message body, URLs, attachments, or an encapsulated copy of the failed message. That returned content creates the abuse opportunity.
In one example Talos observed, a mail delivery system notification carried a WeTransfer-themed file-sharing lure. The administrative wrapper made the message look like routine mail-system noise, while the nested content asked the recipient to engage with what appeared to be a file transfer workflow. The attacker’s goal was to make the phishing lure feel less like an unsolicited external message and more like part of a technical delivery failure that required review. Users are conditioned to view system errors as benign and are far more likely to engage with an “administrative” fix than a suspicious, standalone phishing email.

There are several ways this kind of message can reach a victim. In opportunistic backscatter, an attacker sends mail using the victim’s address as the forged envelope sender. If an intermediate system accepts the message and later fails to deliver it, the resulting DSN may be sent back to the forged sender. If the DSN includes enough of the original message, the bounce itself can carry the lure.
A second possibility is intentional bounce abuse, where the attacker uses an authenticated, compromised, or otherwise controllable sending context to trigger a delivery failure that returns attacker-influenced content. This differs from an outright forged NDR, where the attacker simply fabricates the bounce message and sends it directly. From the recipient’s mailbox, however, these cases can look similar: A delivery-failure wrapper contains content the attacker wants the user to trust.
This distinction matters for defenders. A DSN’s administrative appearance does not validate the content inside it. The outer message may be a legitimate delivery report, while the returned or encapsulated content may still contain a phishing link, credential harvesting page, malicious attachment, or social engineering prompt.
Across these vectors, the defensive failure is consistent: Trusted infrastructure is being treated as a shortcut for trusted content.
Sender authentication remains essential. SPF, DKIM, DMARC, reputation, and infrastructure analysis help determine whether a message came from an expected source. But these controls do not answer a separate and increasingly important question: What was that trusted system instructed to carry?
Order notifications, registration workflows and delivery reports all create opportunities for attacker-influenced content to appear inside messages that users and security tools are conditioned to trust. In the Staples and Dell campaigns, the suspicious content was a phone number placed into transactional fields. In list bombing and registration abuse, the lure can appear inside reflected account or profile data. In bounce abuse, the malicious content may sit inside returned message data or a nested MIME object.
Defending against this requires content-aware validation at multiple points in the delivery chain. Platform owners should treat any user-controlled value rendered into an email template as untrusted data. Fields used for names, addresses, company names, project titles, order notes or support instructions should be validated before storage and again before rendering. Phone numbers, URLs, markup, line breaks, and urgent support language should be rejected or flagged when they appear in fields where they do not belong.
Security gateways should inspect the fully rendered message, not only the sender or template. That includes HTML, text, URLs, redirects, attachments, personalization fields, and nested MIME content. For transactional email, defenders should also evaluate whether the message content aligns with the workflow that produced it. An order notification containing unexpected support numbers, cancellation instructions, or high-urgency language should be treated differently from a routine receipt.
For delivery reports, recursive MIME inspection is especially important. Gateways should parse DSN containers, extract returned messages or message fragments, and apply normal phishing, malware, and URL analysis to the nested content. A bounce should explain a delivery failure, not provide a blind path for untrusted payloads.
The broader lesson is that attackers are no longer only exploiting technical vulnerabilities in infrastructure. They are exploiting the assumptions built into business processes. When legitimate systems render attacker-influenced data into trusted notifications, the result can pass authentication checks and still deliver malicious intent.
Defenders should therefore treat sender trust and content trust as separate but complementary signals. The wrapper can explain where a message came from. It cannot prove that the payload is safe.
Special thanks to Eric Peterson, Dev Shah, and Adam Katz for their professional guidance and input during the development of this research.
Source: Cisco Talos Intelligence · 2026-10-21

In 2023, OCCRP reported that Venezuela’s former head of the treasury under President Hugo Chávez had been under investigation in Liechtenstein for allegedly laundering money using gold bars.
Reporters found that investigators had also looked into Swiss banker Ronnie Budja, but could not confirm whether he faced any charges.
Liechtenstein authorities have since confirmed that an official investigation into Budja was discontinued in 2024 due to insufficient grounds to initiate criminal proceedings.
Source: OCCRP · 2026-10-21
words, the “IRS uses sophisticated, layered computer fraud concealed by falsified, sanitized paper records
Source: CourtListener — Breach & Hacking Opinions · 2026-10-21


In January, we responded to the Lazarus Group’s novel attack campaign against South Korea, which followed last year’s Operation SyncHole. In this new operation, the group employed an updated malware chain that included both their old and new malware, which we disclosed in full, and used another mandatory South Korean security software program as a part of infection chain using a watering‑hole strategy. Notably, the group targeted victims more selectively, sending spear‑phishing emails with links to fabricated but relevant sites, such as portfolio and résumé pages tailored to each target. We dubbed this activity Operation FlashHole.
Our examination reveals that the earliest evidence of this new operation dates back to July 2025. This suggests the group began preparing for the campaign shortly after ending Operation SyncHole, which lasted at least four months. We identified a minimum of three organizations impacted by the campaign in South Korea’s software, construction, and wired communication equipment manufacturing sectors. These sectors differ from those affected by Operation SyncHole, indicating that the group has expanded its target scope over time.
After more than a year since the first observation of Operation SyncHole, we detected a suspicious execution chain originating from legitimate South Korean software. This chain mirrors the one from the previous operation; however, this time, the attacker abused CrossWeb EX instead of Cross EX, which was abused in Operation SyncHole. Both applications appear to be maintained by the same vendor, and both are related to financial security. CrossWeb EX is a financial security solution that is required to access widely used online banking and government websites. It encrypts communications between the user’s browser and the web server using public key infrastructure (PKI). This is not the first time Lazarus has abused this software. It was also used in 2021 to deploy the Racket downloader and again in 2022 and 2023. Although the exact method by which CrossWeb EX was abused remains unclear, we determined that the attack chain ultimately leads to the execution of the malware in memory.
We noted that the spawned process was running with a high integrity level. The parent process, INISAFECrossWebEXSvc.exe, originates from the installation bundle of INISAFE CrossWeb EX V3 version 3.4.1.2, released in 2023 after KrCERT’s public advisory.
As we already mentioned in our SyncHole blog post, this pattern closely mirrors the long‑standing strategy employed by the Lazarus Group to target South Korea. Since CrossWeb EX and similar software is mandatory for South Korean users and typically runs in the background to interact with the browser, it has been leveraged as a critical attack vector by the group. In 2025, a paper was presented at the USENIX Security Symposium that investigated vulnerabilities in South Korea’s mandatory security software and demonstrated how such software can unintentionally create a massive attack surface.
In July 2026, the South Korean government and several local security vendors also published a joint security advisory covering typical Lazarus attack techniques, including exploitation of financial security software. While this advisory overlaps with our findings from Operation FlashHole and Operation SyncHole, and AhnLab’s detailed analysis report Operation Double Barrel covers a wide range of recent Lazarus Group activities, we are conducting a more granular classification based on their TTPs. We will discuss this further in the attribution section.
Although we could not precisely determine what triggered the infection chain, our analysis uncovered a suspicious website hosted on GitHub Pages that is associated with the GitHub account used as the C2 channel. The GitHub account was created last September, and the initial version of the site was designed to showcase the résumé of a senior network appliance developer. In January, however, this site was replaced with another featuring an interior design showcase. The first site was likely accessed by an employee of a wired communication manufacturing company, while the second site likely affected a target in the construction sector.
The first site with the résumé had a photograph supposedly of a job seeker, but the lack of EXIF metadata and the unnatural texture of the image indicate that it was generated by AI. This suggests the Lazarus Group has incorporated AI into its long‑standing strategy, like other Korean‑speaking threat actors (1, 2). The group most likely also used AI to create the lure site: the job seeker’s name resembles the Korean version of “John Doe,” and the portfolio was populated with seemingly meaningless details and random companies. The generated site was then manually tailored to specific targets.
The websites contained embedded links that loaded an external JavaScript file via a script tag.
hxxps://javadevhouse.co[.]kr/ajax/libs/jquery/1.7.3/jquery.min.jshxxps://pythonapischool[.]com/api/detachBased on the analysis, we assess with medium-to-high confidence that the targets received phishing emails containing links to the malicious site hosted on GitHub Pages (using the domain <username>.github.io). The research results showed a high possibility that visiting the malicious site initiated an infection process involving CrossWeb EX software. This assessment aligns with Lazarus’s recent approach, as detailed in the joint advisory published by the South Korean government and security companies.
Following the initial compromise, the legitimate Windows binary fsquirt.exe was executed under the CrossWeb EX process and injected with shellcode containing a malicious DLL – TechHub malware. From our extensive and thorough examination, we identified several malicious payloads and reconstructed the complete infection chain. The infection chain is rather complex and reveals the Lazarus Group’s advanced operational techniques on targeted hosts. These techniques conceal their malicious payloads, intent and their sophisticated malware delivery framework. The latter was updated extensively compared to the previous campaign, despite the new operation starting less than a year later. Significantly, the execution chain below exists only in memory during the initial infiltration, highlighting the attackers’ considerable efforts to hide the initial compromise.
Following the initial compromise, the group sought to maintain persistence on the network by installing a pair of malware strains – TouchHub and TouchShift – leveraging DLL side‑loading under the name mscoree.dll. TouchHub was deployed by the first instance of TechHub. It then used DLL side-loading to launch TouchShift, which led to the in‑memory execution of another TechHub instance. After launching the second time, TechHub deployed another pair, ClientHub and LPEClient, rather than executing Cubridge directly. Only minimal traces of these files were found on disk; the remainder of the malicious code persisted exclusively in memory.
Since Cubridge remains only in memory at the initial compromise stage, we suspect the group designed this indirect, multistage chain to deliberately redeploy Cubridge after gaining persistence, as it serves as the most sophisticated orchestrator of the attack.
The full chain comprises advanced variants of the known Lazarus malware strains, including TechHub, Cubridge, TouchShift, LPEClient, and the newly identified TouchHub and ClientHub.
TechHub, a downloader that plays a central role in this attack, communicates with GitHub using a Personal Access Token (PAT). It serves as the initial payload, providing the top of the chain with sufficient functionality to profile compromised hosts and facilitate subsequent payloads.
This variant is a more advanced version of the malware named CLOUDBURST by Mandiant and NickelLoader by ESET. According to their reports, the earlier version communicated with a C2 server via HTTP(S) to fetch additional payloads. The latest iteration we found, however, communicates with GitHub instead and has updated command strings.
We identified three variants of TechHub in the chain: an in‑memory version, a simple DLL side‑loading version, and a DLL side‑loading version that uses a registered Windows service. Depending on which stage loads the malware, it contacts a private GitHub repository via the GitHub API using either hard‑coded credentials or credentials retrieved from its configuration file.
When TechHub loads, it creates a 4‑byte hexadecimal identifier (ID) in the range 0x1000–0xFFFF or reads one from the configuration file, enabling the attackers to distinguish between compromised hosts. TechHub then checks a GitHub issue by sending the request GET /issues?state=[open/closed] to determine whether any previous communication remains active and removes any traces of it if found. It then proceeds with the handshaking process.
1[ID] with the body “hel” using the POST /issues request, and sets its status to open.2[ID] value in its name. This file contains the RSA public key.1[ID], to the repository.During file exchange, filenames follow the pattern [1|2][ID][random-16-byte-key] throughout communication. The “2” prefix indicates delivery from the repository to TechHub, while “1” indicates delivery from TechHub to the repository. The random 16‑byte key in the filename is used for AES encryption or decryption of each file’s contents, employing either a hard‑coded IV or an updated IV.
After the key exchange is complete, TechHub reads a file with the prefix “2” once again and verifies that the delivered data equals “hel”. If the check passes, TechHub gathers extensive information from the infected host. This data is then encrypted and sent to the repository. After transmitting the device information, the process concludes by updating the body of the previously created issue from “hel” to “hey” using PATCH /issues/[issue number]. The malware is now fully prepared to receive commands from the repository.
TechHub supports four commands. The laeca command deploys a payload packaged in shellcode that reflectively loads the embedded payload directly into memory.
| Command | Description |
mqdrz |
Collect information about the device and its running processes |
laeca |
Directly invoke the received shellcode in memory |
aqvxp |
Terminate the current process |
rtcya |
Beaconing after finishing the handshake process |
Cubridge, deployed via TechHub on the compromised host, is capable of retrieving various payloads through multiple methods. It serves as the central orchestrator of the entire malware framework, supporting a range of plugins, modules, and tools. An earlier version of Cubridge was also disclosed in the reports covering the previous version of TechHub. In those reports, Mandiant identified it as SIDESHOW, and ESET identified one of its modules as LightlessCan.
To establish communication with the C2 server, Cubridge randomly selects one of the predefined C2 servers and constructs a dedicated C2 URL for every request, using the pattern [C2_URL]/[page1]/[page2]/[page3]. This is achieved by concatenating terms from predefined word lists. Our analysis identified a single hardcoded C2 server – hxxps://cubedesign[.]co[.]kr/news/AABBCC – associated with the examined instance that is configured to version 5.1. During URL generation, AABBCC is substituted with a null value. The page3 segment is assigned a randomly generated integer between 10000000 and 99999999. Consequently, each generated URL is designed to appear authentic and remain unique for each request.
The predefined list for page1 is shown below. TechHub randomly selects one item from the list.
economy, opinion, politics, national, international, medical, investment, sports, lifestyle, shopping, culture
The predefined word list for page2 is shown below.
article, list, story
This means the hardcoded URL can later be transformed, for example, into hxxps://cubedesign[.]co[.]kr/news/economy/article/12345678 by following the steps described above.
Authentication using the POST request with the C2 server requires three parameters in the form of key‑value pairs. Each key is randomly generated using a different predefined word dictionary, and the associated values consist of a randomly generated 8‑byte hexadecimal bot ID, a fixed authentication token (KW4Ofw982CNJjxd51AVqkGAop), and a randomly generated 16‑byte hexadecimal session ID.
Cubridge employs a more robust handshaking process than TechHub, combining the RSA and RC6 algorithms. Unlike TechHub, it skips the profiling step and proceeds directly to command and control after the handshake. During communication, the malware mimics browser requests, using X‑CSRF‑Token and X‑Requested‑With headers for authentication and the Upgrade‑Insecure‑Requests header to request additional data.
Cubridge contains extensive functionality, with a particular focus on loading subsequent‑stage payloads. The commands employ various techniques, such as DLL injection, reflective loading, and section‑mapping injection. The payloads may be delivered in various forms:
It is anticipated that the commands for plugins and shellcode will load identical types of plugins because both support a similarly formed exported function for subsequent activity. The shellcode can be generated using the open‑source sRDI tool to package a DLL‑style plugin. The capabilities of a single DLL are likely utilized to load a tool that works independently because when a single DLL is loaded, only its DllMain entry point and its parameters are accessible; no other exported functions are exposed.
| Command | Payload type | Description |
| 0 | – | Collect device info including the computer name, time zone, PID, and other similar details |
| 1 | Archive the specified file/directory using the legacy ZipCrypto algorithm and the hard‑coded password: xdkiTajAAxc3i/w[<881fnC!G*cb1Dit2sh.gAk/ |
|
| 2 | Create a file at the specified path | |
| 3 | Possibly plugin | Inject the provided DLL payload into the target process and load it reflectively using reflective DLL injection |
| 4 | Plugin | Reflectively load a plugin in DLL format |
| 5 | Retrieve the address of the specified exported function from the target plugin and run it with the provided parameters | |
| 6 | Retrieve all information about the loaded plugins | |
| 7 | Unload the specified plugin | |
| 8 | Shellcode | Inject the provided shellcode into the target process and load it using section mapping injection |
| 9 | Load the provided shellcode directly into memory | |
| 10 | Retrieve the address of the specified export function from the target shellcode (likely a plugin in shellcode form) and run it with the provided parameter | |
| 11 | Retrieve all information about the loaded shellcode | |
| 12 | Unload the specified shellcode | |
| 13 | – | Set the scheduled Cubridge execution time (in minutes) by updating a global variable |
| 14 | Set the scheduled Cubridge execution time (in minutes) by updating a global variable, while disabling monitoring by also updating another global variable | |
| 15 | Terminate in a controlled manner | |
| 16 | Get the configuration for Cubridge: retrieve the global flags, the number of C2 servers, the C2 addresses, etc. | |
| 17 | Update the global flags, the number of C2 servers, the C2 addresses, etc. | |
| 18 | Tool | Load a DLL reflectively with the specified parameter |
| 19 | Configure the parameters for loading a single DLL | |
| 20 | Unload the single DLL | |
| 21 | Module | Load the “action module” (ActionModule.dll) reflectively and invoke its AppinfoView export function |
| 22 | Load the “function module” (FunctionModule.dll) reflectively and invoke its PresentationFontConfig export function |
Commands 21 and 22 each load a different module. As their internal names imply, the action module manages basic file and process operations, while the function module implements Windows’ default commands. The action module covers commands 23–41, and the function module handles commands 42–79.
The action module handles system operation commands, file system interactions, and process behavior. It is invoked by passing the appropriate command and parameters to its AppinfoView export function. The module supports 19 commands, numbered 23 through 41. Execution results are first sent to Cubridge, which then forwards them to the C2 server.
| Command | Role |
| 23 | Get local disk space for each drive |
| 24 | Get information about the specified file or directory |
| 25 | Execute the provided command |
| 26 | Get information about the specified file or directory (similar to command 24) |
| 27 | Execute the provided command under the target process (PPID spoofing) |
| 28 | Execute the provided command under the target process within the provided session (PPID spoofing + session impersonation) |
| 29 | Get detailed information about processes |
| 30 | Terminate the provided process |
| 31 | Suspend all threads belonging to the specified process |
| 32 | Resume all threads belonging to the specified process |
| 33 | Permanently delete the file by overwriting its entire contents with the sequence: 0 → 1 → random bytes → 1 → 0 |
| 34 | Rename the provided file to :EFS (the alternate data stream area) and delete it using the native API SetFileInformationByHandle |
| 35 | Set the current working directory |
| 36 | Copy the specified file to the provided path |
| 37 | Delete the specified directory |
| 38 | Move the specified file to the provided path |
| 39 | Create the provided directory |
| 40 | Initiate a non‑blocking connection attempt to the specified IP address and port (possibly for port scanning) |
| 41 | Read the specified file |
The function module implements commands that emulate Windows’ built-in commands. Similar to the action module, its DllMain routine initializes all supported command functions, which are later accessed through the PresentationFontConfig export. Altogether, the module offers 38 commands, numbered from 42 to 79. While we believe this module is based on the previous LightlessCan, this is the first time we’ve seen it in the form of a separate module.
| Command | Role |
| 42 | Capture all displays and archive them using the legacy ZipCrypto algorithm with the hard‑coded password: xdkiTajAAxc3i/w[<881fnC!G*cb1Dit2sh.gAk/ |
| 43 | Synchronize the MAC (Modified, Accessed, and Created) times of the file provided in the second argument to match those of the file provided as the first argument |
| 44 | Get information about the specified directory |
| 45 | Get information about the specified drive |
| 46 | Inject the provided DLL payload into the target process |
| 47 | Unload the specified DLL from the specified process |
| 48 | Implementation of the ipconfig command |
| 49 | Implementation of the net command |
| 50 | Implementation of the netsh advfirewall firewall command |
| 51 | Implementation of the netstat command |
| 52 | Implementation of the ping -6 command |
| 53 | Implementation of the reg command |
| 54 | Implementation of the sc command |
| 55 | Implementation of the ping command |
| 56 | Implementation of the whoami command |
| 57 | Implementation of the nslookup command |
| 58 | Implementation of the schtasks command |
| 59 | Implementation of the systeminfo command |
| 60 | Implementation of the arp command |
| 61 | Call the CryptUnprotectData function to retrieve the AES key that DPAPI protects. Extract the key using the encrypted_key keyword from Chromium’s Local State file located at: %LOCALAPPDATA%\Google\Chrome\User Data\Local State |
| 62 | Not implemented |
| 63 | Not implemented |
| 64 | Read the specified file and decrypt it using an XOR operation with the key 0x59. Then extract the paths from the decrypted buffer and archive files and directories at these paths with the legacy ZipCrypto algorithm, using the hard‑coded password: xdkiTajAAxc3i/w[<881fnC!G*cb1Dit2sh.gAk/ |
| 65 ~ 79 | Not implemented |
Besides the modules, we also observed that the actor deployed various plugins and tools.
| Type of payload | Name | Description |
| Plugin | ADFinder (AdFinder.dll) |
Launches LDAP queries in an Active Directory environment, taking six arguments such as log file path, ADsPath, search filter, and attribute names |
| Plugin | FileCollector (Dll.dll) |
Recursively scans every subdirectory and file in the provided directory, gathering detailed information about each |
| Tool | Browser stealer | Can be injected into Chromium-based browsers, such as Google Chrome, Microsoft Edge, and Brave. Once injected, it extracts files and credentials from the victim’s browsers, including stored passwords, bookmarks, history, preferences, and cookies |
| Tool | Process collector | Iterates over all running processes, collecting each process’s ID, path, and command line |
During our analysis, we obtained a previously unknown malware sample from TechHub’s private GitHub repository, which served as a parent installer for TouchShift. We dubbed this malware TouchHub. Upon execution, it copies the legitimate printfilterpipelinesvc.exe to C:\Windows\System32\RasConv\ImeBroker.exe, registers it as a service, and places an embedded TouchShift payload named mscoree.dll in the same directory. Following creation, the malware synchronizes the MAC timestamps of C:\Windows\System32\drivers\monitor.sys with those of the newly written file, hindering forensic analysis.
It then goes through the service registration process by collecting up to 100 legitimate service names that are registered under the netsvcs svchost group in HKLM\SOFTWARE\Microsoft\Windows NT\CurrentVersion\Svchost. It randomly selects one of these names, appends two random alphabetic characters to form a new service name, and uses this name to create a service that runs the hard‑coded command line C:\Windows\System32\RasConv\ImeBroker.exe -TimeBroker with the description Microsoft Service. The newly created service is started immediately.
Overall, TouchHub creates three files in the designated directory to launch TouchShift with SYSTEM privileges.
| Path | Type | Description |
C:\Windows\System32\RasConv\ImeBroker.exe |
Executable file registered as a service | Copied from C:\Windows\System32\printfilterpipelinesvc.exe |
C:\Windows\System32\RasConv\mscoree.dll |
Side-loaded TouchShift payload | Dropped by TouchHub. It contains encrypted payloads and includes portions of a legitimate DLL’s contents, which significantly inflates its size |
C:\Windows\System32\RasConv\ActivationStore.dat |
TechHub’s configuration file | Dropped by TouchHub after extracting configuration values |
The version of TouchShift dropped by TouchHub is almost identical to the version described in Mandiant’s blog post, even sharing the same malicious export function, LockClrVersion. It takes the argument supplied by TouchHub and XORs it with a hard‑coded key. The resulting value is XORed once more with the executable’s filename, and this result is used as the AES key. All strings involved in this process (the argument, the XOR key, the filename) must be exactly 16 bytes long. If a string is shorter, it is padded with NULL bytes (\x00); if it is longer, it is truncated to 16 characters. For example, one of the string combinations in the obtained sample was:
-TimeBroker\x00\x00\x00\x00\x00 (padded with NULL)x809G736iC3f8Wp8ImeBroker.exe\x00\x00\x00 (padded with NULL)After deriving the key, the malware decrypts the embedded payload using AES‑CBC‑128 without padding. The decrypted data is shellcode that starts with a call instruction. It wraps the next‑stage payload – identified as the third version of TechHub (DLL side-loading with a registered service) – that reads the ActivationStore.dat file as an external configuration.
We also identified a new piece of malware stored in TechHub’s private repository, which we named ClientHub. It supports various commands formed using a bitmask. There are at least two versions of ClientHub: one that communicates with websites via HTTP(S) and one that interacts with the Dropbox API using credentials.
Depending on the version, its configuration is sourced from internal resources or the external configuration file C:\Program Files\Common Files\System\msadc\msadc.inc. The configuration comprises keys and IVs for the SNOW 1.0 algorithm, scheduled execution times, and C2 server addresses encrypted with the SNOW stream cipher. The SNOW cipher is a family of high‑speed stream ciphers used for secure data encryption in telecommunications and wireless networks. This is the first time it has been observed in the malware of the Lazarus Group.
To establish C2 communication, the malware initially generates a 32‑byte random array. It subsequently overwrites portions of this array with data collected from the compromised device. The resulting 32‑byte array comprises a blend of random bytes and relevant information. This array is later used as the key for the SNOW algorithm to decrypt data received from the C2 server. Finally, the key array is encrypted with a hard‑coded RSA public key and encoded in Base64.
| Offset | Size | Field value |
| 0 | 4 | Current process ID |
| 4 | 4 | First four bytes of the decrypted C2 server information. |
| 8 | 7 | Randomly generated bytes |
| 15 | 1 | Calculated flag value that indicates a state machine. |
| 16 | 8 | Current system time, represented as a FILETIME structure. |
| 24 | 8 | Randomly generated bytes |
The ciphertext is delivered to the C2 server via GET requests. Each request contains headers that are atypical for malware: Sec-CH-UA, Sec-CH-UA-Platform, Sec-CH-UA-Mobile, Sec-Fetch-Mode, and Sec-Fetch-Dest. These headers are normally used by legitimate Chromium‑based browsers and enable malware to imitate legitimate traffic and evade detection. The C2 server replies with commands in a custom header and message body.
struct header
{
int has_more_data // whether more body data remains
int body_checksum;// ROR13 checksum for the body data
int body_type; // specifies the body type
int unknown;
int body_length; // Length of the body data
int IV[2]; // Random IV used to encrypt the body data
};
The body_type field in the header determines how the subsequent payload is processed. This value functions as a bitmask, with each bit representing a distinct flag (e.g., 0x1, 0x2, 0x4, etc.). The resulting behavior also depends on whether the least‑significant bit (bit 0) is set: when the value is odd, the malware interprets the incoming message body as an additional payload that is subsequently loaded into memory. Conversely, when the value is even, the malware invokes the previously loaded payload.
The odd value supports four distinct loading methods based on the received message body and ensures that each method executes only once.
| Bitmask | Value in decimal | Description | Result sent to the C2 |
0x00000001 |
1 | DLL loading: load the received body reflectively along with the provided parameter | The payload’s image base |
0x00000011 |
3 | Plugin: load the received body reflectively, obtain the address of a function in the payload, and then invoke that function along with the provided parameter | The payload’s image base, the address of the invoked function, and the execution result |
0x00000101 |
5 | Plugin: load the received body reflectively, obtain the address of a function in the payload, but refrain from invoking it immediately | The payload’s image base, the address of the function |
0x00001011 |
11 | Plugin: execute the behavior associated with value 3, then unload immediately after invoking the plugin | – |
0x00010001 |
17 | DLL loading: load the received body reflectively with the provided parameter, maintaining stateful communication via a persistent interactive session using a shared buffer | The payload’s image base, the address of the interactive shared buffer, and the execution result |
The even value provides two distinct invocation methods for DLLs and plugins that have already been loaded and are associated with the odd‑value bitmask. The 2 (0x10) flag allows the payload previously loaded with the 1, 3, or 5 bitmask to be reused and invoked directly. The value 16 (0x10000) corresponds to the 17 (0x10001) flag in loading mode and uses the established interactive shared buffer to exchange data. All values are guaranteed to act independently.
| Bitmask | Value in decimal | Description | Result sent to the C2 |
0x00000010 |
2 | Invoke the previously loaded DLLs and plugins along with the provided parameter | The execution result |
0x00000100 |
4 | Not implemented | – |
0x00001000 |
8 | Unload the previously loaded DLLs and plugins | The execution result |
0x00010000 |
16 | Send the updated parameter to the payload loaded by the command with the value 17, and exchange data through the interactive session. This command also determines whether to retrieve the execution result or unload the payload | The execution result |
Taking into account the loading mechanism, we identified four plugins deployed to the target that work perfectly with ClientHub.
| Plugin | Description |
| File archiver | Archives the provided file using the legacy ZipCrypto algorithm (without password protection) and returns the compressed data |
| File collector | Searches for all files matching the provided search pattern and collects metadata including filename, MAC timestamps, file size, and attribute values |
| File cleaner | Overwrites the provided file with NULL bytes, renames it to a randomly generated filename of the same length, and then deletes it. If a directory with a search pattern is provided, it locates all matching files, renames each to a randomly generated name of identical length to its original name, and deletes them |
| Drive and session monitor | Monitors remote session changes and local drive changes for the provided duration (in 10-minute intervals) and returns the collected status information |
In addition to the plugins, ClientHub supports the loading of LPEClient malware and communication with it. We found that ClientHub’s body_type values 16 and 17 correspond to LPEClient’s C2 communication mechanism.
LPEClient is the only malware that was also observed in Operation SyncHole, indicating that the actor relies heavily on it for sophisticated victim profiling and payload delivery across multiple operations. LPEClient first appeared in 2019, and was discovered in 2020. Since then, the tool has been widely observed in the Dream Job and Cascade Hole campaigns that targeted South Korea. Recent research conducted by Check Point revealed that LPEClient was used to deploy the FudModule malware using a zero-day.
LPEClient has evolved continuously over time, but we discovered that it recently underwent a major operational revamp. It no longer contains the C2 server address itself; instead, it interacts with ClientHub via a shared buffer. We believe this change is intended to enhance concealment.
The previous version collected the computer name, memory status, CPU specifications, operating system details, version of the ntoskrnl.exe file, firmware table, antivirus name, domain name, user name, the integrity level of the current process, and a random byte sequence of 1,568 bytes. The newly updated LPEClient variant mostly collects the same information; however, it also introduces several changes.
ntoskrnl.exe file by querying the FileVersion value. Instead, depending on the specific build, it reads either the HKLM\SOFTWARE\Microsoft\Windows NT\CurrentVersion\UBR registry key or the SYSTEM_BUILD_VERSION_INFORMATION structure to retrieve the revision portion of the Windows build number. These values can be used to infer the system’s cumulative update or patch level.C:\Windows\System32\wbem\Repository\OBJECTS.DATA and searches for keywords such as AntiVirusProduct, companyName, and displayName to identify the installed products.SYSTEM_KERNEL_VA_SHADOW_INFORMATION structure for the Kernel VA Shadow mitigation status and the SYSTEM_SHADOW_STACK_INFORMATION structure for the Shadow Stack (CET) protection status.Additionally, it generates a 32‑byte random unique identifier by using the HighwayHash algorithm and an XOR operation with the current system time. The collected information, including the generated identifier, is compressed with the XPRESS Huffman algorithm using the maximum compression setting. The compressed data is then concatenated with the message ID 0xF07D6B34 and encrypted using GOST (also known as Magma), Russia’s national cryptographic standard that employs a DES‑like structure, before being sent to the ClientHub via a shared buffer. Initially, KrCERT described the algorithm as a custom DES‑like scheme. However, further analysis by us and Check Point confirmed that it is actually the GOST algorithm. The key is randomly generated by a proprietary key‑generation algorithm and prepended to the encrypted message.
The next request handles the key exchange by delivering the message ID 0xA39CF278 together with the generated unique identifier. The response is decrypted using the AES‑CBC‑256 algorithm. The SHA‑256 hash of the previously generated 1,568‑byte random value, which was originally sent to the C2 server during the collection phase, serves as the key for this decryption.
Through this process, LPEClient obtains a byte array comprising four 1,568‑byte blocks from the C2 response. Each block contains an ML‑KEM‑1024 public key, where ML‑KEM is a NIST‑standardized post‑quantum key encapsulation mechanism derived from CRYSTALS‑Kyber. LPEClient then generates four distinct pairs of shared keys and ciphertexts from these blocks, encrypts the ciphertexts with the GOST algorithm, and transmits them to the C2 server via ClientHub together with the message identifier 0xEF8C0D51 and the associated identifier. Now that the preparation phase for receiving payloads is complete, the malware is ready to receive payloads forwarded by ClientHub from the C2 server, along with the necessary parameters. The use of post-quantum cryptography shows that the group intends to hide subsequent payloads.
The response to the 0xEF8C0D51 message is decrypted with the Threefish algorithm using a 128-byte key, composed of the four distinct shared keys. Threefish is a tweakable block cipher that accepts a ‘tweak’ value alongside the key and the message. The concept of a tweak is similar to that of a nonce or initialization vector, which are used in different types of ciphers. In LPEClient communication, the tweak for the decryption is derived by XORing the unique identifier with 165 (0xA5). The first four bytes of the decrypted message must specify the parameter’s length, followed by the parameter itself and then the payload. The payload must be larger than 4 KB and start with the characters 'MZ', which indicates that the decrypted payload is an executable file. The payload is then reflectively loaded into memory. After successful loading, LPEClient sends the message ID 0xCB790A25 to the C2 server.
Before loading the acquired payload, LPEClient takes measures to bypass security products. Instead of invoking VirtualProtect directly, the malware uses the identified HeapPageAllocator::ProtectPages in jscript9.dll to modify the memory page protection of the MD4Update function. The beginning of the function is then overwritten with a hard‑coded opcode sequence that serves as a syscall stub with the required arguments. LPEClient then uses the syscall stub to disable a user‑mode syscall instrumentation hook.
We identified the final payload that was ultimately loaded as Cubridge. The overall communication process is as follows.
Throughout the engagement, we identified a variety of payloads deployed by TechHub, Cubridge, and ClientHub. These payloads have been categorized as tools, plugins, and modules that constitute the group’s modular malware framework. While we have not yet ascertained which payloads are deployed under specific conditions, the evidence suggests that the Lazarus Group’s toolkit is becoming increasingly sophisticated and segmented into specialized components rather than a single comprehensive backdoor. We also believe that TechHub and Cubridge may share similar tools.
| Deployed via | Type of payload | Family |
| TechHub/Cubridge | Tool | Process collector, Browser stealer |
| Cubridge | Module | Action module, Function module |
| Cubridge | Plugin | ADFinder, FileCollector |
| ClientHub | Plugin | File archiver, File collector, File cleaner, Drive/session monitor |
These modularizations are not confined to the instances within this campaign. As previously noted, similar patterns have been identified in CookiePlus, MISTPEN, SIGNBT, and IMETHOD. Note that we have reclassified the ThreatNeedle variant used in Operation SyncHole as the latest version of IMETHOD, the predecessor of ThreatNeedle in use since at least 2016.
Based on the information we obtained from the TechHub malware, we identified at least three primary repositories used as the C2 server and one fallback repository. The earliest evidence indicates that the group has been leveraging GitHub as a C2 server since at least July 2025. We suspect that all the accounts were created using hijacked email accounts, and disguised as normal repositories by copying or creating normal projects to avoid suspicion.
For the Cubridge and ClientHub C2 servers, the Lazarus Group employed only a minimal number of compromised yet legitimate South Korean media and interior design websites. Later, we observed that a broader range of compromised legitimate sites across various industries were also exploited. In addition, one ClientHub sample that we detected used Dropbox as a C2 channel.
We have identified at least three firms from the software, construction, and wired communication equipment industries in South Korea that were targeted by Operation FlashHole. As with the previous operation, however, we remain confident that a considerably larger number of organizations across a broader spectrum of industries have been affected.
The software sector was the only sector targeted in both the SyncHole and FlashHole campaigns. This suggests the actor is eager to compromise the sector, steal source code, and exploit vulnerabilities for further attacks.
Operation FlashHole is the latest wave in the broader Cascade Hole campaign, which involves the use of South Korean software as a potential entry point to deliver malware targeting the country. Although the malware chain has advanced significantly since last year, we assess with medium-to-high confidence that the same actor is responsible for both the SyncHole and FlashHole operations based on the initial vector, targets, multi‑stage chain, and technical and operational improvements. The use of LPEClient in particular is a strong indicator supporting this assessment.
The malware strains used in the attack are historically linked to the toolsets observed in the Lazarus Group’s notorious Dream Job campaign. Earlier versions of TechHub (also known as CLOUDBURST and NickelLoader), Cubridge (also known as SIDESHOW and LightlessCan), and TouchShift were all observed in that campaign, especially between 2022 and 2023.
We also discovered that both CookiePlus and ClientHub have significant overlaps in class name, configuration path, and plugins. Based on these similarities, we assess with medium‑high confidence that ClientHub is an advanced version of CookiePlus.
Since July, around the time Operation SyncHole began winding down, we have also observed several notable attacks against South Korea employing the COPPERHEDGE backdoor and targeting various South Korean organizations. Interestingly, the start times of these activities align with the earliest evidence we have identified for Operation FlashHole. Although the backdoor was part of the second phase of Operation SyncHole, it has been operating independently with its custom loader since then. These incidents featured malware chains and tools that were distinct from those used in Operation SyncHole and FlashHole.
As AhnLab noted in their report, the same backdoor was likely observed in atypical activity, specifically the Gunra ransomware infection. Our investigation further revealed that one instance of a backdoor infection ultimately resulted in the exfiltration of data to a dark web leak site, which clearly differed from Gunra’s. The site appears to have been crafted exclusively for this activity. In summary, unlike other attacks, the backdoor was used in conjunction with both ransomware and data exfiltration.
Another noteworthy point is that the recent Dream Job campaign employs an updated malware chain that, since around 2024, has primarily involved MISTPEN and ForestTiger rather than the earlier arsenal that included tools such as TechHub and Cubridge. However, the updated versions of this older malware have now re-emerged as part of Operation FlashHole. Considering these changes and all aspects of each attack’s TTPs, we have organized a classification for each attack.
Our analysis shows that the Lazarus Group begins preparing for its next operation shortly after completing the previous one, ultimately deploying an enhanced malware chain by refining existing tools. The group continues to use the advanced version of LPEClient for profiling and payload delivery, indicating that the tool is meticulously managed and well maintained. Ironically, the group seems to have adopted more secure post-quantum cryptography faster than many legitimate security products. These observations suggest the involvement of a dedicated developer, with others orchestrating comprehensive attack scenarios against newly targeted software.
We anticipated that specialized attacks targeting South Korea would persist. However, we did not foresee multiple attack campaigns being executed simultaneously, each leveraging different types of software and tools. Notably, the COPPERHEDGE cluster appears to be involved in monetizing the attacks, while Operation FlashHole is focused on espionage. We are closely monitoring these changes to understand their motivations and ultimate goals.
In October 2025, the South Korean government unveiled a comprehensive cybersecurity plan that will phase out the mandatory installation of security software for users beginning in 2026. We estimate that operations exploiting this software will remain highly active for some time, maximizing efficiency, before the software is fully eliminated or mitigated.
Kaspersky products detect the exploits and malware used in this attack with the following verdicts: MEM:Trojan.Win64.Shellcode.gen, Trojan.Win64.DLLhijack.*, Trojan.Win64.Lazarus.*.
TouchShift
ec84d6cb2ae7974767aedac246b50a3e mscoree.dll
a28cba214058fcae2883d8cffc883abd mscoree.dll
c105d6b16f544582772de0159f24c00a mscoree.dll
2f8475a90a25624ed02f1d18d4e6d65d mscoree.dll
676fabe30a28b53925fba98e34b35986 mscoree.dll
b4a7eff35f048f06fb0a2d7631f23a7d mscoree.dll
ClientHub Loader
ff07641dc56914dd90ee0bd7404d7ad7 liblzma.dll
C:\ProgramData\Package.txt
C:\ProgramData\RasConv\mscoree.dll
C:\ProgramData\Apple\mscoree.dll
C:\ProgramData\ssh\mscoree.dll
C:\ProgramData\qorestor\mscoree.dll
C:\ProgramData\Dell\mscoree.dll
C:\ProgramData\Dell\Dell1.tmp
C:\ProgramData\Dell\Dell3.tmp
C:\Windows\System32\RasConv\mscoree.dll
C:\Windows\System32\RasConv\ActivationStore.dat
C:\Windows\System32\DrvConh\mscoree.dll
C:\Windows\System32\DrvConh\ActivationStore.dat
C:\Program Files\Common Files\System\msadc\msadc.inc
C:\ProgramData\desktops.ini
javadevhouse.co[.]kr
pythonapischool[.]com
hxxps://cubedesign[.]co[.]kr/news C2 of Cubridge
hxxps://cubedesign[.]co[.]kr/mobile/fashion C2 of Cubridge
hxxps://fp-news[.]co[.]kr/shop/cart C2 of Cubridge
hxxps://k-wbc[.]co[.]kr/skin/social/social_view.php C2 of ClientHub
hxxps://rcsh[.]co[.]kr/modules/bbs/tiles/bbs_div/inputForm.php C2 of ClientHub
hxxps://www[.]ksog[.]org/insert_file/handle.php C2 of ClientHub
Source: Securelist (Kaspersky GReAT) · 2026-10-21
ProSoft RLX-IFH24E v2.2.44 – Unsigned Firmware Upgrade Package Executed as Root
Source: Exploit-DB · 2026-10-21