Certificates both protect TLS connections and digitally sign applications, and forged ones turn up in real-world attacks from time to time. We’ve seen forged or stolen certificates abused by the DarkHotel APT and the Flame malware, and in 2011 we saw attack attempts after the certificate authority Comodo was compromised. Pulling off this trick usually takes serious expertise. But attacking eMudhra certificates in 2026 doesn’t take much effort at all. An attacker just has to guess a number from 1 to 255. Private keys for intermediate certificate authorities are normally gigantic numbers. But in this case, eight of them were the following: 4, 56, 66, 115, 155, 156, 230, and 237. They could be guessed using the public keys (available in public certificates) in under a second. As a result, a hypothetical attacker could issue certificates for anything by signing them with one of the compromised private keys.

Six of these keys were meant for issuing TLS certificates, and the other two were for code signing. All eight intermediate certificate authorities (CAs) were also cross-signed by the Sectigo CA. This means clients with different trust chains could trust a forged certificate.

The major browsers have already blocked the dangerous certificate chains. But IT and security teams still need to assess and remediate the risk in many other systems across their organizations. Scripts for scheduled data-processing, corporate NGFWs, monitoring servers, applications with built-in certificate stores, and devices that don’t get regular updates may accept forged certificates and be vulnerable to man-in-the-middle (MitM) attacks. The keys needed for this are already built into publicly available interception tools.

Timeline of the eMudhra certificate authority incident

The problematic keys came from a batch of 24 intermediate CAs that eMudhra created on April 30, 2025. Instead of cryptographically random values for a 384-bit elliptic curve, eight of the keys turned out to be small numbers. According to eMudhra’s own description, a “key wrap/unwrap step” during key generation created a second, weak set of keys. Because keys are created and stored in a dedicated device called a hardware security module (HSM), a weak key is hard to notice on its own. It’s still unclear what error caused the keys to be generated twice and the weak set to be used; the investigation is ongoing.

In May 2025, the Sectigo CA signed all eight intermediate certificates. Then, on October 17, 2026, an independent researcher notified the security teams at Mozilla, Google, and Apple, as well as the CA itself, that the keys were recoverable. On October 20, Mozilla publicly disclosed the incident. This means that for almost a year and a half the keys could have been recovered and certificates forged.

On October 22, eMudhra announced that it was exiting the global SSL/TLS certificate business.

What an attacker can do

Using the vulnerable intermediate CAs, an attacker can sign a forged certificate for someone else’s domain. Clients that still trust that chain and have no other safeguards will take the forgery for the real server.

A certificate alone isn’t enough to intercept HTTPS traffic. The attacker also needs a way to tamper with the victim’s traffic or redirect the connection. That’s possible, for example, in a compromised office network, on a Wi-Fi access point the attacker controls, or by interfering with routing and DNS. And all of this does happen in the wild, as the DarkHotel attacks, among others, have shown.

There’s one more danger: two of the keys can be used for code signing. In theory, that would let an attacker deliver malware that appears to come from a trusted vendor and doesn’t trigger scary OS warnings during installation.

Was it exploited?

Experts from various companies who analyzed the after-effects of the incident haven’t found any malicious attacks that used these certificates. eMudhra and CERT-In have also reported finding no abuse. The Chrome team found no certificates from the six CAs in public Certificate Transparency logs.

This means that systems where browsers check certificates through Certificate Transparency (CT) were most likely not attacked. But many devices and applications — especially servers and IoT devices, don’t check CT at all, so we can’t say anything about them. Today, malicious actors no longer need to write their own hacking tools to pull off an attack like this. Version 12.3 of mitmproxy — a popular tool among security researchers — already has built-in support for compromised keys.

Where the risk has been eliminated, and where that isn’t guaranteed

Major platforms quickly revoked the compromised certificates. As early as October 17, Chrome did so through CRLSets, and Firefox — through OneCRL. On October 18, eMudhra itself revoked the certificates, citing “CA Compromise”. Apple took action on October 19, and the Sectigo CA also revoked the cross-signed copies. Microsoft revoked the certificates on October 20. Depending on the settings of a specific application and OS, revocation may have taken effect even without an application update, since blocklists are often updated separately.

At the same time, a more radical measure is under way: withdrawing trust from the root CA. Chrome has announced the planned removal of “emSign ECC Root CA – G3” from the browser. Certificates issued under the “emSign Root CA – G1” root, and the root itself, aren’t affected. According to eMudhra’s estimate, about 30 000 certificates will need to be migrated.

But certificate revocation only works where the client can find out about the revocation to then be able to actually act upon it. Many applications check the signature, server name, and certificate validity period, but don’t retrieve or update blocklists. Here are the typical cases:

Outdated and LTS systems. LTS (long-term support) status alone doesn’t mean a system is vulnerable. By definition, a system with this status receives support. But old containers, frozen OS images, and systems that are no longer updated can keep trusting revoked CAs for a long time. It all depends on updates to ca-certificates and TLS libraries, and the settings of the specific application.

Automated systems and servers. On emudhra.we-have-a-problem.com — a site created by enthusiasts where you can check any client software for misplaced trust — curl and Zabbix dominate the list of the most vulnerable systems. For HTTP checks, Zabbix usually uses libcurl and the certificate store configured for it. Similar behavior is also documented in the built-in curl in macOS. At the OS level and in Safari, the certificate is revoked, but curl reads a plain /etc/ssl/cert.pem file, and that’s precisely where the fix has to be made. This is a good example: even when system-level trust and revocation mechanisms work, individual applications — including ones that ship with the OS by default — can remain vulnerable.

Python, Ruby, Go, Java, and containers. An application may use its own set of root CAs, which isn’t updated along with the OS. Endor Labs found more than 25 popular packages that contain the affected root.

Slack, GitHub Desktop, and other apps built on the Electron framework. These apps ship with their own Electron/Chromium, so updating a separately installed Chrome doesn’t update Slack. The certificate revocations are already in the new Electron version, but now every developer has to rebuild and distribute their app, and every user has to install the update. That said, not every Electron app is necessarily vulnerable. The outcome depends on the version, how the app updates its blocklists, and which network stack it uses.

Mobile browsers and IoT devices. Mobile Chrome, Firefox, and Safari get certificate revocation data as quickly as their desktop counterparts do. With the stock browsers from smartphone makers, this isn’t the case. In a published test, Samsung Browser 31.0.0.64 accepted all six test chains from emSign while rejecting the ones from Sectigo. For HarmonyOS 6 and 7, researchers found the affected CAs in Huawei’s published list of root CAs, and those CAs can’t be revoked manually.

For unsupported devices, home appliances, and old firmware, a certificate store update may never be released. In those cases, the problem could linger for years.

Impact on TLS inspection in a corporate network

When an NGFW or web gateway inspects encrypted traffic, it maintains two connections: one with the client and the other with the external server. The client receives a certificate signed by the corporate CA, while the gateway itself verifies the authenticity of the external server.

If the gateway accepts a forged eMudhra certificate, even an updated browser on an employee’s computer won’t see the dangerous chain. Instead, it will receive the familiar corporate certificate. In this scenario, the security tool itself hides the problem from the client. That said, carrying out such an attack would also require intercepting traffic.

To fix the validation policy and certificate lists on the inspection device itself, follow the vendor’s instructions — if the vendor has published any, that is.

At Cisco, the status of the issue is documented in detail for all products. Most of them are still listed as “under investigation”, but mitigation measures are recommended for vulnerable devices.

Sophos and Check Point promise device software updates and, in the meantime, advise removing the certificates manually. Neither company has published a security advisory, but employees of each posted recommendations on its support forum.

For Fortinet devices, instructions for checking and removing emSign certificates can be found here. Palo Alto offered only general advice instead of specifics for its own products.

Of course, a properly configured gateway can indeed temporarily protect outdated client devices that trust the dangerous certificates.

To check specific devices, services, containers, and virtual machines, you can use a dedicated website. One possible scenario for proactively hunting for threats that exploit or have previously exploited weak keys is described here.

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.

Operation FlashHole attack flow during initial compromise

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.

Background

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.

Initial infection vector

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.

Appearance of the malicious websites

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.

Suspected use of an AI-generated image on the résumé site

The websites contained embedded links that loaded an external JavaScript file via a script tag.

• Malicious link embedded in the résumé site: hxxps://javadevhouse.co[.]kr/ajax/libs/jquery/1.7.3/jquery.min.js
• Malicious link embedded in interior design site: hxxps://pythonapischool[.]com/api/detach

Based 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.

Full infection chain

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.

Initial infection chain

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.

Expanded infection chain after gaining persistence

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.

Malware set

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 – the start of the chain

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. It creates a new issue titled 1[ID] with the body “hel” using the POST /issues request, and sets its status to open.
2. It then retrieves a file from the repository containing the 2[ID] value in its name. This file contains the RSA public key.
3. It generates a random 16‑byte XOR key, encrypts it with the provided RSA public key, and uploads the result, prefixed with 1[ID], to the repository.
4. The hard‑coded IV is XORed with the generated 16‑byte key and then used after the handshake.

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.

Cubridge – the framework orchestrator

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’s communication sequence

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:

• Plugins – reusable extensions that add functionality as needed and can be invoked at any time (in shellcode and DLL form);
• Tools (in DLL form) – independent utilities that perform one-off tasks;
• Modules – components that are loaded once and remain active providing an extended set of functionalities.

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.

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.

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.

Besides the modules, we also observed that the actor deployed various plugins and tools.

TouchHub installs a service for TouchShift

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.

TouchShift, a prevalent loader employed across multiple infection chains

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:

• Argument: -TimeBroker\x00\x00\x00\x00\x00 (padded with NULL)
• Hard-coded XOR key: x809G736iC3f8Wp8
• Executable filename: ImeBroker.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.

ClientHub

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.

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.

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.

Taking into account the loading mechanism, we identified four plugins deployed to the target that work perfectly with ClientHub.

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

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.

Timeline of LPEClient

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.

• It does not collect the version of the 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.
• To collect information about installed antivirus products, it switched from querying a WQL command to reading the WMI repository file directly. It now reads C:\Windows\System32\wbem\Repository\OBJECTS.DATA and searches for keywords such as AntiVirusProduct, companyName, and displayName to identify the installed products.
• It also collects low‑level Windows security mitigation states. To achieve this, it queries the 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.

Data relay flow between LPEClient and C2 via ClientHub

Comparison of plugins and modules

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.

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.

Infrastructure

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.

Victims

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.

Attribution and links to other campaigns

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.

Data leakage site linked to the COPPERHEDGE backdoor on the dark web

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.

Overlaps between the recent attacks by Lazarus Group

Conclusion

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.*.

Indicators of compromise

File hashes

TouchShift
ec84d6cb2ae7974767aedac246b50a3e             mscoree.dll
a28cba214058fcae2883d8cffc883abd                mscoree.dll
c105d6b16f544582772de0159f24c00a               mscoree.dll
2f8475a90a25624ed02f1d18d4e6d65d              mscoree.dll
676fabe30a28b53925fba98e34b35986              mscoree.dll
b4a7eff35f048f06fb0a2d7631f23a7d                  mscoree.dll

ClientHub Loader
ff07641dc56914dd90ee0bd7404d7ad7               liblzma.dll

File paths

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

C2 servers

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

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.

Operation FlashHole attack flow during initial compromise

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.

Background

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.

Initial infection vector

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.

Appearance of the malicious websites

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.

Suspected use of an AI-generated image on the résumé site

The websites contained embedded links that loaded an external JavaScript file via a script tag.

• Malicious link embedded in the résumé site: hxxps://javadevhouse.co[.]kr/ajax/libs/jquery/1.7.3/jquery.min.js
• Malicious link embedded in interior design site: hxxps://pythonapischool[.]com/api/detach

Based 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.

Full infection chain

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.

Initial infection chain

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.

Expanded infection chain after gaining persistence

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.

Malware set

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 – the start of the chain

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. It creates a new issue titled 1[ID] with the body “hel” using the POST /issues request, and sets its status to open.
2. It then retrieves a file from the repository containing the 2[ID] value in its name. This file contains the RSA public key.
3. It generates a random 16‑byte XOR key, encrypts it with the provided RSA public key, and uploads the result, prefixed with 1[ID], to the repository.
4. The hard‑coded IV is XORed with the generated 16‑byte key and then used after the handshake.

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.

Cubridge – the framework orchestrator

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’s communication sequence

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:

• Plugins – reusable extensions that add functionality as needed and can be invoked at any time (in shellcode and DLL form);
• Tools (in DLL form) – independent utilities that perform one-off tasks;
• Modules – components that are loaded once and remain active providing an extended set of functionalities.

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.

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.

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.

Besides the modules, we also observed that the actor deployed various plugins and tools.

TouchHub installs a service for TouchShift

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.

TouchShift, a prevalent loader employed across multiple infection chains

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:

• Argument: -TimeBroker\x00\x00\x00\x00\x00 (padded with NULL)
• Hard-coded XOR key: x809G736iC3f8Wp8
• Executable filename: ImeBroker.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.

ClientHub

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.

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.

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.

Taking into account the loading mechanism, we identified four plugins deployed to the target that work perfectly with ClientHub.

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

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.

Timeline of LPEClient

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.

• It does not collect the version of the 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.
• To collect information about installed antivirus products, it switched from querying a WQL command to reading the WMI repository file directly. It now reads C:\Windows\System32\wbem\Repository\OBJECTS.DATA and searches for keywords such as AntiVirusProduct, companyName, and displayName to identify the installed products.
• It also collects low‑level Windows security mitigation states. To achieve this, it queries the 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.

Data relay flow between LPEClient and C2 via ClientHub

Comparison of plugins and modules

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.

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.

Infrastructure

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.

Victims

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.

Attribution and links to other campaigns

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.

Data leakage site linked to the COPPERHEDGE backdoor on the dark web

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.

Overlaps between the recent attacks by Lazarus Group

Conclusion

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.*.

Indicators of compromise

File hashes

TouchShift
ec84d6cb2ae7974767aedac246b50a3e             mscoree.dll
a28cba214058fcae2883d8cffc883abd                mscoree.dll
c105d6b16f544582772de0159f24c00a               mscoree.dll
2f8475a90a25624ed02f1d18d4e6d65d              mscoree.dll
676fabe30a28b53925fba98e34b35986              mscoree.dll
b4a7eff35f048f06fb0a2d7631f23a7d                  mscoree.dll

ClientHub Loader
ff07641dc56914dd90ee0bd7404d7ad7               liblzma.dll

File paths

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

C2 servers

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

This one is from 1809, written by Napoleon’s nephew.

ArsTechnica is reporting on a “new” attack against RSA, one that bypasses factoring.

First, this attack isn’t new. The original research is from 2007. What is new is the implementation.

Second, it is a forgery attack. It allows an attacker to forge digital signatures. It does not recover the private key from the public key.

Third, the attack only works against pure signatures. That is, signatures without any formatting or padding. This is not generally how we use RSA in practice.

Fourth, speed is all relative. This is not a polynomial-time algorithm; it’s a subexponential-time algorithm. But it is somewhat faster than factoring. The authors were able to forge messages for 1024-bit RSA with 1380 CPU core-years (over five real-world months).

The authors have a webpage that explains the context much better than the article. And here’s the paper.

EDITED TO ADD: Slashdot thread.

This is pretty amazing:

However, the most astonishing thing about this break is that the GPT­6 Astra did it entirely on its own. Carter Leffer only directed GPT­6 Astra to see if it could break any of the unbroken Enigma messages published on the Crypto Cellar Research web page. After analysing the unbroken messages on the website, it decided that the most promising message was Nr. 172, MVUEH and it also quickly suspected that the plaintext of Nr. 173, SIPVX, might be related to the plaintext of the unbroken MVUEH message. After trying many different approaches, GPT­6 Astra focused on using the repeated place name ROSENOW ROSENOW as a crib. After developing the necessary Python and C++ software for an Enigma simulator and an Enigma Bombe, GPT­6 Astra started a thorough break with the ROSENOW crib, which in the end resulted in the correct key and plaintext for the MVUEH message being found.

We are still analysing the GPT­6 Astra logs to see exactly how it executed the break. And we are discovering amazing details.

More details at the link.

By Yogesh Ranade from Palo Alto Networks, and Senthil Ramakrishnan from AT&T

The digital world is currently navigating a dual-speed revolution. Acceleration of AI and hyperconnectivity is unlocking unprecedented economic value. The silent but rapid progress of quantum computing is fundamentally threatening the cryptographic foundation upon which that value is built.

As leaders in global networking and cybersecurity, Palo Alto Networks and AT&T Business launched Secure Connectivity solutions for Business Customers. We recognize that quantum-readiness is no longer a distant milestone; it is now a strategic imperative. With threatening data longevity and Trust Now, Forge Later targeting digital identities, the risks are already looming. 

By integrating Prisma SD-WAN’s cryptographic innovation with AT&T’s global network, Palo Alto Networks and AT&T Business are proud to deliver the Quantum-Resilient SASE Fabric.

The Quantum Shift Towards Building Resilience for Tomorrow’s Reality

For over 30 years, the difficulty of mathematics has been our primary defense. Classical algorithms, like RSA and Diffie-Hellman, provided the shield for our global economy because they were computationally impossible for classical machines to solve. However, quantum computing fundamentally changes this landscape by providing an exponential speed-up. By leveraging Shor’s Algorithm, quantum computers can break these classical cryptographic foundations, turning a decryption process that would take a classic supercomputer millennia into a task of mere hours.

Neutralizing the Quantum Crisis

Palo Alto Networks is embedding Post-Quantum Cryptography (PQC) as a native pillar of the Prisma SASE fabric. We are moving beyond the forklift-upgrade model to a software-defined, standards-based foundation, which is built on strict separation of management and data plane components:

• Universal Control Plane Hardening (TLS 1.3): We have transitioned all control plane traffic to TLS 1.3 (Transport Layer Security 1.3), the global gold standard for Internet encryption. This secures the "brain" of the network (where routing configurations and security policies are managed), making it immune to quantum-enabled impersonation and credential theft.
• PQC-Hardened Data Plane (IETF Standards): We are operationalizing PQC across the entire fabric by adopting official standards published by the Internet Engineering Task Force (IETF), specifically RFC 9370, 9242, and 8784. In plain terms, these standards allow us to use "hybrid key exchanges." This means we wrap your data in two layers of protection at once: a classical mathematical shield for immediate compatibility, and a quantum-resistant shield to protect against future decryption threats, all without causing packet fragmentation or network slowdowns.
• Logs and Telemetry Plane: All network telemetry and metadata (the automated operational logs and traffic pattern data generated by the network, rather than the actual content of your business files) are encrypted in transit via TLS 1.3. This architecture guarantees that even this secondary network metadata is geofenced to your chosen region with no cross-region aggregation, satisfying the most stringent data residency mandates.
• Crypto-Agility as a Standard: "Crypto-agility" is natively built into our systems, which means the software is designed to adopt new mathematical algorithms. As the National Institute of Standards and Technology (NIST) refines its guidelines, our systems can be upgraded seamlessly via simple, automated cloud updates without requiring expensive hardware replacements to ensure our customers’ security posture.
• Secure Boot Support: Palo Alto Networks Prisma SD-WAN ION hardware supports Secure Boot to ensure that only cryptographically signed bootloaders, kernels, and trusted applications are executed during the boot process. This establishes a chain of trust from the BIOS firmware to the operating system, preventing the execution of unauthorized or tampered software. ION hardware appliances ship with an integrated, dedicated Trusted Platform Module (TPM), which provides hardware-level root-of-trust by securely storing cryptographic keys, certificates, and sensitive data to prevent unauthorized physical tampering and ensure secure device authentication. The OS/software layers use PQC algorithms to negotiate and secure the management, control plane and data plane tunnels. This ensures quantum readiness without requiring an immediate, widespread rip-and-replace of physical branch hardware.

The AT&T Perspective Views Security at Global Scale

From the perspective of a global leader like AT&T, PQC is an operational mandate. Providing connectivity to the world’s most regulated industries means that security cannot be bolted on. Security must be an inherent property of the transport layer and the connectivity infrastructure itself.

Turning Complexity into a Strategic Advantage

Managing a global footprint that spans across 5G, fiber, and legacy underlays requires an institutional expertise that few can match. For AT&T, the move to a more secure quantum-ready fabric with Dynamic Defense is about providing security where it matters most: the network. Our customers shouldn't have to worry about whether their data is traveling over an MPLS circuit or the public internet.

Through this collaboration, AT&T expands the delivery of Dynamic Defense:

• Cross-Underlay Consistency: We enable PQC protection to be applied uniformly across all transport mediums, eliminating the "weak links" that often exist in hybrid environments where data moves between private and public circuits.
• Automated PQC Policy Orchestration: New branch locations are seamlessly integrated into the quantum-ready fabric through automated policy distribution. The moment a device is activated via zero touch provisioning, the branch is enabled to be protected against HNDL threats from the first packet without requiring manual site-by-site intervention.
• Compliance: With mandates like NIS2/DORA in Europe and NORA/CNSA 2.0 in the U.S., our clients face a closing window for compliance. AT&T provides the verifiable chain of trust required to prove "Quantum Readiness" across the entire circuit path, ensuring your fabric is audit-ready and compliant with global standards.

The Power of the Post-Quantum Secure Fabric

The true value of this relationship lies in the synergy between the network and the security stack. By combining our strengths, we have built a solution that is significantly more resilient than the sum of its parts.

The SPI Advantage Is Performance Without Compromise

Through Service Provider Interconnect (SPI), Palo Alto Networks' security platforms natively integrate with AT&T’s private network core to deliver a seamless quantum-safe on-ramp. This means business traffic can connect directly to a secure AT&T network without having to build slow, complex software tunnels over the public internet, preserving high performance while delivering next-generation encryption. Historically, high-level encryption meant a "performance tax" on latency and throughput. Our combined architecture allows quantum-safe traffic to flow over AT&T’s network backbone, enabling organizations to modernize their security without sacrificing the user experience.

Securing the Decentralized Perimeter (The Branch as the Edge)

In today’s highly distributed business landscape, the traditional corporate "headquarters" is no longer the center of gravity. The network perimeter has shifted to the branch (decentralized edge locations like retail storefronts, remote clinics, regional bank offices, and warehouse hubs) and the individual 5G-connected devices employees use. Securing these remote, local edge points is critical because they represent the primary gateway where sensitive company data first enters the network. 

By utilizing AT&T’s leadership in WAN, 5G and cellular technologies, we leverage Hybrid Public Key Infrastructure (PKI) to secure these edge locations. Hybrid PKI is a digital identity framework that issues dual security credentials to every device: one "classical" identity to ensure compatibility with existing networks today, and one "quantum-resistant" identity. This double-verification guarantees that a cellular-connected remote branch or a mobile site is just as immune to quantum decryption or identity spoofing as a fortified corporate data center.

The Path Forward Is a Vision for Long-Term Trust

The transition to a quantum-ready future is a marathon, not a sprint, and the first steps must be taken now. Palo Alto Networks and AT&T Business are offering a clear, practical path to quantum resilience.

We are delivering more than a simple software update as we prepare customers for the next generation of digital commerce. Together, we are designing our network to help ensure the data of today remains protected against the threats of tomorrow, securing the digital integrity of every enterprise we serve.

As we redefine the boundaries of security in connectivity, we invite you to join us in helping secure your organization’s digital future. Contact your or Palo Alto Networks account representative today to begin a strategic Quantum-Readiness Assessment and experience the power of the Quantum-Resilient SASE Fabric.

The post Palo Alto Networks and AT&T - Delivering Quantum-Resilient SASE Fabric appeared first on Palo Alto Networks Blog.

France is accelerating its transition to post-quantum encryption:

France’s cybersecurity agency ANSSI said on Tuesday it would stop certifying security products that lack quantum-resistant encryption, a move that will force government bodies and critical operators to shift away from older systems.

Samih Souissi, ANSSI’s chief of staff, said at the France Quantum conference that the agency would halt such certifications from 2027, and that businesses should be buying only quantum-safe products by 2030.

ANSSI approval is required for use in French government agencies and critical infrastructure, making the policy a de facto phase-out of older encryption.

Interesting research on a new class of weak RSA keys: keys with lots of zeros. It turns out that these keys are out in the wild.

The badkeys project is an open-source service that checks public keys for known vulnerabilities. While developing this tool, Hanno collected a massive number of real-world keys from public sources, including Certificate Transparency logs, internet-wide TLS and SSH scans, PGP keys, and many others. By searching this dataset for unexpectedly sparse RSA moduli, we uncovered a large number of keys in the wild with the patterns in Figure 1.

Both patterns include several regularly spaced blocks of all zeros interleaved with seemingly random data. Pattern 1 appears in CT logs for certificates issued to several large organizations, including Yahoo and Verizon, and on some devices running NetApp software. Fortunately, these certificates have already expired, but we still shared our findings with these companies. We wanted to learn more about which product could be responsible for generating these keys, but we did not hear back. Pattern 2 appears on SSH hosts running the CompleteFTP software from EnterpriseDT. The underlying vulnerability affects RSA keys generated using versions 10.0.0­12.0.0 (Dec 2016­Mar 2019) and DSA keys generated with v10.0.0­23.0.4 (Dec 2016­Dec 2023).

These vulnerabilities affect a small minority of hosts on the internet, but the more interesting takeaway is that independent cryptographic implementations failed in similar ways. More implementations may include the same bugs, and so it’s worth tailoring cryptanalytic algorithms for this particular type of failure.

The article doesn’t speculate, but I will. This could be a deliberately designed backdoor, of the sort I wrote about back in 2013. I could imagine some government agency figuring out how to break this class of RSA keys, and then convincing different providers to hand them out to users.

Researchers are using machine learning algorithms to decrypt historical pencil-and-paper ciphers.

As part of their 20th Anniversary celebration, Dark Reading asked five cybersecurity industry leaders who wrote blogs or columns for them over the years to select their favorite piece and share their reflections on the topic today. This is my section.

Renowned technologist and author Bruce Schneier contributed a column on June 20, 2010, warning about cryptography’s inability to secure modern networks, a point he says he has been trying to argue since 2000.

“For a while now, I’ve pointed out that cryptography is singularly ill-suited to solve the major network security problems of today: denial-of-service attacks, website defacement, theft of credit card numbers, identity theft, viruses and worms, DNS attacks, network penetration, and so on.

“Recently, I talked to a former NSA employee at a conference. He told me that back in the 1990s, he had a copy of my book Applied Cryptography by his desk, as did many other cryptographers working at Ft. Meade. People were allowed to refer to it, but they were not allowed to cite it.

“The 1990s were an important decade for cryptography. This was before the internet went mass market, when cryptography was just emerging from a niche academic discipline to a mainstream engineering one. There wasn’t much that programmers could read. The NSA used my book for the same reason it became a bestseller: because it collected all the academic cryptography of the time in one place and made it understandable to people who weren’t mathematicians. They feared it for exactly the same reason.

“I’ve been thinking about that conversation as I revisit a 2010 essay I wrote for Dark Reading, ‘The Failure of Cryptography to Secure Modern Networks.’ Cryptography has inherent mathematical properties that greatly favor the defender. Adding a single bit to the length of a key adds only a slight amount of work for the defender but doubles the amount of work the attacker has to do. Doubling the key length doubles the amount of work the defender has to do (if that—I’m being approximate here) but increases the attacker’s workload exponentially. For many years, we have exploited that mathematical imbalance.

“Computer security is much more balanced. There’ll be a new attack, and a new defense, and a new attack, and a new defense. It’s an arms race between attacker and defender. And it’s a very fast arms race. New vulnerabilities are discovered all the time. The balance can tip from defender to attacker overnight, and back again the night after. Computer security defenses are inherently very fragile.

“That isn’t a new idea. I said much the same thing in the preface to my 2000 book, Secrets and Lies:

“‘Cryptography is a branch of mathematics. And like all mathematics, it involves numbers, equations, and logic. Security, real security that you or I might find useful in our lives, involves people: things people know, relationships between people, people and how they relate to machines. Digital security involves computers: complex, unstable, buggy computers.’

“I especially like how I phrased it in 2016: ‘Cryptography is harder than it looks, primarily because it looks like math. Both algorithms and protocols can be precisely defined and analyzed. This isn’t easy, and there’s a lot of insecure crypto out there, but we cryptographers have gotten pretty good at getting this part right. However, math has no agency; it can’t actually secure anything. For cryptography to work, it needs to be written in software, embedded in a larger software system, managed by an operating system, run on hardware, connected to a network, and configured and operated by users. Each of these steps brings with it difficulties and vulnerabilities.’

“It’s a lesson we have all learned over the decades. Cryptography is still necessary for cybersecurity—although I wouldn’t have used that word back then—but is not sufficient. There are particular attack and forms of mass surveillance that cryptography prevents. But as computers have infused throughout our lives, and networks have connected all those computers, those aspects of cybersecurity have become increasingly important, and vulnerable.

“Today, the cybersecurity world is changing yet again, this time due to the capabilities of artificial intelligence. AI isn’t advancing cryptography, but it’s changing cybersecurity. AI has demonstrated a superhuman ability to find vulnerabilities in software and to write exploits. A similar ability to write patches is probably coming. This has profound implications for both attackers and defenders, and it is unclear who will win the particular arms race in a world of what I call instant software.”

aws cloudtrail lookup-events \
--lookup-attributes AttributeKey=EventName,AttributeValue=GetSecretValue \
--max-results 5 \
--region <YOUR-REGION> \
--query 'Events[0].CloudTrailEvent' \
--output text

{
    "eventVersion": "1.11",
    "userIdentity": {
        "type": "AssumedRole",
        "principalId": "AROA123456789EXAMPLE:i-0c1a23fc456b7ab89",
        "arn": "arn:aws:sts::111122223333:assumed-role/YOUR-EC2-INSTANCE-PROFILE/i-0c1a23fc456b7ab89",
        "accountId": "111122223333",
        "accessKeyId": "ASIAIOSFODNN7EXAMPLE",
        "sessionContext": {
            "sessionIssuer": {
                "type": "Role",
                "principalId": "AROA123456789EXAMPLE",
                "arn": "arn:aws:iam::111122223333:role/YOUR-EC2-INSTANCE-PROFILE",
                "accountId": "111122223333",
                "userName": "YOUR-EC2-INSTANCE-PROFILE"
            },
            "attributes": {
                "creationDate": "2026-03-27T17:08:37Z",
                "mfaAuthenticated": "false"
            },
            "ec2RoleDelivery": "2.0"
        },
        "inScopeOf": {
            "issuerType": "AWS::EC2::Instance",
            "credentialsIssuedTo": "arn:aws:ec2:eu-west-2:111122223333:instance/i-0c1a23fc456b7ab89"
        }
    },
    "eventTime": "2026-03-27T17:12:54Z",
    "eventSource": "secretsmanager.amazonaws.com",
    "eventName": "GetSecretValue",
    "awsRegion": "eu-west-2",
    "sourceIPAddress": "1.2.3.4",
    "userAgent": "aws-sdk-rust/1.3.14 os/linux lang/rust/1.94.1 aws-secrets-manager-agent/2.0.0",
    "requestParameters": {
        "secretId": "arn:aws:secretsmanager:eu-west-2:111122223333:secret:your-secret"
    },
    "responseElements": null,
    "requestID": "027507ea-f377-43d9-bf2f-646d4dc19223",
    "eventID": "f9c3ed0f-81f5-450b-a561-2b9e54fa9e73",
    "readOnly": true,
    "resources": [
        {
            "accountId": "111122223333",
            "type": "AWS::SecretsManager::Secret",
            "ARN": "arn:aws:secretsmanager:eu-west-2:111122223333:secret:your-secret"
        }
    ],
    "eventType": "AwsApiCall",
    "managementEvent": true,
    "recipientAccountId": "111122223333",
    "eventCategory": "Management",
    "tlsDetails": {
        "tlsVersion": "TLSv1.3",
        "cipherSuite": "TLS_AES_128_GCM_SHA256",
        "clientProvidedHostHeader": "secretsmanager.eu-west-2.amazonaws.com",
        "keyExchange": "X25519MLKEM768"
    }
}

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Accelerating the Migration to the Post-Quantum Era

The promise of quantum computing brings an unprecedented paradox. While it will unlock revolutionary breakthroughs in science, materials discovery and medicine, it simultaneously poses an existential threat to the mathematical foundations of modern cybersecurity.

For decades, the global economy has relied on public key cryptography to safeguard everything from personal privacy to national security. This cryptography is built on mathematical problems that are computationally infeasible for classical computers to solve but that quantum computers can solve efficiently, rendering today’s cryptographic protocols obsolete.

Using Shor’s algorithm, a sufficiently powerful quantum computer could factor the large prime numbers that underpin public key cryptography, in minutes. These are tasks that would take today’s most advanced supercomputers a millennium to crack. This capability would effectively turn our strongest digital defenses into open doors, creating a period of vulnerability leading up to Q-Day – the day today’s encryption is broken.

The Migration Crisis: Why Traditional Strategies Fail

For CISOs and technical leaders, the transition to post-quantum cryptography (PQC) is not a simple patch-and-deploy exercise. It is a multiyear transformation that requires updating cryptography across every device, application, certificate and infrastructure component in the enterprise.

Most enterprises today are constrained by cryptographic debt – years of accumulated, undocumented and deprecated encryption protocols buried deep within legacy applications, third-party software libraries and unmanaged IoT devices. This creates a vast and largely invisible attack surface that traditional vulnerability scanners were never designed to detect.

The challenge is compounded by the absence of a unified source of truth. Existing tools offer a fragmented "outside-in" view of the environment. They may identify devices on the network, but they lack visibility into cryptographic libraries embedded within live traffic. Without a real-time Cryptographic Bill of Materials (CBOM), security teams are forced to rely on manual, point-in-time audits that become outdated almost immediately. Spreadsheets cannot scale to this problem.

This visibility gap makes it impossible to prioritize remediation, leaving sensitive data exposed to harvest now, decrypt later (HNDL) attacks. In these attacks, adversaries intercept and store encrypted data today with the intent of unlocking it once quantum computing capabilities mature.

Operationally, traditional migration approaches are equally unworthy. Manually updating cryptography across thousands of global endpoints and branch offices often requires disruptive rip and replace strategies that threaten uptime and demand specialized expertise that is in extremely short supply. Organizations need a way to bridge today’s classical infrastructure with a quantum-resilient future without disrupting business operations or exhausting IT resources.

At Palo Alto Networks, we believe global enterprises cannot afford to wait. Our new Quantum-Safe Security solution is designed to remove these operational roadblocks by making cryptographic discovery, risk assessment and transition both continuous and actionable. We empower enterprises to gain real-time visibility into cryptographic risk and begin building agentic resilience at enterprise scale by integrating with existing security and infrastructure systems, including security information and event management (SIEM), load balancers, endpoint detection and response (EDR), as well as Application Vulnerability Management (AVM) tools.

The Four Stages of Cryptographic Inventory & Remediation

Palo Alto Networks Quantum-Safe Security is built around four foundational stages.

1. Continuous Discovery through Ecosystem Ingestion

Visibility is the first line of defense, but in a complex enterprise, true visibility requires more than a periodic scan. It requires continuous, high-fidelity ingestion of cryptographic intelligence across the environment.

Our solution acts as a central nervous system for your cryptographic posture, ingesting telemetry and logs directly from PAN-OS NGFW and Prisma® Access, enriched with data from a broad ecosystem of third-party security solutions, simplifying Day 0 onboarding. By leveraging your existing network infrastructure as sensors, we provide a comprehensive view of the cryptographic behavior of all assets without the operational friction of deploying new software.

To eliminate blind spots, we go beyond our own telemetry to ingest critical information from your existing systems you rely on. This includes syncing with configuration management database (CMDB) and asset management platforms to align cryptographic data with business inventories, integrating with EDR and access control solutions to monitor endpoint behavior, and aggregating data from network clouds and log platforms. The result is a unified intelligence layer that reflects how cryptography is actually used across the enterprise.

By synthesizing these data streams, we deliver a multidimensional view of cryptographic exposure:

• Discovery – Identification of every application, user device, infrastructure component and IoT device.
• Behavior – Analysis of traffic metadata, including protocols, key exchange mechanisms, encryption algorithms, hashes, certificates and tunnels.
• Context – Precise attribution of hardware models, cryptographic libraries (such as deprecated OpenSSL versions), and browser versions in use.

2. Risk Assessment & Prioritization

Not all data is created equal, and a successful migration requires a surgical focus on where the exposure is most acute. Our Quantum Safe Security solution quantifies risk by correlating cryptographic strength with business criticality, providing a clear, prioritized view of current risk and where remediation matters most.

Assets are categorized into strategic zones, starting with immediate exposure risks caused by deprecated protocols that are vulnerable to classical exploitation today. From there, the solution addresses long-term harvest now, decrypt later threats. As threat models evolve, the risk engine is designed to expand to emerging vectors like identity and authentication integrity, anticipating risks such as “Trust Now, Forge Later" attacks that could undermine digital trust at scale.

At the same time, the solution validates and tracks quantum-secure assets that have successfully transitioned to post-quantum or hybrid-PQC algorithms. By correlating this intelligence with business criticality and data shelf-life, security leaders can make informed decisions. For example, a crown jewel asset containing data that must remain confidential for a decade or more, is flagged as a high HNDL risk today and elevated to the top of the migration queue.

3. Comprehensive Remediation

Moving from a vulnerable state to quantum resilience is a structured journey. Our comprehensive remediation framework guides organizations through three critical stages, supported by automated workflows and prioritized recommendations at every step.

• Current State to Quantum Ready: The first stage focuses on infrastructure modernization. Using continuous discovery insights, the solution provides hardware and software recommendations required to support next-generation cryptographic protocols. An asset reaches a Quantum Ready state once it has the underlying hardware and OS capabilities to support post-quantum algorithms, even if those protocols are not yet activated.
• Quantum Ready to Quantum-Safe: Transitioning to a Quantum-safe state requires activation and configuration of post-quantum defenses. Our solution provides data configuration and certificate compliance guidance to enable PQC/Hybrid-PQC algorithms to be correctly implemented across the estate.
• Virtual Patching via Cipher Translation: For all current and especially legacy systems or IoT devices that cannot be upgraded, we provide an accelerated path to quantum-safety. Through Cipher Translation, the infrastructure acts as a proxy, providing agentic remediation that reencrypts vulnerable traffic into quantum-safe standards (such as ML-KEM) in real-time at the network edge. This approach instantly moves legacy assets from a high-risk current state to a Quantum-safe posture without a single line of code change.

4. Governance: Continuous Crypto-Hygiene & Global Compliance

Quantum readiness is not a one-time event; it is a strategic enterprise transformation that requires continuous oversight to prevent the re-emergence of vulnerabilities. Our governance framework provides the guardrails for your migration through two critical layers of management:

Continuous Crypto-Hygiene & Ongoing Management: Maintaining high-fidelity visibility is essential to preventing the accumulation of "crypto-debt." Our solution automates real-time mapping of all cryptographic dependencies, ensuring your CBOM remains dynamic and accurate as your environment evolves. Furthermore, we introduce Active Drift Detection, which automatically detects and can even block the use of weak or noncompliant ciphers in real-time, preventing developers or third-party services from accidentally introducing insecure protocols.

Global Crypto-Compliance Enforcement & Reporting: As regulatory pressure from governments (like the US Commercial National Security Algorithm Suite 2.0) mounts, organizations must demonstrate measurable progress. Our solution will provide Automated Framework Auditing, offering continuous, native mapping of your environment against global standards, including NIST, FIPS 140-3, and DORA.

Architecting a Quantum-Resilient Enterprise

The transition to quantum-safe security is far more than a technical upgrade. It represents a fundamental shift in how organizations protect the longevity and integrity of their digital assets. Achieving quantum resilience is a multiyear effort that requires both advanced technology and strategic partnership.

That's why Palo Alto Networks has established Integrated Quantum Practices, bringing together technology, partners and professional services to help organizations navigate the complexity of this transition with confidence. By combining deep cryptographic visibility with intelligent, agentic remediation, organizations can systematically retire their cryptographic debt and build resilience into their security architecture over time.

This proactive approach does more than mitigate emerging risk. It establishes a foundation of digital trust that is resilient against the threats of tomorrow, enabling your most sensitive intellectual property to remain secure for its entire shelf life, even as cryptographic standards evolve.

Secure Your First-Mover Advantage: The Quantum Readiness Assessment

Don’t let the complexity of the quantum transition stall your organization’s progress. Begin your path to resilience with a Quantum Readiness Assessment, a focused engagement to clarify current exposure and identify the most critical areas for action. To go deeper, watch the Quantum-Safe Summit on demand for expert perspectives on cryptographic risk and quantum readiness.

The Palo Alto Networks Quantum-Safe Security solution is expected to be generally available to customers on January 30, 2026, with additional integration enhancements planned for April 2026.

Forward-Looking Statements

This blog contains forward-looking statements that involve risks, uncertainties and assumptions, including, without limitation, statements regarding the benefits, impact or performance or potential benefits, impact or performance of our products and technologies or future products and technologies. These forward-looking statements are not guarantees of future performance, and there are a significant number of factors that could cause actual results to differ materially from statements made in this [blog. We identify certain important risks and uncertainties that could affect our results and performance in our most recent Annual Report on Form 10-K, our most recent Quarterly Report on Form 10-Q, and our other filings with the U.S. Securities and Exchange Commission from time-to-time, each of which are available on our website at investors.paloaltonetworks.com and on the SEC's website at www.sec.gov. All forward-looking statements in this blog are based on information available to us as of the date hereof, and we do not assume any obligation to update the forward-looking statements provided to reflect events that occur or circumstances that exist after the date on which they were made.

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