Knife Cutting the Edge: Disclosing a China-nexus gateway-monitoring AitM framework

  • Cisco Talos uncovered “DKnife,” a fully featured gateway-monitoring and adversary-in-the-middle (AitM) framework comprising seven Linux-based implants that perform deep-packet inspection, manipulate traffic, and deliver malware via routers and edge devices. Based on the artifact metadata, DKnife has been used since at least 2019 and the command and control (C2) are still active as of January 2026.
  • DKnife’s attacks target a wide range of devices, including PCs, mobile devices, and Internet of Things (IoT) devices. It delivers and interacts with the ShadowPad and DarkNimbus backdoors by hijacking binary downloads and Android application updates.
  • DKnife primarily targets Chinese-speaking users, indicated by credential harvesting for Chinese-language services, exfiltration modules for popular Chinese mobile applications and code references to Chinese media domains. Based on the language used in the code, configuration files and the ShadowPad malware delivered in the campaign, we assess with high confidence that China-nexus threat actors operate this tool.
  • We discovered a link between DKnife and a campaign delivering WizardNet, a modular backdoor known to be delivered by a different AiTM framework Spellbinder, suggesting a shared development or operational lineage.

Background 

Knife Cutting the Edge: Disclosing a China-nexus gateway-monitoring AitM framework

Since 2023, Cisco Talos has continuously tracked the MOONSHINE exploit kit and the DarkNimbus backdoor it distributes. The exploit kit and backdoor were historically used for delivering Android and iOS exploits. While hunting for DarkNimbus samples, Talos discovered an executable and linkable format (ELF) binary communicating with the same C2 server as the DarkNimbus backdoor, which retrieved a gzip-compressed archive. Analysis revealed that the archive contained a fully featured gateway monitoring and AiTM framework, dubbed “DKnife” by its developer. Based on the artifact metadata, the tool has been used since at least 2019, and the C2 is still active as of January 2026. 

Link between DKnife and WizardNet campaigns 

During Talos’ pivot on the C2 infrastructure associated with DKnife, we identified additional servers exhibiting open ports and configurations consistent with previously observed DKnife deployments. Notably, one host (43.132.205[.]118) displayed port activity characteristic of DKnife infrastructure and was additionally found hosting the WizardNet backdoor on port 8881. 

WizardNet is a modular backdoor first disclosed by ESET in April 2025, known to be deployed via Spellbinder, a framework that performs AitM attacks leveraging IPv6 Stateless Address Autoconfiguration (SLAAC) spoofing. 

Network responses from the WizardNet server align closely with the tactics, techniques, and procedures (TTPs) documented in ESET’s analysis. Specifically, the server delivered JSON-formatted tasking instructions that included a download URL pointing to an archive named minibrowser11_rpl.zip, which include the Wizardnet backdoor downloader.  

{ 
  "CSoftID": 22, 
  "CommandLine": "", 
  "Desp": "1.1.1160.80", 
  "DownloadUrl": "http://43.132.205.118:81/app/minibrowser11_rpl.zip", 
  "ErrCode": 0, 
  "File": "minibrowser11.zip", 
  "Flags": 1, 
  "Hash": "cd09f8f7ea3b57d5eb6f3f16af445454", 
  "InstallType": 0, 
  "NewVer": "1.1.1160.900", 
  "PatchFile": "QBDeltaUpdate.exe", 
  "PatchHash": "cd09f8f7ea3b57d5eb6f3f16af445454", 
  "Sign": "", 
  "Size": 36673429, 
  "VerType": "" 
} 

Spellbinder’s TTPs, which involve hijacking legitimate application update requests and serving forged responses to redirect victims to malicious download URLs, are similar to DKnife’s method of compromising Android application updates. Spellbinder has also been observed distributing the DarkNimbus backdoor, whose C2 infrastructure previously led to the initial discovery of DKnife. The URL redirection paths (http[:]//[IP]:81/app/[app name]) and port configurations identified in these cases are identical to those used by DKnife, indicating a shared development or operational lineage.  

Targeting scope  

Based on artifacts recovered from the DKnife framework, this campaign appears to primarily target Chinese-speaking users. Indicators supporting this assessment include data collection and processing logic explicitly designed for Chinese mail services , as well as parsing and exfiltration modules tailored for Chinese mobile applications and messaging platforms, including WeChat. In addition, code references to Chinese media domains were identified in both the binaries and configuration files. The screenshot below illustrates an Android application hijacking response that targeted a Chinese taxi service and rideshare application. 

It is important to note that Talos obtained the configuration files for analysis from a single C2 server. Therefore, it remains possible that the operators employ different servers or configurations for distinct regional targeting scopes. Considering the connection between DKnife and the WizardNet campaign and given ESET’s reporting that WizardNet activity has targeted the Philippines, Cambodia, and the United Arab Emirates, we cannot rule out a broader regional or multilingual targeting scope. 

Knife Cutting the Edge: Disclosing a China-nexus gateway-monitoring AitM framework
Figure 1. The manifest response used for Android application update.

Indication of Chinese-speaking threat actors 

DKnife contains several artifacts that suggest the developer and operators are familiar with Simplified Chinese. Multiple comments written in Simplified Chinese appear throughout the DKnife configuration files (see Figure 2). 

Knife Cutting the Edge: Disclosing a China-nexus gateway-monitoring AitM framework
Figure 2. Example of Simplified Chinese language used in the comment of configuration files.

One component of DKnife is named yitiji.bin. The term “Yitiji” is the Pinyin (official romanization system for Mandarin Chinese) for “一体机” which means “all-in-one.” In DKnife, this component is responsible for opening the local interface on the device to route traffic through a single device in this scenario. 

Additionally, within the DKnife code, when reporting user activities back to the remote C2 server, multiple messages are labelled in Simplified Chinese to indicate the types of activities. 

Knife Cutting the Edge: Disclosing a China-nexus gateway-monitoring AitM framework
Figure 3. Simplified Chinese message embedded in the code and sent to remote C2.

DKnife: A gateway monitoring and AitM framework 

DKnife is a full-featured gateway monitoring framework composed of seven ELF components that perform traffic manipulation across a target network. In addition to the seven ELF components that provide the core functionality, the framework comes with a list of configuration files (see Appendix for the full list), self-signed certificates, phishing templates, forged HTTP responses for hijacking and phishing, log files, and backdoor binaries. 

 The framework is designed to work with backdoors installed on compromised devices. Its key capabilities include serving update C2 for the backdoors, DNS hijacking, hijacking Android application updates and binary downloads, delivering ShadowPad and DarkNimbus backdoors, selectively disrupting security-product traffic and exfiltrating user activity to remote C2 servers. The following sections highlight DKnife’s key capabilities and explain how its seven ELF binaries work together to implement them. 

Targeted platform 

DKnife binaries are 64-bit Linux (x86-64) ELF implants that run on Linux-based devices. One of the components remote.bin imports the library “libcrypto.so.10”, indicating it targets CentOS/RHEL-based platforms. Configuration elements such as PPPoE, VLAN tagging, a bridged interface (br0), and adjustable MTU and MAC parameters suggest that DKnife is tailored for edge or router devices running Linux-based firmware.  

Knife Cutting the Edge: Disclosing a China-nexus gateway-monitoring AitM framework
Figure 4. wxha.conf config file. 

Key capabilities 

The Deep Packet Inspection (DPI) logic and modular design of DKnife enable operators to conduct traffic monitoring campaigns ranging from covert monitoring of user activity to active in-line attacks that replace legitimate downloads with malicious payloads. The following sections highlight the framework’s key capabilities including: 

  • Serving C2 to Android and Windows DarkNimbus malware 
  • DNS hijacking 
  • Android Application binary update hijacking 
  • Windows binary hijacking 
  • Anti-virus traffic disruption 
  • User activity monitoring 

Serving updated C2 to the Android and Windows DarkNimbus backdoors 

In previously published research about the DarkNimbus backdoor, analysts noted that some samples communicated with their C2 servers using a custom protocol, leading to the hypothesis that the backdoor operated within an AiTM environment. Talos’ discovery of DKnife validates this assessment. 

DKnife is designed to work with both Android and Windows variants of DarkNimbus. For the Windows version, the dknife.bin component inspects UDP traffic and sends them to port 8005. When it identifies a request containing the string marker DKGETMMHOST, it constructs and returns a response specifying the C2 server address. The response includes two parameters: DKMMHOST and DKFESN. The DKMMHOST value is read from DKnife’s configuration file (“/dksoft/conf/server.conf”), which contains the line MMHOST URL=[value]. The DKFESN value represents a device identifier that DKnife retrieves from an internal server located at “192.168.92.92:8080”.  

Knife Cutting the Edge: Disclosing a China-nexus gateway-monitoring AitM framework
Figure 5. Code excerpt from DKnife showing the handler for “Obtain C2” requests from the Windows version of DarkNimbus.

For the Android variants, the backdoor attempts to contact a Baidu URL “http[:]//fanyi.baidu[.]com/query_config_dk” to retrieve its C2 information. This URL does not return any response from Baidu itself; rather, it serves as a recognizable trigger for DKnife, which intercepts the request and injects the C2 response.  

Knife Cutting the Edge: Disclosing a China-nexus gateway-monitoring AitM framework
Figure 6. Code from Android DarkNimbus sample e50247787d2e12c1e8743210a0c0e562cf694744436d93920a037d2f927f533.
Knife Cutting the Edge: Disclosing a China-nexus gateway-monitoring AitM framework
Figure 7. Code in DKnife for handling “Obtain C2” request from Android version of DarkNimbus.

DNS hijacking 

The DKnife framework relies on two main configuration files to control its DNS-based hijacking and attack logic. The dns.conf file defines the global keyword-to-IP mapping rules and framework parameters used for DNS interception. The perdns.conf file extends this by defining per-target or campaign-specific DNS attack tasks, including timing parameters such as interval and duration for each attack. In the archive we obtained from the C2 server, only perdns.conf was present; it contained a template for setup rather than active attack data. 

Knife Cutting the Edge: Disclosing a China-nexus gateway-monitoring AitM framework
Figure 8. Perdns.conf template.

DKnife supports both IPv4 and IPv6 DNS hijacking: 

  • IPv4 (A) DNS hijacking:
    • For configured domains: replies with the per-domain IPv4 from dns.conf 
    • For test.com: replies with 8.8.8.8 (and logs) 
    • For JD-related domains (“api.m.jd.com”, “beta-api.m.jd.com”, “api.jd.co.th”, or “beta-api.jd.co.th”): replies with 10.3.3.3 
  • IPv6 (AAAA) DNS hijacking:
    • For configured domains and for test.com: replies with fixed IPv6 IP 240e:a03:a03:303:a03:303:a03:303 (crafted) 

The private IP address 10.3.3.3 belongs to the local interface created by the yitiji.bin component in DKnife. DKnife uses the local interface for delivering malicious binaries (see the following section). The crafted AAAA response is not an actual public address. When DKnife sees traffic addressed to that crafted IPv6, it checks the last 8 bytes of the address and converts it to the local interface address 10.3.3.3.  

The code also specially tempers the domains associated with mail services. It takes the queried domain, removes any trailing period if present, then splits on “.” and extracts the leftmost label (e.g., “mail.example.com” into “mail”). It then looks up that label in the same per-domain configuration. Once the attack flag is enabled and the cooldown window has elapsed, it immediately injects a configured response to replace the original response.  

Android application binary update hijacking 

Knife Cutting the Edge: Disclosing a China-nexus gateway-monitoring AitM framework
Figure 9. Android APK download hijacking workflow.

DKnife can hijack and replace Android application updates by intercepting the update manifest requests. When an Android application sends an APK update manifest request, DKnife intercepts it, consults the configuration file, and selects the corresponding JSON response file to reply. This response contains a download URL redirecting to the URL of address 10.3.3.3, which DKnife recognizes and routes to the yitiji.bin created Local Area Network (LAN) to deliver malware instead of the legitimate update APK. 

 The configuration file /dksoft/conf/url.cfg defines the rules and responses used for traffic blocking, phishing on Android and Windows platforms, executable file (.exe)  hijacking, and credential-phishing page responses. The file follows the format: [Request URL] [Response JSON file] as shown in Figure 11. 

Knife Cutting the Edge: Disclosing a China-nexus gateway-monitoring AitM framework
Figure 10. Configuration file url.cfg defines the targeted sites and update manifest file response DKnife is sending to the requested URL.

Within the /bin/html/dkay-scripts folder of the DKnife archive, there are 185 JSON files configured to hijack applications. The targeted applications are mostly popular Chinese-language services (some only available in China), including news media, video streaming, image editing apps, e-commerce platforms, taxi-service platforms, gaming, and pornography video streaming, among others. An example response used to hijack a Chinese photo editing application update request is shown below: 

Knife Cutting the Edge: Disclosing a China-nexus gateway-monitoring AitM framework
Figure 11. The response manifest file (11184.json) for hijacking the APK download

Windows binary hijacking for delivering Shadowpad and DarkNimbus 

In addition to Android update hijacking, DKnife also supports hijacking of Windows and other binary downloads. The hijacking rules are set up during initialization. DKnife attempts to read the rules configuration file at /dksoft/conf/rules.aes and decrypts it using a variant of the Tiny Encryption Algorithm (TEA) algorithm employed by Tencent’s older OICQ/QQ login protocols, commonly referred to as QQ TEA. DKnife decrypts the file with a key dianke0123456789, and saves the decrypted file as rules.conf.  

Knife Cutting the Edge: Disclosing a China-nexus gateway-monitoring AitM framework
Figure 12. QQ TEA decipher algorithm

Talos did not obtain the rules.aes file from the archive we downloaded. However, based on the code analysis, rules.conf is the configuration to define what requests to match, what to send back, when to throttle and tracking the response. The rules include the following information:  

Field in the line  

Description 

id=<number> 

Rule ID 

host=<regex> 

Matching host IP 

user_agent=<regex> 

Matching User Agent 

url=<regex> 

Matching URL 

file=<relative path> 

Relative file name points into /dksoft/html/dkay-scripts/. 

location=<HTTP Location> 

HTTP location used for 302 redirects 

msg=<plain text> 

Message for operator 

interval=<sec> 

Minimum seconds between two injections to the same victim 

duration=<sec> 

How long the rule stays active once triggered 

After reading the rules into a data structure in the memory, the rules.conf file is deleted on the device. When an HTTP request’s Host and URI match the configured rule, DKnife evaluates the rule’s duration and interval timers to determine whether to trigger. If the rule fires and the requested filename has a matching extension (e.g., “.exe”, “.rar”, “.zip”, or “.apk”), DKnife forges an HTTP 302 redirect whose Location URL is taken from the rule’s data field. 

Knife Cutting the Edge: Disclosing a China-nexus gateway-monitoring AitM framework
Figure 13. Code to match on the binary download and respond with HTTP 302.

If the binary download URL matches a specific pattern (“.exe” extension after the query symbol), the file name is replaced with install.exe

Knife Cutting the Edge: Disclosing a China-nexus gateway-monitoring AitM framework
Figure 14. Code to replace .exe download file name.

Shadowpad and DarkNimbus backdoors 

The install.exe file (SHA256: 2550aa4c4bc0a020ec4b16973df271b81118a7abea77f77fec2f575a32dc3444) is found in the downloaded archive under path /dkay-scripts/. It is a RAR self extraction package containing three binaries, that are actually ShadowPad and the DarkNimbus backdoor, which both being reported [1,2] used by China-nexus threat actors. When launched, the legitimate .exe (TosBtKbd.exe) sideloads the ShadowPad DLL loader (TosBtKbd.dll), which then loads the DarkNimbus DLL backdoor (TosBtKbdLayer.dll). That DarkNimbus backdoor calls out to the Cloudflare DNS address 1.1.1.1, which DKnife intercepts to return the real C2 IP. 

Knife Cutting the Edge: Disclosing a China-nexus gateway-monitoring AitM framework
Figure 15. Shadowpad and DarkNimbus backdoor delivered by DKnife.

The Shadowpad sample has not been previously reported but is very similar to a previously reported sample. Although it uses a different unpacking XOR seed key, it employs the same unpacking algorithm. 

Knife Cutting the Edge: Disclosing a China-nexus gateway-monitoring AitM framework
Figure 16. Unpacking algorithm used in the Shadowpad loader sample (SHA256: 43891d3898a54a132d198be47a44a8d4856201fa7a87f3f850432ba9e038893a)
Knife Cutting the Edge: Disclosing a China-nexus gateway-monitoring AitM framework
Figure 17. Unpacking algorithm used in the Trend Micro’s sample (SHA256: c59509018bbbe5482452a205513a2eb5d86004369309818ece7eba7a462ef854)

The Shadowpad samples (both .exe and .dll) are signed with two certificates both issued from the signer “四川奇雨网络科技有限公司”. This is a company located in Sichuan Chengdu, China specialised in developing computer software and providing network communication devices, according to publicly available information. Pivoting on this signer, Talos found 17 samples that contain the Shadowpad and DarkNimbus backdoor.  

Anti-virus traffic disruption 

The DKnife traffic inspection module actively identifies and interferes with communications from antivirus and PC-management products. It detects 360 Total Security by searching HTTP headers (e.g., the DPUname header in GET requests or the x-360-ver header in POST requests) and by matching known service domain names. When a match is found, the module drops or otherwise disrupts the traffic with the crafted TCP RST packet. It similarly looks for and disrupts connections to Tencent services and PC-management endpoints. 

Recognized Tencent-related domains: 

  • dlied6.qq.com 
  • pcmgr.qq.com 
  • pc.qq.com 
  • www.qq.com/q.cgi 

Keywords used to match 360 Total Security-related domains: 

  • 360.cn 
  • 360safe 
  • qihucdn 
  • duba.net 
  • mbdlog.iqiyi.com 

User activity monitoring 

DKnife inspects traffic to monitor and report user’s network activity to its remote C2 in real time. Observed telemetry categories include messaging (Signal and WeChat activities including voice/video calls, sent texts, received images, in-app article views), shopping, news consumption, map searches, video streaming, gaming, dating, taxi and rideshare requests, mail checking, and other user actions. Most of the activity reports are triggered by monitoring the request to service/platform domains or URLs. When reporting, the code sends a corresponding embedded message representing the reported activity. For example, Figure 18 shows the code to report Signal messaging activities. The message sent to remote C2 translates to “Using Signal encryption chat APP”. 

Knife Cutting the Edge: Disclosing a China-nexus gateway-monitoring AitM framework
Figure 18. Code for reporting Signal communication

The table below shows some of the observed telemetry categories and the embedded messages.  

WeChat activities 

微信打语音或视频电话 (WeChat voice or video calls) 

微信发送一条文字消息 (WeChat send a text message) 

微信发送或者接收图片 (WeChat send or receive picture) 

微信打开公众号看文章 (WeChat checking official account and articles) 

Using Signal 

使用signal加密聊天APP (Use the Signal encrypted-chat app) 

Shopping activity 

查询**商品信息 (Query product information on **) 

Query train-ticket information 

查询火车票信息 (Query train-ticket information) 

Searching on Maps 

查看**地图 (View the map) 

Reading News 

****看新闻 (Read news) 

Dating Activity 

****打开时 (When the dating app opens) 

Email/platforms credential harvesting and phishing 

DKnife can harvest credentials from a major Chinese email provider and host phishing pages for other services.  For harvesting email credentials, the sslmm.bin component presents its own TLS certificate to clients, terminates and decrypts POP3/IMAP connections, and inspects the plaintext stream to extract usernames and passwords. Extracted credentials are tagged with “PASSWORD”, forwarded to the postapi.bin component, and ultimately relayed to remote C2 servers. 

Knife Cutting the Edge: Disclosing a China-nexus gateway-monitoring AitM framework
Figure 19. Code to forward password.

DKnife can also serve phishing pages. The phishing routes are defined in url.cfg, and several phishing templates were discovered under /dkay-scripts/. All discovered pages submit harvested passwords to endpoints whose paths end with dklogin.html; however, no dklogin.html file was found in the local script directory. 

Knife Cutting the Edge: Disclosing a China-nexus gateway-monitoring AitM framework
Figure 20. Phishing page setup.

In addition to the capabilities described above, Talos observed DKnife functions that may target IoT devices. Talos is coordinating with the device vendor on mitigations. 

The DKnife downloader 

The ELF binary (17a2dd45f9f57161b4cc40924296c4deab65beea447efb46d3178a9e76815d06) we discovered from hunting is a downloader that downloads and performs initial setup for the DKnife framework. Upon execution, it attempts to load a configuration file from /dksoft/conf/server.conf to set up the C2 server. The server.conf file contains the C2 configuration in the format UPDATE URL=[config]. If the file does not exist, the binary defaults to the embedded C2 URL http://47.93.54[.]134:8005/

After configuring the C2, the binary retrieves or generates a UUID for the host device based on the MAC addresses of its network interfaces and stores it in /etc/diankeuuid. The UUID follows the format YYYYMMDDhhmmss[MAC1][MAC2] (e.g., 20240219165234000c295de649). The updater also stores a 32-character hexadecimal MD5 checksum in /dksoft/conf/<UUID>.ini, which is later used to verify updates from the C2 server.  

The code establishes persistence by modifying the /etc/rc.local file, a script commonly used to execute commands and scripts after the system boots and initializes services. The updater adds its commands between markers #startdianke and #enddianke. It also copies the currently running executable into the /dksoft/update/ directory and appends a corresponding entry to /dksoft/update/[executable path] auto to ensure the binary runs automatically each time the system starts. 

After creating the folders for DKnife deployment, the downloader fetches the DKnife archive from the C2 and launches every binary in /dksoft/bin/ using nohup [filepath] 2>/dev/null 1>/dev/null &. The folder contains seven binaries, each performing a distinct role within the DKnife framework. 

DKnife’s seven components 

The seven implants in DKnife serve the purpose of DPI engine, data reporting, reverse proxy for AitM attack, malicious APK download, framework update, traffic forwarding, and building P2P communication channel with the remote C2. A summary of the components and their roles are listed in the table below:

ELF Implant 

Role 

Description 

dknife.bin 

DPI & Attack Engine 

 

The main engine of DKnife. Includes logic for deep packet inspection, user activities reporting, binary download hijacking, DNS hijacking, etc. 

postapi.bin 

Data Reporter 

Performs as traffic labelling and relay component, receives traffic from DKnife and reports to remote C2. 

sslmm.bin 

Reverse Proxy 

Reverse proxy server module modified from HAProxy. TLS termination, email decryption, and URL rerouting. 

mmdown.bin 

Updater 

Malicious Android APK downloader/updater. It connects to C2 to download the APKs used for the attack. 

yitiji.bin 

Packets Forwarder 

Creates a bridged TAP interface on the router to host and route attacker-injected LAN traffic. 

remote.bin 

P2P VPN 

Customized N2N (a P2P) VPN client component that creates a communication channel to remote C2. 

dkupdate.bin 

Updater & Watchdog 

Updater and Watchdog to keep the components alive. 

The graph below shows how the seven DKnife components work together. 

Knife Cutting the Edge: Disclosing a China-nexus gateway-monitoring AitM framework
Figure 21. Functions of seven DKnife components.

DKnife.bin 

The dknife.bin implant is the main component that acts as the brain of DKnife. It is in charge of all the packet inspection and attack logics, as described in the Key Capabilities section. Upon execution, the implant does some initial setup for the framework. It reads the configuration file /dksoft/conf/wxha.conf to search for the sniffing interface (INPUT_ETH) and attacker interface (ATT_ETH). If the config file is not presented, the default interface for both are eth0. It also reads configuration files for attacking rules and remote C2.  

Throughout the packet inspection process, dknife.bin reports information including collected data, user’s activities, attack status and average throughput to the relay component postapi.bin listening at the 7788 port on the device. The reporting packets are a 256-byte UDP datagram with a fixed seven bytes prefix DK7788. At offset 0x40 a label is attached, which represents types of the information (example types including DKIMSI for IMSI information, USERID for harvested user accounts, WECHAT for WeChat activities reporting, ATKRESULT for attack results, etc). Each type of reporting has the corresponding report value format. We listed some examples in the graph below.  

Knife Cutting the Edge: Disclosing a China-nexus gateway-monitoring AitM framework
Figure 22. Report UDP datagram send from dknife.bin to postapi.bin.
Knife Cutting the Edge: Disclosing a China-nexus gateway-monitoring AitM framework
Figure 23. Message reporting format.

Postapi.bin 

This is the data relay component in DKnife. It receives forwarded UDP dataframe from dknife.bin, processes, identifies, and labels the data and sends them to remote C2 servers. When receiving the UDP dataframe, it validates the DK7788 prefix and extracts device ID, MAC address, source and destination IPs and ports. It then exfiltrates more interesting data based on the rules defined in file ssluserid.conf. The file is a rulebook for defining the targeted services/platforms and the corresponding scrapping data. The rules define the following methods for scraping: 

  • get_url: scrape a value from the URL of a GET request  
  • get_cookie: scrape from Cookie header of a GET  
  • post_url: scrape from the URL of a POST  
  • post_cookie: scrape from Cookie header of a POST  
  • post_content: scrape from the body of a POST  

Each rule also defines which data fields to collect. These include device IDs, phone numbers, IMEIs/IMSIs, MACs, UUIDs, IPs, usernames, etc. DKnife targets dozens of popular Chinese-language mobile and web apps, some of which are only available to Chinese users. Figure below shows part of the rules in the configuration file

Knife Cutting the Edge: Disclosing a China-nexus gateway-monitoring AitM framework
Figure 24. Rules in ssluserid.conf.

Postapi.bin loads the configuration file server.conf to obtain the address of the remote C2 server used for data exfiltration. If the file is missing, it defaults to https://47.93.54[.]134:8003. The component uses libcurl to send different types of exfiltrated and reporting data via HTTP POST requests to specific API endpoints. The following table lists the reporting URLs and the corresponding data transmitted.

Default URL in the binary 

Data Transmitted 

https://47.93.54[.]134:8003/protocol/tcp-data 

Full HTTP or DNS records: URL, headers, optional body (Base-64); raw packet excerpts 

https://47.93.54 [.] 134:8003/protocol/channel-trigger-log 

DKnife status log, debugging logs 

https://47.93.54 [.] 134:8003/protocol/virtual-id 

Bundles of device identifiers (IMEI, IMSI, phone number, MAC, UUID, IP) tied to a host name 

https://47.93.54 [.] 134:8003/protocol/user-account 

Harvested user credentials 

https://47.93.54 [.] 134:8003/protocol/application 

Posts per-application DNS/traffic-hijack data 

https://47.93.54 [.] 134:8003/protocol/target-info 

Online/offline heart-beat for a specific subscriber: PPPoE, MAC, last-seen time, device UUID 

https://47.93.54 [.] 134:8003/public/bind-ip 

IP&UUID bindings 

https://47.93.54 [.] 134:8003/protocol/internet-action 

WeChat/QQ “internet action” logs (e.g., friend-adds, file-sends) 

https://47.93.54 [.] 134:8003/protocol/attack-result 

Logs of attacking results 

The posted data always include a dkimsi=<IMSI> at the end of the data, which is the IMSI or mobile identifier extracted from the packets if available. The binary set a default IMSI 460110672021628 in the code, which is an IMSI with a China Telecom carrier. 

Sslmm.bin 

This component acts as the reverse proxy server for the AitM attack and is implemented as a pre-configured, customized build of HAProxy. It loads its primary configuration from sslmm.cfg and performs request hijacking and replacement according to rules defined in url.cfg. Copies of hijacked traffic and execution results are encapsulated as UDP dataframes and sent to the postapi.bin component, similar to the behavior implemented in dknife.bin

In addition to standard HAProxy proxying, sslmm.bin includes custom logic to inspect, log, exfiltrate, and conditionally rewrite client HTTP(S) requests after TLS termination. Content injection is primarily performed through HTTP request-line replacement, redirecting victims to attacker-controlled resources that are typically hosted under the /dkay-scripts/ directory. The resulting telemetry and artifacts are then relayed via postapi.bin to remote C2 infrastructure. 

Operationally, the HAProxy configuration terminates TLS on HTTPS and mail-over-TLS ports (443, 993, 995) using a self-signed certificate stored at /dksoft/conf/server.pem, and proxies the decrypted traffic to the appropriate backends. A management/statistics interface is exposed on 0.0.0.0:10800 and protected only by static credentials. Requests matching the /dkay-scripts/ path are selectively downgraded to plain HTTP and routed to a local service at 127.0.0.1:81, enabling response modification or injection before content is returned to the client. 

This interception model depends on a key trust assumption: for the TLS MITM to be transparent, endpoints must accept the certificate chain presented by the gateway. One hypothesis is that the associated endpoint malware (given the broader DarkNimbus toolchain across Windows and Android) may be used to establish that trust or weaken certificate validation, enabling host-specific certificates to be presented during interception. However, we did not have the artifacts to confirm that such trust establishment or validation bypass is performed on victim devices.  

Knife Cutting the Edge: Disclosing a China-nexus gateway-monitoring AitM framework
Figure 25. Code for request line injection.
Knife Cutting the Edge: Disclosing a China-nexus gateway-monitoring AitM framework
Figure 26. Part of HAProxy configuration.

Yitiji.bin 

Yitiji.bin is a DKnife component that creates a bridged TAP interface on the router to host and route attacker-injected LAN traffic. It creates a virtual TAP interface named “yitiji”, using the IP address 10.3.3.3 and MAC address 1E:17:8E:C6:56:40, and bridges that interface to the real network. 

DKnife responds to binary download requests using URL points to the Yitiji interface (e.g., http://10.3.3.3:81/app/base.apk). When such a request is received, the dknife.bin component forwards the traffic to UDP port 555, where yitiji.bin is listening. The component then determines the appropriate link-layer encapsulation, reconstructs complete Ethernet/IP/TCP frames (primarily TCP and ICMP), corrects packet lengths and checksums, and injects them into the TAP interface. This causes the kernel to treat the forged traffic as legitimate LAN communication. Through this mechanism, DKnife can receive the binary download request and serve the payload via this interface. In the reverse direction, Yitiji captures packets leaving the TAP, restores their original VLAN/PPPoE/4G headers, recalculates IP and TCP checksums, and transmits them through the physical network interface specified in the configuration file /dksoft/conf/wxha.conf. It also fabricates ARP replies so other hosts treat the interface as a device in the LAN. 

In this way, Yitiji creates a distinct LAN for delivering the malware. This approach facilitates the AitM attack for binary downloads in a stealthy way that avoids IP conflicts and detection.  

Remote.bin 

This component functions as an N2N peer-to-peer VPN client. When executed it creates a virtual network device named “edge0” and attaches it to a P2P overlay, automatically joining the hardcoded community dknife and registering with the embedded supernode. All traffic routed into edge0 is encapsulated and forwarded over UDP to overlay peers, and the binary also binds a management UDP port on 5644. 

With this component, the gateway itself becomes reachable from the overlay and can serve as an egress point for data exfiltration. The implementation supports Twofish encryption if an N2N_KEY environment variable is supplied, but no such key was embedded in the analysed code or associated files. 

Mmdown.bin 

This binary is a simple Android APK malware downloader and update component in the DKnife framework. It communicates with a hardcoded C2 (http://47.93.54[.]134:8005) and periodically checks for an update manifest and then downloads whatever files the server specifies. 

On startup it ensures a handful of local directories exist and generates or reads the UUID from file /etc/diankeuuid to uses it as the filename for the downloaded per-host manifest file <UUID>.mm. The “.mm” file is a list of URLs and MD5 pairs in the format of http://[URL]<TAB><16-byte MD5>. After downloading the manifest file, it parses the file and repeatedly attempts to download each URL over plain HTTP, verifies the downloaded file’s MD5, and on success copies the file into the local web content directory /dksoft/html/app/. When one or more files are successfully fetched it archives the manifest into /dksoft/conf/<UUID>.mm and updates internal MD5 bookkeeping so it doesn’t repeatedly download the same files. 

Dkupdate.bin 

This binary functions as a DKnife download, deploy, and update component similar to the downloader we initially discovered, but with additional capabilities. It retrieves an update archive update_bin.tar.gz from a C2 server (using a different embedded default URL: http://117.175.185[.]81:8003/), launches a separate binary called eth5to2.bin (not included in the downloaded archive, likely for traffic forwarding) and starts Nginx to run the web server to serve the hijacking components that manipulate HTTP/HTTPS responses.

Getting Network Devices Information 

In both dknife.bin and postapi.bin components, DKnife tries to login to an interface which is likely for router management at 192.168.92.92:8080 via the following POST request to retrieve network users and PPPOE information. The POST request for login and getting device information both sent a password MD5 (which is the MD5 of q1w2e3r4) for authentication. If successful login, the server replies with a device serial number (SN) and number of users currently registered. If the number is not zero, the implant requests for the list of MAC and PPPoE ID mapping. 

POST /login HTTP/1.1 

Host: 192.168.92.92:8080 

Content-Type: application/json 

Content-Length: 38 

 

{"passwdMD5":"c62d929e7b7e7b6165923a5dfc60cb56"} 

 

POST /fe-device-info HTTP/1.1 

Host: 192.168.92.92:8080 

User-Agent: Mozilla/5.0 

Cookie: feWebSession={"sessionId":****} 

Content-Length: 48 

 

{"passwdMD5":"c62d929e7b7e7b6165923a5dfc60cb56"} 

 

POST /user HTTP/1.1 

Host: 192.168.92.92:8080 

User-Agent: Mozilla/5.0 

Cookie: feWebSession={"sessionId":} 

Content-Type: application/json 

Content-Length: 15 

 

{"index":"all"} 

Knife Cutting the Edge: Disclosing a China-nexus gateway-monitoring AitM framework
Figure 27. Code parsing the session ID response from management interface.

Conclusion 

Routers and edge devices remain prime targets in sophisticated targeted attack campaigns. As threat actors intensify their efforts to compromise this infrastructure, understanding the tools and TTPs they employ is critical. The discovery of the DKnife framework highlights the advanced capabilities of modern AitM threats, which blend deep‑packet inspection, traffic manipulation, and customized malware delivery across a wide range of device types. Overall, the evidence suggests a well‑integrated and evolving toolchain of AitM frameworks and backdoors, underscoring the need for continuous visibility and monitoring of routers and edge infrastructure. 

Appendix 

Configuration Files 

Config file 

In Default Archive 

Description 

/dksoft/conf/wxha.conf 

Yes 

Config for the attack and sniff interface, output environment, QQ proxy host. 

/dksoft/conf/rules.aes 

/dksoft/conf/rules.conf 

 

rulebook for HTTP(S) traffic hijacking.  

 /dksoft/conf/dns.conf  

 

DNS hijacking mapping configuration.  

/dksoft/conf/url.cfg 

Yes 

Configuration for traffic blocking, Android + Windows phishing, executable file (.exe)  replacement, credential-stealer pages & scripts. 

/dksoft/conf/server.conf 

 

C2 configuration 

/dksoft/conf/adsl.conf 

 

Configuration related to the ADSL related rules  

/dksoft/conf/userid.conf 

 

Configuration to define what user information to collect from the targeted traffic.  

/dksoft/conf/appdns.conf 

 

Configuration to map domain names to certain apps.  

/dksoft/conf/browser.conf 

 

Configuration to map user agents to browsers.  

/dksoft/conf/perdns.conf 

Yes 

DNS hijacking mapping configuration for more specific arguments for control.  

/dksoft/conf/target.conf 

 

Configuration about targets. Operator’s watchlist of subscriber identifiers (MAC or PPPoE) 

/dksoft/conf/target_mac.conf 

 

Shadow file of target list. 

/dksoft/conf/ssluserid.conf  

 

Read by postapi.bin, not in the archive by default. Traffic sniffing and data exfiltration playbook 

/dksoft/conf/appname.conf 

 

Configuration that lets the implant classify traffic for apps and attach rich context before sending it to C2 or using it in hijack/redirect logic. 

/dksoft/conf/retry.conf 

 

The rules to define what traffic for retry 

/dksoft/conf/black.conf 

Yes 

The config file for blocking traffic 

/dksoft/conf/white.conf 

 

The config file for approving traffic 

/dksoft/conf/datacenter.conf 

 

mapping of UUID in URL&IP for the postAPI module. 

/dksoft/conf/sslmm.cfg 

 

Config for the sslmm HAproxy module. 

/dksoft/conf/hosts 

 

DNS list for triggering rules 

Certificate 

Fingerprint=78:47:E0:0E:9C:0A:60:80:A6:48:CE:97:7F:30:63:7E:8A:D5:22:97:EA:10:8E:5F:CB:E9:87:48:49:BC:A5:47 

Certificate: 

    Data: 

        Version: 3 (0x2) 

        Serial Number: 

            c7:d6:08:d3:74:d1:a8:0e 

        Signature Algorithm: sha256WithRSAEncryption 

        Issuer: C=CN, ST=beijing, L=beijng, O=BEIJING JINGDONG SHANKE, OU=BEIJING JINGDONG SHANKE, CN=*.jd.com 

        Validity 

            Not Before: Jan  9 01:38:16 2020 GMT 

            Not After : Jan  4 01:38:16 2040 GMT 

        Subject: C=CN, ST=beijing, L=beijing, O=BEIJING JINGDONG SHANKE, OU=BEIJING JINGDONG SHANKE, CN=*.jd.com 

        Subject Public Key Info: 

            Public Key Algorithm: rsaEncryption 

Fingerprint=80:BC:19:8B:A9:E9:0E:62:50:4B:21:EC:69:2F:87:30:3B:7D:75:E7:A8:95:06:D3:0B:FA:52:18:57:23:3D:72 

Certificate: 

    Data: 

        Version: 3 (0x2) 

        Serial Number: 

            c0:5d:fd:b4:4c:28:07:72 

        Signature Algorithm: sha256WithRSAEncryption 

        Issuer: C=CN, ST=Sichuan, L=Chengdu, O=Default Company Ltd 

        Validity 

            Not Before: Sep 20 06:43:37 2018 GMT 

            Not After : Aug 27 06:43:37 2118 GMT 

        Subject: C=CN, ST=Sichuan, L=Chengdu, O=Default Company Ltd 

        Subject Public Key Info: 

            Public Key Algorithm: rsaEncryption 

Coverage 

The following ClamAV signature detects and blocks this threat: 

  • Win.Trojan.Shadowpad-10010830-1 
  • Win.Loader.WizardNet-10044819-0 
  • Win.Trojan.DarkNimbus-10059255-0  
  • Win.Trojan.DKnife-10059257-0 
  • Unix.Trojan.DKnife-10059259-0   
  • Win.Trojan.DKnife-10059260-0   

The following Snort rules cover this threat: 

  • Snort 2 – 65533
  • Snort 3 – 65533

Indicators of Compromise (IoCs) 

IOCs for this research can also be found at our GitHub repository here.

Cisco Talos Blog – ​Read More

OfferUp scammers are out in force: Here’s what you should know

The mobile marketplace app has a growing number of users, but not all of them are genuine. Watch out for these common scams.

WeLiveSecurity – ​Read More

Malicious use of virtual machine infrastructure

Bulletproof hosting providers are abusing the legitimate ISPsystem infrastructure to supply virtual machines to cybercriminals

Categories: Threat Research

Tags: virtual machine, cybercrime, Ransomware, ISPs

Sophos Blogs – ​Read More

Ransomware Attacks Have Surged 30% Since Q4 2025

ransomware groups in Q4 2025

Ransomware groups claimed more than 2,000 attacks in the last three months of 2025 – and they’re starting 2026 at the same elevated pace. 

Cyble recorded 2,018 claimed attacks by ransomware groups in the fourth quarter of 2025, an average of just under 673 a month. The threat groups maintained that pace in January 2026, claiming 679 ransomware victims. 

By comparison, in the first nine months of 2025, ransomware groups averaged 512 claimed victims a month, so the trend in the last four months has been more than 30% above the previous nine-month period. The chart below shows ransomware attacks by month since 2021. 

ransomware attacks by year 2021-2026

Qilin Leads All Ransomware Groups as CL0P Returns 

Qilin once again led all ransomware groups, with 115 claimed attacks in January. A resurgent CL0P has claimed scores of victims in the last two weeks, yet as of this writing had provided no technical details on the group’s latest campaign. Akira once again remained among the leaders with 76 claimed victims, while newcomers Sinobi and The Gentlemen rounded out the top five (chart below). 

ransomware groups distribution

The U.S. once again was the most attacked country by a significant margin, accounting for just under half of all ransomware attacks in January (chart below). The UK and Australia experienced higher-than-usual attack volumes; CL0P’s recent campaign was a factor in both of those increases. 

ransomware groups country wise attacks

Construction, professional services, and manufacturing continue to lead the sectors hit by ransomware attacks, likely due to opportunistic threat actors targeting vulnerable environments (chart below). The IT industry also remains a frequent target of ransomware groups, likely due to the rich target the sector represents and the potential to pivot into downstream customer environments.

industry wise attacks by ransomware groups

Recent Ransomware Attacks 

Here are some of the most significant ransomware attacks that occurred in January, several of which had supply chain implications. Additional details will be provided in Cyble’s forthcoming January 2026 Threat Landscape Report, which will be published in the Research Reports section. 

As CL0P tends to claim victims in clusters, such as its exploitation of Oracle E-Business Suite flaws that helped drive supply chain attacks to records in October, new campaigns by the group are noteworthy. Among the claimed victims in the latest campaign have been 11 Australia-based companies spanning a broad range of sectors such as IT and IT services, banking and financial services (BFSI), construction, hospitality, professional services, and healthcare.  

Other claimed victims have included a U.S.-based IT services and staffing company, a global hotel company, a major media firm, a UK payment processing company, and a Canada-based mining company engaged in platinum group metals production. 

The Everest ransomware group claimed responsibility for breaching a major U.S. manufacturer of telecommunications networking equipment and claimed to have exfiltrated 11 GB of data. Everest claims the data includes PDF documents containing sensitive engineering materials, such as electrical schematics, block diagrams, and service subsystem documentation.  

Additional directories reportedly contain .brd files, which are printed circuit board (PCB) layout files detailing information critical to hardware manufacturing and replication. The group also shared multiple samples showing internal directories, engineering blueprints, and 3D design-related materials. 

The Qilin ransomware group claimed responsibility for breaching a U.S.-based airport authority responsible for managing commercial aviation operations and related services. The group shared 16 data samples as proof-of-compromise. The materials suggest access to financial documents, telehealth-related reports, internal email correspondence, scanned identification documents, non-disclosure agreements (NDAs), and other confidential agreements, suggesting exposure of sensitive administrative and operational information. 

The Sinobi ransomware group claimed a breach of an India-based IT services company providing digital transformation, cloud, ERP, and managed services. The threat group alleges the theft of more than 150 GB of data, including contracts, financial records, and customer data. Samples shared by the attackers indicate access to internal infrastructure, including Microsoft Hyper-V servers, multiple virtual machines, backups, and storage volumes. 

The Rhysida ransomware group claimed responsibility for breaching a U.S. company providing life sciences and biotechnology instrumentation and solutions. According to the threat group, the allegedly stolen data has already been sold, though no information was provided regarding the buyer or the price at which the dataset was advertised.  

The victim was listed as directly sold rather than placed under a traditional negotiation or countdown model. Despite this, samples remain accessible and indicate exposure of email correspondence, engineering blueprints, project documentation, and non-disclosure agreements (NDAs), suggesting compromise of both technical and corporate information. 

The RansomHouse extortion group claimed responsibility for breaching a China-based electronics manufacturing company providing precision components and assembly services for global technology and automotive manufacturers. As evidence, RansomHouse published documentation indicating access to extensive proprietary engineering and production-related data. The shared materials reference confidential 3D CAD models (STEP/PRT), 2D CAD drawings (DWG/DXF), engineering documentation, printed circuit board (PCB) design data, Gerber files, electrical and layout architecture data, and manufacturing drawings. Notably, the group claims the compromised archives contain data associated with multiple major technology and automotive companies. 

INC Ransom claimed responsibility for breaching a Hong Kong–based manufacturer supplying precision components to the global electronics and automotive industries. According to the group, approximately 200 GB of data was allegedly exfiltrated. The claimed dataset reportedly includes client-related information associated with more than a dozen major global brands, plus confidential contracts and project documentation for at least three major IT companies. 

The Qilin ransomware group claimed responsibility for breaching a Taiwan-based company operating in the semiconductor and electronics manufacturing sector. According to the group, approximately 275 GB of data was allegedly exfiltrated. Based on the file tree information shared by Qilin, the dataset reportedly consists of 19,822 directories and 177,551 files, suggesting broad access to internal systems. 

The Nitrogen ransomware group leaked more than 71 GB of data allegedly stolen from a U.S. company providing engineered components and systems for the automotive industry. According to the threat group, the exposed data includes sensitive corporate and technical information such as CAD drawings, accounts payable and receivable records, invoices, and balance sheet documentation. To substantiate its claims, Nitrogen published selected project blueprints and shared a file tree indicating the alleged theft of approximately 116,180 files, suggesting broad access to internal engineering and financial systems. 

The Anubis ransomware group claimed responsibility for breaching an Italian government authority responsible for the management, regulation, and development of regional maritime port operations. According to the group, the compromised data includes incident and safety reports, logistics and operational data, port infrastructure layouts, audit results, internal reports, and business correspondence. 

New Ransomware Groups 

Among new ransomware groups that have emerged recently, Green Blood has launched an onion-based data leak site. While the group has not yet publicly named specific victims, it claims that affected organizations are located in India, Senegal, and Colombia. The group provides TOX ID and email-based communication channels for victim contact. Notably, malware samples associated with Green Blood have been observed in the wild. The ransomware encrypts files using the “.tgbg” extension and drops a ransom note titled “!!!READ_ME_TO_RECOVER_FILES!!!.txt” 

A new ransomware-as-a-service (RaaS) operation named DataKeeper has surfaced, promoting an updated affiliate model referred to as CrystalPartnership RaaS. The group claims this approach improves trust by splitting ransom payments directly between the operator’s and affiliate’s Bitcoin addresses at the time of payment, removing reliance on centralized payout handling. DataKeeper is advertised as a Windows-focused ransomware toolkit. The operation claims to use a hybrid encryption scheme combining symmetric file encryption with RSA-4096 key protection, unique per-build identifiers, and TOR-based payment links. Encryption and decryption workflows are tied to a victim-specific ID, with decryption requiring delivery of a key file following payment.  

The group emphasizes operational features such as in-memory execution, multithreaded encryption, optional shadow copy removal, network share targeting, and evading security controls. 

The threat actor (TA) MonoLock announced a new RaaS operation on the RAMP cybercrime forum (the forum has since been seized by the FBI). MonoLock’s core design is based on Beacon Object Files (BoF), enabling full in-memory execution, reduced payload exposure, and centralized control from a single post-exploitation command-and-control (C2) instance without dropping files.  

While BoF usage is common in Windows environments, MonoLock introduced a custom Linux ELF-based BoF loader, derived from the TrustedSec ELFLoader, adding chained execution, command packing, encryption, and in-memory deployment. The group promotes a “Zero Panel” extortion model, explicitly rejecting leak sites and Tor-based negotiation panels.  

MonoLock claims that avoiding public extortion infrastructure reduces law enforcement exposure and leverages silence as negotiation pressure, minimizing reputational damage for victims. Affiliates are recruited under a 20% revenue share with a USD $500 registration fee, alongside a limited referral program running from January 11 to March 31. 

Conclusion 

The persistently high level of ransomware attacks – and the emergence of new ransomware groups eager to compete on features and price – highlight the urgent need for security teams to adopt a defense-in-depth cyber strategy. Cybersecurity best practices that can help build resilience against attacks include: 

  • Protecting web-facing assets. 

  • Segmenting networks and critical assets. 

  • Hardening endpoints and infrastructure. 

  • Strong access controls, allowing no more access than is required, with frequent verification. 

  • A strong source of user identity and authentication, including multi-factor authentication and biometrics, as well as machine authentication with device compliance and health checks. 

  • Encryption of data at rest and in transit. 

  • Ransomware-resistant backups that are immutable, air-gapped, and isolated as much as possible. 

  • Honeypots that lure attackers to fake assets for early breach detection. 

  • Proper configuration of APIs and cloud service connections. 

  • Monitoring for unusual and anomalous activity with SIEM, Active Directory monitoring, endpoint security, and data loss prevention (DLP) tools. 

  • Routinely assessing and confirming controls through audits, vulnerability scanning, and penetration tests. 

Cyble’s comprehensive attack surface management solutions can help by scanning network and cloud assets for exposures and prioritizing fixes, in addition to monitoring for leaked credentials and other early warning signs of major cyberattacks. 

Additionally, Cyble’s third-party risk intelligence can help organizations carefully vet partners and suppliers, providing an early warning of potential risks. 

The post Ransomware Attacks Have Surged 30% Since Q4 2025 appeared first on Cyble.

Cyble – ​Read More

Release Notes: Workflow Improvements, MISP Integration & 2,000+ New Detections 

First month of the year, and we’re starting it off with updates that support faster decisions and more predictable SOC operations. 

In January, we introduced a major workflow enhancement with the new ANY.RUN Sandbox integration with MISP, alongside expanded detection coverage across behavior signatures, YARA rules, and Suricata. 

Let’s find out what this means for your team. 

Product Updates 

January brought another solid round of improvements focused on practical SOC workflows: faster alert validation, less manual back-and-forth, and earlier decisions that help stop incidents from growing into bigger problems. 

The main highlight of the month was the release of the ANY.RUN Sandbox integration with MISP; an important step for teams that use MISP daily for threat intelligence and investigations. 

ANY.RUN x MISP: Boost Your Triage & Response 

Most SOC teams spend too much time validating alerts, moving samples between tools, and filling in missing context. When execution evidence is separated from threat intelligence platforms, investigations slow down, MTTR increases, and SLAs come under pressure. 

With the ANY.RUN Sandbox integration for MISP, analysts can now bring real execution behavior directly into MISP, turning it from a passive intelligence repository into an active investigation layer. 

MISP integration with ANY.RUN Sandbox
MISP “Phishing attempt” event enriched with ANY.RUN Sandbox and phishing-related tags

Using native MISP modules, suspicious files and URLs can be sent straight from MISP into the ANY.RUN Sandbox, without any context switching or manual handoffs.  

You can easily integrate the modules, using the following links: 

Analysis runs automatically using Automated Interactivity. This allows the sandbox to behave like a real user by clicking, opening files, and waiting when needed. This is critical for exposing modern threats that delay execution or hide behind user-driven actions. 

MITRE ATT&CK technique T1082 expanded inside MISP
MITRE ATT&CK technique T1082 expanded inside MISP, displaying its description and related metadata 

Once execution completes, results are automatically returned to MISP, including, verdict and risk assessment, extracted IOCs, adirect link to the interactive sandbox session, HTML analysis report, mapped MITRE ATT&CK techniques and tactics. 

This allows analysts to validate alerts using real behavior, not assumptions, directly inside their existing workflow. 

Add behavior-based evidence to your MISP

Cut triage time and reduce noise



Reach out for details 


Benefits for Your SOC and Business 

For organizations using MISP as part of daily operations, this integration delivers clear operational gains: 

  • Lower incident costs: Shorter investigations reduce effort per case 
  • Reduced MTTR: Faster validation and response limit business impact 
  • Stronger SLA performance: Helps MSSPs meet response time and quality commitments 
  • No extra headcount: Scale investigation capacity without growing the team 
  • Zero integration overhead: No custom development required when MISP is already in use 
TI Feeds contribute to your company’s proactive defense
TI Feeds contribute to your company’s proactive defense and help you catch attacks early 

To support proactive coverage at scale, ANY.RUN Threat Intelligence Feeds deliver verified malicious network IOCs from real attacks across 15,000+ organizations, in STIX/TAXII format, ready for use in MISP, SIEM, or SOAR platforms. 

Learn more about TI Feeds integration with MISP 

  • Early detection with continuously updated indicators 
  • 99% unique indicators for broader coverage 
  • Verified data to reduce false positives 
  • Improved correlation across campaigns 
  • Less manual enrichment work for the team 

Improve early detection at scale

Get fresh IOCs from over 15k+ orgs



Contact us 


Threat Coverage Update 

In January, our team continued expanding the detection layer across sandbox execution, behavioral analytics, and network visibility, reinforcing ANY.RUN as a unified operational solution for detection, validation, and response. 

This month’s updates include: 

  • 158 new behavior signatures were added to strengthen coverage across ransomware and loader activity, plus common attacker tradecraft, helping security teams spot malicious intent earlier in execution. 
  • 4 new YARA rules went live in production, improving classification and hunting coverage for active malware and tooling seen in recent investigations. 
  • 1,897 new Suricata rules were deployed, expanding network visibility for phishing infrastructure (including PhaaS URL patterns), backdoor C2 attempts, and stealer-related HTTP traffic. 

Together, these updates help security teams move faster from alert to decision, without switching tools or waiting for late-stage indicators. 

New Behavior Signatures  

January’s behavior signature updates focus on early-stage execution signals and hands-on attacker activity, helping teams identify malicious intent before payloads fully deploy or damage occurs. 

Petty ransomware analyzed inside ANY.RUN’s Interactive Sandbox 
Petty ransomware detonated inside ANY.RUN’s Interactive Sandbox 

The new detections expand coverage across ransomware families, loaders, stealers, and post-exploitation techniques, with particular attention to abuse of native Windows tooling and suspicious command-line behavior often seen in real-world intrusions. 

This month, our team added signatures that detect: 

Malware and loader execution patterns, such as 

Suspicious use of built-in Windows tools, including 

Persistence and system modification techniques, such as 

Remote access and administrative tools observed in malicious contexts, including 

Mutex- and pattern-based detections, including 

New YARA Rules 

In January, 4 new YARA rules went live in production, expanding detection and hunting coverage inside ANY.RUN, especially useful when teams need quick classification and reliable pivots during triage. 

Anubis analyzed inside ANY.RUN sandbox 
Anubis detected inside ANY.RUN sandbox 

Highlighted additions include: 

These rules help security teams tag and cluster related samples faster, validate whether a file matches known patterns, and speed up investigation workflows without relying on a single indicator type. 

New Suricata Rules  

Our team deployed 1,897 new Suricata rules to expand network-level visibility into phishing infrastructure, backdoor communication, and stealer-related traffic patterns. These detections help teams identify malicious activity even when payloads are fileless, heavily obfuscated, or delivered through multi-stage web flows. 

Highlighted additions include: 

  • VShell backdoor C2 connection (sid:85005789): Identifies attempts by a fileless Go-based backdoor to establish communication with its C2 infrastructure 
  • SantaStealer HTTP activity (sid:84000895): Detects malware C2 communication based on specific artifacts present in outbound HTTP requests 

About ANY.RUN 

ANY.RUN is a core part of modern security operations, helping organizations make faster, more confident decisions across the full investigation lifecycle, from early alert validation to deep analysis and continuous threat awareness. 

By exposing real attacker behavior in real time, ANY.RUN adds the context that alerts often lack and keeps detections aligned with how threats actually operate in the wild. This allows SOC teams to reduce noise, shorten response times, and focus effort where it matters most. 

Today, more than 600,000 security specialists and 15,000 organizations worldwide rely on ANY.RUN to accelerate triage, limit unnecessary escalations, and stay ahead of fast-moving phishing and malware campaigns 

Integrate ANY.RUN’s solution for Tier 1/2/3 in your organization → 

The post Release Notes: Workflow Improvements, MISP Integration & 2,000+ New Detections  appeared first on ANY.RUN’s Cybersecurity Blog.

ANY.RUN’s Cybersecurity Blog – ​Read More

Sophos Protected Browser Early Access and FAQ

Categories: Products & Services

Tags: Workspace

Sophos Blogs – ​Read More

The Week in Vulnerabilities: Open-Sources Fixes Urged by Cyble

Top IT vulnerabilities this week

Cyble Vulnerability Intelligence researchers tracked 1,147 vulnerabilities in the last week, and more than 128 of the disclosed vulnerabilities already have a publicly available Proof-of-Concept (PoC), significantly increasing the likelihood of real-world attacks. 

A total of 108 vulnerabilities were rated as critical under the CVSS v3.1 scoring system, while 54 received a critical severity rating based on the newer CVSS v4.0 scoring system. 

Below are some of the IT vulnerabilities flagged by Cyble threat intelligence researchers for prioritization by security teams in recent reports to clients. 

The Week’s Top IT Vulnerabilities 

Cyble’s network of honeypot sensors detected attack attempts on CVE-2025-68613, a critical remote code execution flaw in the n8n open-source workflow automation platform. Workflow expressions supplied by authenticated users could execute in an insufficiently isolated context under the Improper Control of Dynamically-Managed Code Resources flaw, potentially enabling arbitrary code execution with n8n privileges and potential full system compromise. The issue is fixed in versions 1.120.4, 1.121.1, and 1.122.0. 

Vulnerabilities generating discussion in open-source communities included CVE-2025-8088, a high-severity path traversal vulnerability in WinRAR that exploits Alternate Data Streams (ADS) in crafted RAR archives. The vulnerability was added to CISA’s Known Exploited Vulnerabilities (KEV) catalog last August, but recent reports reveal that multiple actors, including nation-state adversaries and financially motivated groups, are exploiting the flaw to establish initial access and deploy a diverse array of payloads. 

Also under active discussion is CVE-2025-15467, a critical stack buffer overflow in OpenSSL’s CMS (Cryptographic Message Syntax) AuthEnvelopedData parsing when using AEAD ciphers like AES-GCM. OpenSSL 3.6, 3.5, 3.4, 3.3 and 3.0 are vulnerable to the issue, while FIPS modules and OpenSSL 1.1.1 and 1.0.2 are not. 

Among the recent additions to CISA’s Known Exploited Vulnerabilities (KEV) catalog were CVE-2026-24858, an authentication bypass vulnerability in Fortinet products; CVE-2025-68645, a Local File Inclusion (LFI) vulnerability in the Webmail Classic UI of Zimbra Collaboration Suite (ZCS); and CVE-2026-1281, an Ivanti Endpoint Manager Mobile (EPMM) Code Injection vulnerability. 

CVE-2026-24061 is another recent CISA KEV addition, a critical authentication bypass vulnerability in GNU Inetutils telnetd. The flaw lies in the improper neutralization of argument delimiters, specifically allowing an attacker to inject the “-f root” value into the USER environment variable. After successful exploitation, a remote unauthenticated attacker can bypass authentication mechanisms to gain immediate root-level access to the system over the network. Cyble dark web researchers have observed threat actors on underground forums discussing weaponizing the vulnerability. 

Another vulnerability under discussion by threat actors on the dark web is CVE-2025-27237, a high-severity local privilege escalation vulnerability affecting Zabbix Agent and Agent 2 on Windows. The vulnerability is caused by an uncontrolled search path that loads the OpenSSL configuration file from a directory writable by low-privileged users. By modifying this configuration file and injecting a malicious DLL, a local attacker could elevate their privileges to the SYSTEM level on the affected Windows host. 

CVE-2026-22794, a critical authentication bypass vulnerability in Appsmith, is also under active discussion by threat actors. The flaw occurs because the application trusts a user-controlled HTTP “Origin” header during security-sensitive workflows, such as password resets. An attacker could use this to generate fraudulent links that, when clicked by a victim, send secret authentication tokens to an attacker-controlled domain, enabling full account takeover of any user, including administrators. 

Among industrial control system (ICS) vulnerabilities of note, Festo Didactic SE MES PCs shipped with Windows 10 include a copy of XAMPP that contains around 140 vulnerabilities from third-party open-source applications, CISA said in a recent advisory. The issues can be fixed by replacing XAMPP with Festo Didactic’s Factory Control Panel application. 

Conclusion 

The high number of number of open-source vulnerabilities this week highlights the ever-present threat of software supply chain attacks, requiring constant vigilance by both security and development teams. Best practices aimed at reducing cyber risk and improving resilience include: 

  • Protecting web-facing assets.  

  • Segmenting networks and critical assets.  

  • Hardening endpoints and infrastructure.  

  • Strong access controls, allowing no more access than is required, with frequent verification.  

  • A strong source of user identity and authentication, including multi-factor authentication and biometrics, as well as machine authentication with device compliance and health checks.  

  • Encryption of data at rest and in transit.  

  • Ransomware-resistant backups that are immutable, air-gapped, and isolated as much as possible.  

  • Honeypots that lure attackers to fake assets for early breach detection.  

  • Proper configuration of APIs and cloud service connections.  

  • Monitoring for unusual and anomalous activity with SIEM, Active Directory monitoring, endpoint security, and data loss prevention (DLP) tools.  

  • Routinely assessing and confirming controls through audits, vulnerability scanning, and penetration tests.  

Cyble’s comprehensive attack surface management solutions can help by scanning network and cloud assets for exposures and prioritizing fixes, in addition to monitoring for leaked credentials and other early warning signs of major cyberattacks.  

Additionally, Cyble’s third-party risk intelligence can help organizations carefully vet partners and suppliers, providing an early warning of potential risks. 

The post The Week in Vulnerabilities: Open-Sources Fixes Urged by Cyble appeared first on Cyble.

Cyble – ​Read More

Enterprise Phishing: How Attackers Abuse Microsoft & Google Platforms 

ANY.RUN observes a growing trend of phishing kit infrastructure being hosted on legitimate cloud and CDN platforms, rather than on newly registered domains. These campaigns often target enterprise users specifically, creating a global threat to businesses. The shift createsserious visibility challenges for security teams, as trusted platforms and valid indicators shield malicious activity from detection. 

For a deeper dive, read on and see the breakdown of such cases, along with tips on what works and what doesn’t. 

Key Takeaways 

  • Modern phishing campaigns increasingly rely on trusted cloud infrastructure, not disposable domains. 
  • Cloudflare, Microsoft Azure, Google Firebase, and AWS are frequently abused. 
  • Traditional IOCs like IPs, TLS fingerprints, and certificates are becoming unreliable

Enterprises Under Fire: AITM kits and Cloudflare Abuse 

The most widespread and dangerous phishing campaigns today are powered by AiTM (Adversary-in-the-middle kits). These toolsets help unfold phishing attacks where threat actors become a proxy between the victim and a legitimate service. 

Multi-stage attack unraveled inside ANY.RUN sandbox 

A typical phishkit attack starts with an email containing a link (including in the form of a QR code) leading to attackers’ infrastructure. Most campaigns also involve a CAPTCHA challenge and a string of redirects as a means to avoid detection by AVs and static systems.Advanced evasion leads to a high rate of missed attacks for organizations that suffer from data theft as a result of this. 

ANY.RUN’s Interactive Sandbox ensures fast detection of phishing attacks 

ANY.RUN’s Interactive Sandbox provides security teams with the capabilities to quickly detect phishkit attacks thanks to interactive analysis. In addition to static detection, the sandbox lets SOC analysts safely follow the entire attack chain in an isolated VM and go past all the evasion layers to reveal the final malicious credential theft page or payload. 

The result for businesses that have adopted ANY.RUN’s solutions in their infrastructure is a lower risk of a data breach and a more effective SOC team that can quickly identify phishing attempts with a high degree of certainty. 

Faster decisions and lower workload:
Cut investigation time in half with ANY.RUN



Integrate in your SOC 


The top three most active phishing kits remain stable quarter to quarter. The list features: 

  • Tycoon2FA: Phishing-as-a-service (PhaaS) platform designed to bypass multi-factor authentication (MFA). 
  • Sneaky2FA: Adversary-in-the-Middle (AiTM) threat used in Business Email Compromise (BCE) attacks. 
  • EvilProxy: Reverse-proxy phishing kit, often used for account takeover attacks aimed at high-ranking executives. 

Mostly these campaigns are hosted behind Cloudflare CDN infrastructure. You can find live examples using Threat Intelligence Lookup with queries like these: 

threatName:”tycoon” AND destinationIpAsn:”cloudflarenet” 

Threat Intelligence Lookup results for Tycoon threats abusing Cloudflare 

Use TI Lookup to strengthen alert triage and proactive threat hunting: 

  • Accelerate detection and response: Correlate alerts with real-time threat intelligence to reduce triage time and missed threats. 
  • Improve threat visibility: Gain deeper insight into emerging malware and attack trends across industries. 
  • Stay ahead of risk: Proactively monitor relevant threats with automated alerts and expert intelligence reports. 

Power your threat hunting with TI Lookup
Intelligence from 15K SOCs and 600K analysts 



Get live intel


Why Treat Actors Choose Cloudflare 

For threat actors, Cloudflare abuse offers critical advantages: 

  • Complicated detection: Cloudflare operates as both a CDN and reverse proxy. The real origin server (often a VPS) gets hidden behind Cloudflare’s IP addresses. SOC analysts only see trusted Cloudflare ASN, valid HTTPS, and ordinary CDN traffic. The original IP can’t be scanned, blocked, or easily linked to other campaigns. 
  • Resistance to blocking and takedowns: Cloudflare’s IPs are nearly impossible to block without significant disruption. If a malicious domain is taken down, threat actors can register a new own right away and hide it behind Cloudflare just the same, without changing the basic infrastructure. 
  • Built-in anti-analysis techniques: Even in mass mailing cases, the CDN helps sustain the activity and lowers the risk of VPS’s takedown. It also provides easy-to-use anti-analysis and access control techniques, such as CAPTCHA, Turnstile, geo fencing, ASN and User-Agent filtering, and blocking of automated scanners and sandboxes. 

Because TLS termination happens at Cloudflare, SSL certificates and TLS session’s fingerprints like JA3S lose value as indicators for SOC analysts. IP- and TLS-based detection becomes inefficient, and the only remaining leads for analysts are domains and their reputation. 

Implications and Recommendations for Decison-Makers 

  • Attackers increasingly rely on trusted platforms to evade detection, reflecting cloud-based phishing growth to a mainstream technique. 
  • In many cases, there’s a clear intent to target large companies specifically. 
  • Traditional detection methods and static IOCs aren’t sufficient for a strong defense strategy. 
  • Effective detection requires non-stop monitoring of phishing campaigns, as well as constantly updated signature databases. 
Business impact powered by ANY.RUN 

Interactive sandboxing combined with threat intelligence solutions enable analysts to uncover evasive phishing threats and helps achieve: 

  • Early warning through global intelligence: Learn from real-world incidents across industries to anticipate threats before they reach your organization. 
  • Faster, more confident triage: Enrich alerts with proven historical evidence to reduce false positives and unnecessary escalations. 
  • Deeper visibility into real threats: Observe malicious behavior as it unfolds to uncover evasive techniques that static analysis often misses. 
  • Operational efficiency at scale: Eliminate manual correlation across multiple sources and streamline investigations within a single workflow. 
  • Stronger SOC performance: Support analysts at all levels while accelerating the full security operations lifecycle, from detection to response. 
The result is measurable:
+62.7% more threats detected overall
94% of surveyed users report faster triage
63% year-over-year user growth, driven by analyst efficiency
30% fewer alerts require escalation to senior analysts

ANY.RUN delivers measurable SOC outcomes
via dynamic analysis and extended threat coverage 



Reach out for Enterprise access 


Modern Phishing: No Longer Seen by the Naked Eye 

Until recently, a typical phishing attack looked like this: 

View analysis 

The malicious intent here is obvious if you take a look at the domain  

As shown above, the login form is hosted on a newly registered domain, not legitimate Microsoft 365 one (e.g., windows[.]net, microsoftonline[.]com, office[.]net, or live[.]com). This clearly indicates phishing. 

VirtusTotal provides no information on this domain 

But modern phishing threats are significantly more complex and therefore dangerous. In many cases, even the domain name stops being a reliable IOC. That’s what can be observed in this sample: 

View analysis 

A malicious Tycoon2FA sample on a legitimate Microsoft Blob Storage domain 

In this analysis, login form is hosted on legitimate Microsoft Azure Blob Storage, complicating the chance of detection. This sample belongs to Tycoon2FA, which we’ve discussed in detail in this article. 

Immediate phishing detection with ANY.RUN Sandbox 
See the full attack chain in seconds



Get started


In the POST request below, the victim’s encrypted password is transmitted from Microsoft Azure page to an attacker-controlled server: 

POST request used by attackers to steal the password 

The response from a malicious reserve proxy returns a “wrong password” message, mimicking Microsoft’s legitimate authentication flow. 

“Wrong password” error message appears after password input 

Trends: Rapid Growth of Cloud-Hosted Threats 

At the time of writing, it’s been a week the previous publication of these findings. Since then, the amount of similar phishing cases has nearly doubled. 

You can find examples of this trend on TI Lookup: 

threatName:”tycoon” AND domainName:”*.blob.core.windows.net” 

Tycoon threats abusing Microsoft storage platform are observed in numerous regions 

On average, SOC teams from the US and Europe encounter Tycoon-based phishing abusing trusted Microsoft infrastructure multiple times a day, indicating a growing rise in their activity.  

Sneaky2FA Targeting Enterprises 

Similar behavior is observed in Sneaky2FA campaigns, commonly hosted at Google Firebase Storage: 

View analysis 

Sneaky2FA threat sample hosted on Google Storage 

As well as at AWS CloudFront: 

View analysis 

Another Sneaky2FA malicious samples hosted on AWS CloudFront 

What differentiates Sneaky2FA from Tycoon2FA is its focus on large companies, not mass campaigns. The kit excludes free personal email addresses hosted on gmail.com, yahoo.com, and outlook.com, focusing only on corporate emails.  

Sneaky2FA uses a Base64-encoded domain list to filter for corporate accounts 

EvilProxy: Different Threat, Same Method 

In addition to Tycoon2FA and Sneaky2FA, EvilProxy also demonstrates similar abuse of trusted cloud platforms: 

View analysis 

EvilProxy sample hosted on legitimate Google domain 

The underlying strategy is similar and involves hiding malicious activity behind legitimate infrastructure. 

Cephas: Beyond Mainstream 

Another example of a Microsoft 365 phishing abusing a trusted cloud infrastructure was found among less common phishkits, such as Cephas.  

View analysis 

Cephas sample hosted on legitimate Microsoft storage domain 

This confirms the trend, which solidifies cloud platform abuse as a standard technique, not a one-off case. 

To find more phishing domains based on Microsoft Azure, use the following TI Lookup query: 

threatName:”phishing” AND domainName:”*blob.core.windows.net” 

Phishing samples based on Microsoft Blob Storage domain. Search in TI Lookup 

Phishing hosted on trusted cloud infrastructure is becoming increasingly widespread. The risk for large organizations grows daily, and detecting this type of attacks at early stages is made possible through continuous monitoring of phishing campaigns.  

ANY.RUN provides this visibility by delivering continuous signature updates and empowering SOC teams in 195 countries to detect sophisticated phishing threats for maximum business protection. 

About ANY.RUN 

ANY.RUN develops advanced solutions for malware analysis and threat hunting, trusted by 600,000+ cybersecurity professionals worldwide. 

Its interactive malware analysis sandbox enables hands-on investigation of threats targeting Windows, Linux, and Android environments. ANY.RUN’s Threat Intelligence Lookup and Threat Intelligence Feeds help security teams quickly identify indicators of compromise, enrich alerts with context, and investigate incidents early. Together, the solutions empowers analysts to strengthen overall security posture at enterprises.  

Request ANY.RUN access for your company  

Frequently Asked Questions (FAQ) 

What is enterprise phishing? 

Enterprise phishing refers to targeted phishing attacks aimed at corporate users, often designed to steal credentials, session cookies, or gain access to business systems rather than personal accounts. 

How do attackers abuse Microsoft and Google platforms for phishing? 

Attackers host phishing pages on legitimate services like Microsoft Azure Blob Storage, Google Firebase, and Cloudflare, allowing malicious activity to blend in with trusted cloud traffic and evade traditional detection. 

Why is cloud-hosted phishing harder to detect? 

Because these attacks use trusted domains, valid HTTPS, and well-known cloud infrastructure, common indicators such as IP addresses, TLS fingerprints, and certificates lose effectiveness. 

What are AiTM phishing kits? 

AiTM (Adversary-in-the-Middle) phishing kits act as real-time proxies between victims and legitimate services, enabling attackers to bypass MFA and steal credentials without raising obvious suspicion. 

Which phishing kits most commonly target enterprises? 

Tycoon2FA, Sneaky2FA, and EvilProxy are among the most active kits, frequently used in enterprise-focused campaigns abusing trusted cloud and CDN platforms 

Can traditional email security tools stop modern phishing attacks? 

Traditional tools alone are often insufficient, as modern phishing relies on trusted infrastructure and advanced evasion techniques that bypass static rules and reputation-based detection. 

How can organizations detect cloud-based phishing attacks early? 

Early detection requires continuous monitoring of phishing campaigns, up-to-date threat intelligence, and behavioral analysis using interactive sandboxing and real-time investigation tools like ANY.RUN. 

The post Enterprise Phishing: How Attackers Abuse Microsoft & Google Platforms  appeared first on ANY.RUN’s Cybersecurity Blog.

ANY.RUN’s Cybersecurity Blog – ​Read More

A slippery slope: Beware of Winter Olympics scams and other cyberthreats

It’s snow joke – sporting events are a big draw for cybercriminals. Make sure you’re not on the losing side by following these best practices.

WeLiveSecurity – ​Read More

How does cyberthreat attribution help in practice?

Not every cybersecurity practitioner thinks it’s worth the effort to figure out exactly who’s pulling the strings behind the malware hitting their company. The typical incident investigation algorithm goes something like this: analyst finds a suspicious file → if the antivirus didn’t catch it, puts it into a sandbox to test → confirms some malicious activity → adds the hash to the blocklist → goes for coffee break. These are the go-to steps for many cybersecurity professionals — especially when they’re swamped with alerts, or don’t quite have the forensic skills to unravel a complex attack thread by thread. However, when dealing with a targeted attack, this approach is a one-way ticket to disaster — and here’s why.

If an attacker is playing for keeps, they rarely stick to a single attack vector. There’s a good chance the malicious file has already played its part in a multi-stage attack and is now all but useless to the attacker. Meanwhile, the adversary has already dug deep into corporate infrastructure and is busy operating with an entirely different set of tools. To clear the threat for good, the security team has to uncover and neutralize the entire attack chain.

But how can this be done quickly and effectively before the attackers manage to do some real damage? One way is to dive deep into the context. By analyzing a single file, an expert can identify exactly who’s attacking his company, quickly find out which other tools and tactics that specific group employs, and then sweep infrastructure for any related threats. There are plenty of threat intelligence tools out there for this, but I’ll show you how it works using our Kaspersky Threat Intelligence Portal.

A practical example of why attribution matters

Let’s say we upload a piece of malware we’ve discovered to a threat intelligence portal, and learn that it’s usually being used by, say, the MysterySnail group. What does that actually tell us? Let’s look at the available intel:

MysterySnail group information

First off, these attackers target government institutions in both Russia and Mongolia. They’re a Chinese-speaking group that typically focuses on espionage. According to their profile, they establish a foothold in infrastructure and lay low until they find something worth stealing. We also know that they typically exploit the vulnerability CVE-2021-40449. What kind of vulnerability is that?

CVE-2021-40449 vulnerability details

As we can see, it’s a privilege escalation vulnerability — meaning it’s used after hackers have already infiltrated the infrastructure. This vulnerability has a high severity rating and is heavily exploited in the wild. So what software is actually vulnerable?

Vulnerable software

Got it: Microsoft Windows. Time to double-check if the patch that fixes this hole has actually been installed. Alright, besides the vulnerability, what else do we know about the hackers? It turns out they have a peculiar way of checking network configurations — they connect to the public site 2ip.ru:

Technique details

So it makes sense to add a correlation rule to SIEM to flag that kind of behavior.

Now’s the time to read up on this group in more detail and gather additional indicators of compromise (IoCs) for SIEM monitoring, as well as ready-to-use YARA rules (structured text descriptions used to identify malware). This will help us track down all the tentacles of this kraken that might have already crept into corporate infrastructure, and ensure we can intercept them quickly if they try to break in again.

Additional MysterySnail reports

Kaspersky Threat Intelligence Portal provides a ton of additional reports on MysterySnail attacks, each complete with a list of IoCs and YARA rules. These YARA rules can be used to scan all endpoints, and those IoCs can be added into SIEM for constant monitoring. While we’re at it, let’s check the reports to see how these attackers handle data exfiltration, and what kind of data they’re usually hunting for. Now we can actually take steps to head off the attack.

And just like that, MysterySnail, the infrastructure is now tuned to find you and respond immediately. No more spying for you!

Malware attribution methods

Before diving into specific methods, we need to make one thing clear: for attribution to actually work, the threat intelligence provided needs a massive knowledge base of the tactics, techniques, and procedures (TTPs) used by threat actors. The scope and quality of these databases can vary wildly among vendors. In our case, before even building our tool, we spent years tracking known groups across various campaigns and logging their TTPs, and we continue to actively update that database today.

With a TTP database in place, the following attribution methods can be implemented:

  1. Dynamic attribution: identifying TTPs through the dynamic analysis of specific files, then cross-referencing that set of TTPs against those of known hacking groups
  2. Technical attribution: finding code overlaps between specific files and code fragments known to be used by specific hacking groups in their malware

Dynamic attribution

Identifying TTPs during dynamic analysis is relatively straightforward to implement; in fact, this functionality has been a staple of every modern sandbox for a long time. Naturally, all of our sandboxes also identify TTPs during the dynamic analysis of a malware sample:

TTPs of a malware sample

The core of this method lies in categorizing malware activity using the MITRE ATT&CK framework. A sandbox report typically contains a list of detected TTPs. While this is highly useful data, it’s not enough for full-blown attribution to a specific group. Trying to identify the perpetrators of an attack using just this method is a lot like the ancient Indian parable of the blind men and the elephant: blindfolded folks touch different parts of an elephant and try to deduce what’s in front of them from just that. The one touching the trunk thinks it’s a python; the one touching the side is sure it’s a wall, and so on.

Blind men and an elephant

Technical attribution

The second attribution method is handled via static code analysis (though keep in mind that this type of attribution is always problematic). The core idea here is to cluster even slightly overlapping malware files based on specific unique characteristics. Before analysis can begin, the malware sample must be disassembled. The problem is that alongside the informative and useful bits, the recovered code contains a lot of noise. If the attribution algorithm takes this non-informative junk into account, any malware sample will end up looking similar to a great number of legitimate files, making quality attribution impossible. On the flip side, trying to only attribute malware based on the useful fragments but using a mathematically primitive method will only cause the false positive rate to go through the roof. Furthermore, any attribution result must be cross-checked for similarities with legitimate files — and the quality of that check usually depends heavily on the vendor’s technical capabilities.

Kaspersky’s approach to attribution

Our products leverage a unique database of malware associated with specific hacking groups, built over more than 25 years. On top of that, we use a patented attribution algorithm based on static analysis of disassembled code. This allows us to determine — with high precision, and even a specific probability percentage — how similar an analyzed file is to known samples from a particular group. This way, we can form a well-grounded verdict attributing the malware to a specific threat actor. The results are then cross-referenced against a database of billions of legitimate files to filter out false positives; if a match is found with any of them, the attribution verdict is adjusted accordingly. This approach is the backbone of the Kaspersky Threat Attribution Engine, which powers the threat attribution service on the Kaspersky Threat Intelligence Portal.

Kaspersky official blog – ​Read More