DarkSword and Coruna are two new tools for invisible attacks on iOS devices. These attacks require no user interaction and are already being actively used by bad actors in the wild. Before these threats emerged, most iPhone users didn’t have to lose sleep over their data security. Protection was really only a major concern for a narrow group — politicians, activists, diplomats, high-level business execs, and others who handle extremely sensitive data — who might be targeted by foreign intelligence agencies. We’ve covered sophisticated spyware used against such a group before — noting how hard to come by those tools were.

However, DarkSword and Coruna — discovered by researchers earlier this year — are total game-changers. This malware is being used for mass infections of everyday users. In this post, we dive into why this shift happened, why these tools are so dangerous, and how you can stay protected.

What we know about DarkSword, and how it can target your iPhone

In mid-March 2026, three separate research teams coordinated the release of their findings on a new spyware strain called DarkSword. This tool is capable of silently hacking devices running iOS 18 without the user ever knowing something is wrong.

First, we should clear up some confusion: iOS 18 isn’t as vintage as it might sound. Even though the latest version is iOS 26, Apple recently overhauled its versioning system, which threw everyone for a loop. They decided to jump ahead eight versions — from 18 straight to 26 — so the OS number matches the current year. Despite the jump, Apple estimates that about a quarter of all active devices still run iOS 18 or older.

With that cleared up, let’s get back to DarkSword. Research shows that this malware infects victims when they visit perfectly legitimate websites that have been injected with malicious code. The spyware installs itself without any user interaction at all: you just have to land on a compromised page. This is what’s known as a zero-click infection technique. Researchers report that several thousand devices have already been hit this way.

To compromise a device, DarkSword uses a six-vulnerability exploit chain to escape the sandbox, escalate privileges, and execute code. Once it’s in, the malware harvests data from the infected device, including:

• Passwords
• Photos
• Chats and data from iMessage, WhatsApp, and Telegram
• Browser history
• Information from Apple’s Calendar, Notes, and Health apps

On top of all that, DarkSword lets attackers scoop up crypto-wallet data, making it essentially dual-purpose malware that functions as both a spy tool and a way to drain your crypto.

The only bit of good news is that the spyware doesn’t survive a reboot. DarkSword is fileless malware, meaning it lives in the device’s RAM, and never actually embeds itself into the file system.

Coruna: how older iOS versions are being targeted

Just two weeks before the DarkSword findings went public, researchers flagged another iOS threat dubbed Coruna. This malware is capable of compromising devices running older software — specifically iOS 13 through 17.2.1. Coruna uses the exact same playbook as DarkSword: victims visit a legitimate site injected with malicious code which then drops the malware onto the device. The whole process is completely invisible and requires zero user interaction.

A deep dive into Coruna’s code revealed it exploits a total of 23 different iOS vulnerabilities, several of which are tucked away in Apple’s WebKit. It’s worth reminding that, generally speaking (outside the EU), all iOS browsers are required to use the WebKit engine. This means these vulnerabilities don’t just affect Safari users — they’re a threat to anyone using a third-party browser on their iPhone as well.

The latest version of Coruna, much like DarkSword, includes modifications designed to drain crypto wallets. It also harvests photos and, in certain instances, email data. From what we can tell, stealing cryptocurrency seems to be the primary motive behind Coruna’s widespread deployment.

Who created Coruna and DarkSword — and how did they end up in the wild?

Code analysis of both tools suggests that Coruna and DarkSword were likely built by different developers. However, in both cases, we’re looking at software originally created by state-affiliated companies, possibly from the U.S. The high quality of the code points to this; these aren’t just Frankenstein kits cobbled together from random parts, but uniformly engineered exploits. Somewhere along the line, these tools leaked into the hands of cybercrime gangs.

Experts at Kaspersky’s GReAT analyzed all of Coruna’s components and confirmed that this exploit kit is actually an updated version of the framework used in Operation Triangulation. That earlier attack targeted Kaspersky employees, a story we covered in detail on this blog.

One theory suggests an employee at the company that developed Coruna sold it to hackers. Since then, the malware has been used to drain crypto wallets belonging to users in China; experts estimate that at least 42 000 devices were infected there alone.

As for DarkSword, cybercriminals have already used it to compromise users in Saudi Arabia, Turkey, and Malaysia. The problem is exacerbated by the fact that the attackers who first deployed DarkSword left the full source code on infected websites, meaning it could easily be picked up by other criminal groups.

The code also includes detailed comments in English explaining exactly what each component does, which supports the theory of its Western origins. These step-by-step instructions make it easy for other hackers to adapt the tool for their own purposes.

How to protect yourself from Coruna and DarkSword

Serious malware that allows for the mass infection of iPhones while requiring zero interaction from the user has now landed in the hands of an essentially unlimited pool of cybercriminals. To pick up Coruna or DarkSword, you simply have to visit the wrong site at the wrong time. So this is one of those cases where every user needs to take iOS security seriously — not just those in high-risk groups.

The best thing you can do to protect yourself from Coruna and DarkSword is to update your devices to the latest version of iOS or iPadOS 26, as soon as you can. If you can’t update to the newest software — for instance, if your device is older and doesn’t support iOS 26 — you should still install the latest version available to you. Specifically, look for versions 15.8.7, 16.7.15, or 18.7.7. In a rare move, Apple patched a wide range of older operating systems.

To protect your Apple devices from similar malware that will likely pop up in the future, we recommend the following:

• Install updates promptly on all your Apple devices. The company regularly releases OS versions that patch known vulnerabilities — don’t skip them.
• Enable Background Security Improvements. This feature allows your device to receive critical security fixes separately from full iOS updates, reducing the window for hackers to exploit vulnerabilities. To enable it, go to Settings → Privacy & Security → Background Security Improvements and turn on the Automatically Install
• Consider using Lockdown Mode. This is a heightened security setting that limits some device features but simultaneously blocks or significantly complicates attacks. To enable this, go to Settings → Privacy & Security → Lockdown Mode → Turn On Lockdown Mode.
• Reboot your device once a day (or more). This stops fileless malware in its tracks, since these threats aren’t embedded in the system and disappear after a restart.
• Use encrypted storage for sensitive data. Keep things like crypto wallet keys, photos of IDs, and confidential info in a secure vault. Kaspersky Password Manager is a great fit for this; it manages your passwords, two-factor authentication tokens, and passkeys across all your devices while also keeping your notes, photos, and docs synced and encrypted.

The idea that Apple devices are bulletproof is a myth. They’re vulnerable to zero-click attacks, Trojans, and ClickFix infection techniques — and we’ve even seen malicious apps slip into the App Store more than once. Read more here:

• Predator vs. iPhone: the art of invisible surveillance
• AirBorne: Attacks on Apple devices through vulnerabilities in AirPlay
• Are your Bluetooth headphones spying on you?
• SparkCat trojan stealer infiltrates App Store and Google Play, steals data from photos
• Banshee: A stealer targeting macOS users

Introduction

On March 4, 2026, Google and iVerify published reports about a highly sophisticated exploit kit targeting Apple iPhone devices. According to Google, the exploit kit was first discovered in targeted attacks conducted by a customer of an unnamed surveillance vendor. It was later used by other attackers in watering-hole attacks in Ukraine and in financially motivated attacks in China. Additionally, researchers discovered an instance with the debug version of the exploit kit, which revealed the internal names of the exploits and the framework name used by its developers — Coruna. Analysis of the kit showed that it relies on the exploitation of many previously patched vulnerabilities and also includes exploits for CVE-2023-32434 and CVE-2023-38606. These two vulnerabilities particularly caught our attention because they had been first discovered as zero-days used in Operation Triangulation.

Operation Triangulation is a complex mobile APT campaign targeting iOS devices. We discovered it while monitoring the network traffic of our own corporate Wi-Fi network. We noticed suspicious activity that originated from several iOS-based phones. Following the investigation, we learned that this campaign employed a sophisticated spyware implant and multiple zero-day exploits. The investigation lasted for over six months, during which we disclosed our findings in connection to the attack. Kaspersky GReAT experts also presented these findings at the 37th Chaos Communication Congress (37C3).

Although all the details of both CVE-2023-32434 and CVE-2023-38606 have long been publicly available, and other researchers have developed their own exploits without ever seeing the Triangulation code, we decided to closely investigate the exploits used in Coruna. Some of the exploit kit distribution links provided by Google remained active at the time the report was published, which allowed us to collect, decrypt, and analyze all components of Coruna.

During our analysis, we discovered that the kernel exploit for CVE-2023-32434 and CVE-2023-38606 vulnerabilities used in Coruna, in fact, is an updated version of the same exploit that had been used in Operation Triangulation. The images below illustrate a high-level overview of the two attack chains. The exploit in question is highlighted with a red rectangle.

Moreover, we discovered that Coruna includes four additional kernel exploits that we had not seen used in Operation Triangulation, two of which were developed after the discovery of Operation Triangulation. All of these exploits are built on the same kernel exploitation framework and share common code. Code similarities from kernel exploits can also be found in other components of Coruna. These findings led us to conclude that this exploit kit was not patchworked but rather designed with a unified approach. We assume that it’s an updated version of the same exploitation framework that was used — at least to some extent — in Operation Triangulation.

Technical details

While we continue to investigate all exploits and vulnerabilities used by Coruna, this post provides a high-level overview of the exploit kit and attack chain.

Safari

Exploitation begins with a stager that fingerprints the browser and selects and executes appropriate remote code execution (RCE) and pointer authentication code (PAC) exploits depending on the browser version. It also contains a URL to an encrypted file with information about all available packages containing exploits and other components. The stager also includes a 256-bit key used to decrypt it. The URL and decryption key are passed to a payload embedded in PAC exploits.

Payload

The payload is responsible for initiating the exploitation of the kernel. After initialization, the payload first downloads a file with information about other available components. To extract it, the payload performs several steps processing multiple file formats.

First, the downloaded file is decrypted using the ChaCha20 stream cipher. Decryption yields a container with the magic number 0xBEDF00D, which stores LZMA-compressed data.

The file format used by the exploit kit to store compressed data

Offset	Field
0x00	Magic number (0xBEDF00D)
0x04	Decompressed data size
0x08	LZMA-compressed data

The decompressed data presents another container with the magic number 0xF00DBEEF. This file format is used in the exploit kit to store and retrieve files by their IDs.

The file format used by the exploit kit to store files

Offset	Field
0x00	Magic number (0xF00DBEEF)
0x04	Number of entries
0x08	Entry[0].File ID
0x0C	Entry[0].Status
0x10	Entry[0].File offset
0x14	Entry[0].File size

We provide a description of all possible File ID values below. At this stage, when the payload gathers information about all available file packages, this container holds only one file, and its File ID is 0x70000.

Finally, we get to the file with information about all available file packages. It starts with the magic value 0x12345678. The exploit kit uses this file format to obtain URLs and decryption keys for additional components that need to be downloaded.

The file format used by the exploit kit to store information about file packages

Offset	Field
0x00	Magic number (0x12345678)
0x04	Flags
0x08	Directory path
0x108	Number of entries
0x10C	Entry[0].Package ID
0x110	Entry[0].ChaCha20 key
0x130	Entry[0].File name

The components required for exploiting a targeted device are selected using the Package ID. Its high byte specifies the package type and required hardware. We’ve seen the following package types:

• 0xF2 – exploit for ARM64,
• 0xF3 – exploit for ARM64E,
• 0xA2 – Mach-O loader for ARM64,
• 0xA3 – Mach-O loader for ARM64E,
• 2 – implant for ARM64,
• 0xE2 – implant for ARM64E.

The payload code also supports additional package types, such as 0xF1, an exploit for older ARM devices that do not support 64-bit architecture. Interestingly, however, the files for such exploits are missing.

Other bytes of the Package ID define the supported firmware version and CPU generation.

Some of the observed Package IDs (those with unique content)

Package ID	Description
0xF3300000	Kernel exploit (iOS < 14.0 beta 7) and other components
0xF3400000	Kernel exploit (iOS < 14.7) and other components
0xF3700000	Kernel exploit (iOS < 16.5 beta 4) and other components
0xF3800000	Kernel exploit (iOS < 16.6 beta 5) and other components
0xF3900000	Kernel exploit (iOS < 17.2) and other components
0xA3030000	Mach-O loader (iOS 16.X) (A13 – A16)
0xA3050000	Mach-O loader (iOS 16.0 – 16.4)

The files inside these packages are also stored in encrypted and compressed 0xF00DBEEF containers, but this time compression is optional and is determined by the second bit in the Flags field. Different packages contain different sets of files. A description of all possible File IDs is given in the table below.

Observed File IDs

File ID	Description
0x10000	Implant
0x50000	Mach-O loader (default)
0x70000	List of additional components
0x70005	Launcher config
0x80000	Launcher in 0xF2/0xF3 packages, or Mach-O loader in 0xA2/0xA3
0x90000	Kernel exploit
0x90001	Kernel exploit (for Mach-O loader)
0xA0000	Logs cleaner
0xA0001	Mach-O loader component
0xA0002	Mach-O loader component
0xF0000	RPC stager

After downloading the necessary components, the payload begins executing kernel exploits, Mach-O loaders, and the malware launcher. The payload selects an appropriate Mach-O loader based on the firmware version, CPU, and presence of the iokit-open-service permission.

Kernel exploits

We analyzed all five kernel exploits from the kit and discovered that one of them is an updated version of the same exploit we discovered in Operation Triangulation. There are many small changes, but the most noticeable are as follows:

• The code takes into account more values ​​from XNU version strings, allowing for more accurate version checking.
• Added a check for iOS 17.2. We assume that this was the latest version of iOS at the time of development (released in December 2023).
• Added checks for newer Apple processors: A17, M3, M3 Pro, M3 Max (released in fall 2023).
• Added a check for iOS version 16.5 beta 4. This version patched the exploit after our report to Apple.

Why does the exploit need to check for iOS 17.2 and newer CPUs if the targeted vulnerabilities were fixed in iOS 16.5 beta 4? The answer can be found by examining other exploits: they are all based on the same source code. The only difference is in the vulnerabilities they exploit, so these checks were added to support the newer exploits and appeared in the older version after recompilation.

Launcher

The launcher is responsible for orchestrating the post-exploitation activities. It also uses the kernel exploit and the interface it provides. However, since the exploit creates special kernel objects during its execution that provide the ability to read and write to kernel memory, the launcher simply reuses these objects without the need to trigger vulnerabilities and go through the entire exploitation path again. The launcher cleans up exploitation artifacts, retrieves the process name for injection from a config with the 0xDEADD00F magic number, injects a stager into the target process, uses it to execute itself, and launches the implant.

Conclusions

This case demonstrates once again the dangers associated with such malicious tools that lie in their potential wide usage. Originally developed for cyber-espionage purposes, this framework is now being used by cybercriminals of a broader kind, placing millions of users with unpatched devices at risk. Given its modular design and ease of reuse, we expect that other threat actors will begin incorporating it into their attacks. We strongly recommend that users install the latest security updates as soon as possible, if they have not already done so.

Introduction

On March 4, 2026, Google and iVerify published reports about a highly sophisticated exploit kit targeting Apple iPhone devices. According to Google, the exploit kit was first discovered in targeted attacks conducted by a customer of an unnamed surveillance vendor. It was later used by other attackers in watering-hole attacks in Ukraine and in financially motivated attacks in China. Additionally, researchers discovered an instance with the debug version of the exploit kit, which revealed the internal names of the exploits and the framework name used by its developers — Coruna. Analysis of the kit showed that it relies on the exploitation of many previously patched vulnerabilities and also includes exploits for CVE-2023-32434 and CVE-2023-38606. These two vulnerabilities particularly caught our attention because they had been first discovered as zero-days used in Operation Triangulation.

Operation Triangulation is a complex mobile APT campaign targeting iOS devices. We discovered it while monitoring the network traffic of our own corporate Wi-Fi network. We noticed suspicious activity that originated from several iOS-based phones. Following the investigation, we learned that this campaign employed a sophisticated spyware implant and multiple zero-day exploits. The investigation lasted for over six months, during which we disclosed our findings in connection to the attack. Kaspersky GReAT experts also presented these findings at the 37th Chaos Communication Congress (37C3).

Although all the details of both CVE-2023-32434 and CVE-2023-38606 have long been publicly available, and other researchers have developed their own exploits without ever seeing the Triangulation code, we decided to closely investigate the exploits used in Coruna. Some of the exploit kit distribution links provided by Google remained active at the time the report was published, which allowed us to collect, decrypt, and analyze all components of Coruna.

During our analysis, we discovered that the kernel exploit for CVE-2023-32434 and CVE-2023-38606 vulnerabilities used in Coruna, in fact, is an updated version of the same exploit that had been used in Operation Triangulation. The images below illustrate a high-level overview of the two attack chains. The exploit in question is highlighted with a red rectangle.

Moreover, we discovered that Coruna includes four additional kernel exploits that we had not seen used in Operation Triangulation, two of which were developed after the discovery of Operation Triangulation. All of these exploits are built on the same kernel exploitation framework and share common code. Code similarities from kernel exploits can also be found in other components of Coruna. These findings led us to conclude that this exploit kit was not patchworked but rather designed with a unified approach. We assume that it’s an updated version of the same exploitation framework that was used — at least to some extent — in Operation Triangulation.

Technical details

While we continue to investigate all exploits and vulnerabilities used by Coruna, this post provides a high-level overview of the exploit kit and attack chain.

Safari

Exploitation begins with a stager that fingerprints the browser and selects and executes appropriate remote code execution (RCE) and pointer authentication code (PAC) exploits depending on the browser version. It also contains a URL to an encrypted file with information about all available packages containing exploits and other components. The stager also includes a 256-bit key used to decrypt it. The URL and decryption key are passed to a payload embedded in PAC exploits.

Payload

The payload is responsible for initiating the exploitation of the kernel. After initialization, the payload first downloads a file with information about other available components. To extract it, the payload performs several steps processing multiple file formats.

First, the downloaded file is decrypted using the ChaCha20 stream cipher. Decryption yields a container with the magic number 0xBEDF00D, which stores LZMA-compressed data.

The file format used by the exploit kit to store compressed data

Offset	Field
0x00	Magic number (0xBEDF00D)
0x04	Decompressed data size
0x08	LZMA-compressed data

The decompressed data presents another container with the magic number 0xF00DBEEF. This file format is used in the exploit kit to store and retrieve files by their IDs.

The file format used by the exploit kit to store files

Offset	Field
0x00	Magic number (0xF00DBEEF)
0x04	Number of entries
0x08	Entry[0].File ID
0x0C	Entry[0].Status
0x10	Entry[0].File offset
0x14	Entry[0].File size

We provide a description of all possible File ID values below. At this stage, when the payload gathers information about all available file packages, this container holds only one file, and its File ID is 0x70000.

Finally, we get to the file with information about all available file packages. It starts with the magic value 0x12345678. The exploit kit uses this file format to obtain URLs and decryption keys for additional components that need to be downloaded.

The file format used by the exploit kit to store information about file packages

Offset	Field
0x00	Magic number (0x12345678)
0x04	Flags
0x08	Directory path
0x108	Number of entries
0x10C	Entry[0].Package ID
0x110	Entry[0].ChaCha20 key
0x130	Entry[0].File name

The components required for exploiting a targeted device are selected using the Package ID. Its high byte specifies the package type and required hardware. We’ve seen the following package types:

• 0xF2 – exploit for ARM64,
• 0xF3 – exploit for ARM64E,
• 0xA2 – Mach-O loader for ARM64,
• 0xA3 – Mach-O loader for ARM64E,
• 2 – implant for ARM64,
• 0xE2 – implant for ARM64E.

The payload code also supports additional package types, such as 0xF1, an exploit for older ARM devices that do not support 64-bit architecture. Interestingly, however, the files for such exploits are missing.

Other bytes of the Package ID define the supported firmware version and CPU generation.

Some of the observed Package IDs (those with unique content)

Package ID	Description
0xF3300000	Kernel exploit (iOS < 14.0 beta 7) and other components
0xF3400000	Kernel exploit (iOS < 14.7) and other components
0xF3700000	Kernel exploit (iOS < 16.5 beta 4) and other components
0xF3800000	Kernel exploit (iOS < 16.6 beta 5) and other components
0xF3900000	Kernel exploit (iOS < 17.2) and other components
0xA3030000	Mach-O loader (iOS 16.X) (A13 – A16)
0xA3050000	Mach-O loader (iOS 16.0 – 16.4)

The files inside these packages are also stored in encrypted and compressed 0xF00DBEEF containers, but this time compression is optional and is determined by the second bit in the Flags field. Different packages contain different sets of files. A description of all possible File IDs is given in the table below.

Observed File IDs

File ID	Description
0x10000	Implant
0x50000	Mach-O loader (default)
0x70000	List of additional components
0x70005	Launcher config
0x80000	Launcher in 0xF2/0xF3 packages, or Mach-O loader in 0xA2/0xA3
0x90000	Kernel exploit
0x90001	Kernel exploit (for Mach-O loader)
0xA0000	Logs cleaner
0xA0001	Mach-O loader component
0xA0002	Mach-O loader component
0xF0000	RPC stager

After downloading the necessary components, the payload begins executing kernel exploits, Mach-O loaders, and the malware launcher. The payload selects an appropriate Mach-O loader based on the firmware version, CPU, and presence of the iokit-open-service permission.

Kernel exploits

We analyzed all five kernel exploits from the kit and discovered that one of them is an updated version of the same exploit we discovered in Operation Triangulation. There are many small changes, but the most noticeable are as follows:

• The code takes into account more values ​​from XNU version strings, allowing for more accurate version checking.
• Added a check for iOS 17.2. We assume that this was the latest version of iOS at the time of development (released in December 2023).
• Added checks for newer Apple processors: A17, M3, M3 Pro, M3 Max (released in fall 2023).
• Added a check for iOS version 16.5 beta 4. This version patched the exploit after our report to Apple.

Why does the exploit need to check for iOS 17.2 and newer CPUs if the targeted vulnerabilities were fixed in iOS 16.5 beta 4? The answer can be found by examining other exploits: they are all based on the same source code. The only difference is in the vulnerabilities they exploit, so these checks were added to support the newer exploits and appeared in the older version after recompilation.

Launcher

The launcher is responsible for orchestrating the post-exploitation activities. It also uses the kernel exploit and the interface it provides. However, since the exploit creates special kernel objects during its execution that provide the ability to read and write to kernel memory, the launcher simply reuses these objects without the need to trigger vulnerabilities and go through the entire exploitation path again. The launcher cleans up exploitation artifacts, retrieves the process name for injection from a config with the 0xDEADD00F magic number, injects a stager into the target process, uses it to execute itself, and launches the implant.

Conclusions

This case demonstrates once again the dangers associated with such malicious tools that lie in their potential wide usage. Originally developed for cyber-espionage purposes, this framework is now being used by cybercriminals of a broader kind, placing millions of users with unpatched devices at risk. Given its modular design and ease of reuse, we expect that other threat actors will begin incorporating it into their attacks. We strongly recommend that users install the latest security updates as soon as possible, if they have not already done so.

The fourth quarter of 2025 went down as one of the most intense periods on record for high-profile, critical vulnerability disclosures, hitting popular libraries and mainstream applications. Several of these vulnerabilities were picked up by attackers and exploited in the wild almost immediately.

In this report, we dive into the statistics on published vulnerabilities and exploits, as well as the known vulnerabilities leveraged with popular C2 frameworks throughout Q4 2025.

Statistics on registered vulnerabilities

This section contains statistics on registered vulnerabilities. The data is taken from cve.org.

Let’s take a look at the number of registered CVEs for each month over the last five years, up to and including the end of 2025. As predicted in our last report, Q4 saw a higher number of registered vulnerabilities than the same period in 2024, and the year-end totals also cleared the bar set the previous year.

Total published vulnerabilities by month from 2021 through 2025 (download)

Now, let’s look at the number of new critical vulnerabilities (CVSS > 8.9) for that same period.

Total number of published critical vulnerabilities by month from 2021 to 2025< (download)

The graph shows that the volume of critical vulnerabilities remains quite substantial; however, in the second half of the year, we saw those numbers dip back down to levels seen in 2023. This was due to vulnerability churn: a handful of published security issues were revoked. The widespread adoption of secure development practices and the move toward safer languages also pushed those numbers down, though even that couldn’t stop the overall flood of vulnerabilities.

Exploitation statistics

This section contains statistics on the use of exploits in Q4 2025. The data is based on open sources and our telemetry.

Windows and Linux vulnerability exploitation

In Q4 2025, the most prevalent exploits targeted the exact same vulnerabilities that dominated the threat landscape throughout the rest of the year. These were exploits targeting Microsoft Office products with unpatched security flaws.

Kaspersky solutions detected the most exploits on the Windows platform for the following vulnerabilities:

• CVE-2018-0802: a remote code execution vulnerability in Equation Editor.
• CVE-2017-11882: another remote code execution vulnerability, also affecting Equation Editor.
• CVE-2017-0199: a vulnerability in Microsoft Office and WordPad that allows an attacker to assume control of the system.

The list has remained unchanged for years.

We also see that attackers continue to adapt exploits for directory traversal vulnerabilities (CWE-35) when unpacking archives in WinRAR. They are being heavily leveraged to gain initial access via malicious archives on the Windows operating system:

• CVE-2023-38831: a vulnerability stemming from the improper handling of objects within an archive.
• CVE-2025-6218 (formerly ZDI-CAN-27198): a vulnerability that enables an attacker to specify a relative path and extract files into an arbitrary directory. This can lead to arbitrary code execution. We covered this vulnerability in detail in our Q2 2025 report.
• CVE-2025-8088: a vulnerability we analyzed in our previous report, analogous to CVE-2025-6218. The attackers used NTFS streams to circumvent controls on the directory into which files were being unpacked.

As in the previous quarter, we see a rise in the use of archiver exploits, with fresh vulnerabilities increasingly appearing in attacks.

Below are the exploit detection trends for Windows users over the last two years.

Dynamics of the number of Windows users encountering exploits, Q1 2024 – Q4 2025. The number of users who encountered exploits in Q1 2024 is taken as 100% (download)

The vulnerabilities listed here can be used to gain initial access to a vulnerable system. This highlights the critical importance of timely security updates for all affected software.

On Linux-based devices, the most frequently detected exploits targeted the following vulnerabilities:

• CVE-2022-0847, also known as Dirty Pipe: a vulnerability that allows privilege escalation and enables attackers to take control of running applications.
• CVE-2019-13272: a vulnerability caused by improper handling of privilege inheritance, which can be exploited to achieve privilege escalation.
• CVE-2021-22555: a heap overflow vulnerability in the Netfilter kernel subsystem.
• CVE-2023-32233: another vulnerability in the Netfilter subsystem that creates a use-after-free condition, allowing for privilege escalation due to the improper handling of network requests.

Dynamics of the number of Linux users encountering exploits, Q1 2024 – Q4 2025. The number of users who encountered exploits in Q1 2024 is taken as 100% (download)

We are seeing a massive surge in Linux-based exploit attempts: in Q4, the number of affected users doubled compared to Q3. Our statistics show that the final quarter of the year accounted for more than half of all Linux exploit attacks recorded for the entire year. This surge is primarily driven by the rapidly growing number of Linux-based consumer devices. This trend naturally attracts the attention of threat actors, making the installation of security patches critically important.

Most common published exploits

The distribution of published exploits by software type in Q4 2025 largely mirrors the patterns observed in the previous quarter. The majority of exploits we investigate through our monitoring of public research, news, and PoCs continue to target vulnerabilities within operating systems.

Distribution of published exploits by platform, Q1 2025 (download)

Distribution of published exploits by platform, Q2 2025 (download)

Distribution of published exploits by platform, Q3 2025 (download)

Distribution of published exploits by platform, Q4 2025 (download)

In Q4 2025, no public exploits for Microsoft Office products emerged; the bulk of the vulnerabilities were issues discovered in system components. When calculating our statistics, we placed these in the OS category.

Vulnerability exploitation in APT attacks

We analyzed which vulnerabilities were utilized in APT attacks during Q4 2025. The following rankings draw on our telemetry, research, and open-source data.

TOP 10 vulnerabilities exploited in APT attacks, Q4 2025 (download)

In Q4 2025, APT attacks most frequently exploited fresh vulnerabilities published within the last six months. We believe that these CVEs will remain favorites among attackers for a long time, as fixing them may require significant structural changes to the vulnerable applications or the user’s system. Often, replacing or updating the affected components requires a significant amount of resources. Consequently, the probability of an attack through such vulnerabilities may persist. Some of these new vulnerabilities are likely to become frequent tools for lateral movement within user infrastructure, as the corresponding security flaws have been discovered in network services that are accessible without authentication. This heavy exploitation of very recently registered vulnerabilities highlights the ability of threat actors to rapidly implement new techniques and adapt old ones for their attacks. Therefore, we strongly recommend applying the security patches provided by vendors.

C2 frameworks

In this section, we will look at the most popular C2 frameworks used by threat actors and analyze the vulnerabilities whose exploits interacted with C2 agents in APT attacks.

The chart below shows the frequency of known C2 framework usage in attacks against users during Q4 2025, according to open sources.

TOP 10 C2 frameworks used by APTs to compromise user systems in Q4 2025 (download)

Despite the significant footprints it can leave when used in its default configuration, Sliver continues to hold the top spot among the most common C2 frameworks in our Q4 2025 analysis. Mythic and Havoc were second and third, respectively. After reviewing open sources and analyzing malicious C2 agent samples that contained exploits, we found that the following vulnerabilities were used in APT attacks involving the C2 frameworks mentioned above:

• CVE-2025-55182: a React2Shell vulnerability in React Server Components that allows an unauthenticated user to send commands directly to the server and execute them from RAM.
• CVE-2023-36884: a vulnerability in the Windows Search component that allows the execution of commands on a system, bypassing security mechanisms built into Microsoft Office applications.
• CVE-2025-53770: a critical insecure deserialization vulnerability in Microsoft SharePoint that allows an unauthenticated user to execute commands on the server.
• CVE-2020-1472, also known as Zerologon, allows for compromising a vulnerable domain controller and executing commands as a privileged user.
• CVE-2021-34527, also known as PrintNightmare, exploits flaws in the Windows print spooler subsystem, enabling remote access to a vulnerable OS and high-privilege command execution.
• CVE-2025-8088 and CVE-2025-6218 are similar directory-traversal vulnerabilities that allow extracting files from an archive to a predefined path without the archiving utility notifying the user.

The set of vulnerabilities described above suggests that attackers have been using them for initial access and early-stage maneuvers in vulnerable systems to create a springboard for deploying a C2 agent. The list of vulnerabilities includes both zero-days and well-known, established security issues.

Notable vulnerabilities

This section highlights the most noteworthy vulnerabilities that were publicly disclosed in Q4 2025 and have a publicly available description.

React2Shell (CVE-2025-55182): a vulnerability in React Server Components

We typically describe vulnerabilities affecting a specific application. CVE-2025-55182 stood out as an exception, as it was discovered in React, a library primarily used for building web applications. This means that exploiting the vulnerability could potentially disrupt a vast number of applications that rely on the library. The vulnerability itself lies in the interaction mechanism between the client and server components, which is built on sending serialized objects. If an attacker sends serialized data containing malicious functionality, they can execute JavaScript commands directly on the server, bypassing all client-side request validation. Technical details about this vulnerability and an example of how Kaspersky solutions detect it can be found in our article.

CVE-2025-54100: command injection during the execution of curl (Invoke-WebRequest)

This vulnerability represents a data-handling flaw that occurs when retrieving information from a remote server: when executing the curl or Invoke-WebRequest command, Windows launches Internet Explorer in the background. This can lead to a cross-site scripting (XSS) attack.

CVE-2025-11001: a vulnerability in 7-Zip

This vulnerability reinforces the trend of exploiting security flaws found in file archivers. The core of CVE-2025-11001 lies in the incorrect handling of symbolic links. An attacker can craft an archive so that when it is extracted into an arbitrary directory, its contents end up in the location pointed to by a symbolic link. The likelihood of exploiting this vulnerability is significantly reduced because utilizing such functionality requires the user opening the archive to possess system administrator privileges.

This vulnerability was associated with a wave of misleading news reports claiming it was being used in real-world attacks against end users. This misconception stemmed from an error in the security bulletin.

RediShell (CVE-2025-49844): a vulnerability in Redis

The year 2025 saw a surge in high-profile vulnerabilities, several of which were significant enough to earn a unique nickname. This was the case with CVE-2025-49844, also known as RediShell, which was unveiled during a hacking competition. This vulnerability is a use-after-free issue related to how the load command functions within Lua interpreter scripts. To execute the attack, an attacker needs to prepare a malicious script and load it into the interpreter.

As with any named vulnerability, RediShell was immediately weaponized by threat actors and spammers, albeit in a somewhat unconventional manner. Because technical details were initially scarce following its disclosure, the internet was flooded with fake PoC exploits and scanners claiming to test for the vulnerability. In the best-case scenario, these tools were non-functional; in the worst, they infected the system. Notably, these fraudulent projects were frequently generated using LLMs. They followed a standardized template and often cross-referenced source code from other identical fake repositories.

CVE-2025-24990: a vulnerability in the ltmdm64.sys driver

Driver vulnerabilities are often discovered in legitimate third-party applications that have been part of the official OS distribution for a long time. Thus, CVE-2025-24990 has existed within code shipped by Microsoft throughout nearly the entire history of Windows. The vulnerable driver has been shipped since at least Windows 7 as a third-party driver for Agere Modem. According to Microsoft, this driver is no longer supported and, following the discovery of the flaw, was removed from the OS distribution entirely.

The vulnerability itself is straightforward: insecure handling of IOCTL codes leading to a null pointer dereference. Successful exploitation can lead to arbitrary command execution or a system crash resulting in a blue screen of death (BSOD) on modern systems.

CVE-2025-59287: a vulnerability in Windows Server Update Services (WSUS)

CVE-2025-59287 represents a textbook case of insecure deserialization. Exploitation is possible without any form of authentication; due to its ease of use, this vulnerability rapidly gained traction among threat actors. Technical details and detection methodologies for our product suite have been covered in our previous advisories.

Conclusion and advice

In Q4 2025, the rate of vulnerability registration has shown no signs of slowing down. Consequently, consistent monitoring and the timely application of security patches have become more critical than ever. To ensure resilient defense, it is vital to regularly assess and remediate known vulnerabilities while implementing technology designed to mitigate the impact of potential exploits.

Continuous monitoring of infrastructure, including the network perimeter, allows for the timely identification of threats and prevents them from escalating. Effective security also demands tracking the current threat landscape and applying preventative measures to minimize risks associated with system flaws. Kaspersky Next serves as a reliable partner in this process, providing real-time identification and detailed mapping of vulnerabilities within the environment.

Securing the workplace remains a top priority. Protecting corporate devices requires the adoption of solutions capable of blocking malware and preventing it from spreading. Beyond basic measures, organizations should implement adaptive systems that allow for the rapid deployment of security updates and the automation of patch management workflows.

The fourth quarter of 2025 went down as one of the most intense periods on record for high-profile, critical vulnerability disclosures, hitting popular libraries and mainstream applications. Several of these vulnerabilities were picked up by attackers and exploited in the wild almost immediately.

In this report, we dive into the statistics on published vulnerabilities and exploits, as well as the known vulnerabilities leveraged with popular C2 frameworks throughout Q4 2025.

Statistics on registered vulnerabilities

This section contains statistics on registered vulnerabilities. The data is taken from cve.org.

Let’s take a look at the number of registered CVEs for each month over the last five years, up to and including the end of 2025. As predicted in our last report, Q4 saw a higher number of registered vulnerabilities than the same period in 2024, and the year-end totals also cleared the bar set the previous year.

Total published vulnerabilities by month from 2021 through 2025 (download)

Now, let’s look at the number of new critical vulnerabilities (CVSS > 8.9) for that same period.

Total number of published critical vulnerabilities by month from 2021 to 2025< (download)

The graph shows that the volume of critical vulnerabilities remains quite substantial; however, in the second half of the year, we saw those numbers dip back down to levels seen in 2023. This was due to vulnerability churn: a handful of published security issues were revoked. The widespread adoption of secure development practices and the move toward safer languages also pushed those numbers down, though even that couldn’t stop the overall flood of vulnerabilities.

Exploitation statistics

This section contains statistics on the use of exploits in Q4 2025. The data is based on open sources and our telemetry.

Windows and Linux vulnerability exploitation

In Q4 2025, the most prevalent exploits targeted the exact same vulnerabilities that dominated the threat landscape throughout the rest of the year. These were exploits targeting Microsoft Office products with unpatched security flaws.

Kaspersky solutions detected the most exploits on the Windows platform for the following vulnerabilities:

• CVE-2018-0802: a remote code execution vulnerability in Equation Editor.
• CVE-2017-11882: another remote code execution vulnerability, also affecting Equation Editor.
• CVE-2017-0199: a vulnerability in Microsoft Office and WordPad that allows an attacker to assume control of the system.

The list has remained unchanged for years.

We also see that attackers continue to adapt exploits for directory traversal vulnerabilities (CWE-35) when unpacking archives in WinRAR. They are being heavily leveraged to gain initial access via malicious archives on the Windows operating system:

• CVE-2023-38831: a vulnerability stemming from the improper handling of objects within an archive.
• CVE-2025-6218 (formerly ZDI-CAN-27198): a vulnerability that enables an attacker to specify a relative path and extract files into an arbitrary directory. This can lead to arbitrary code execution. We covered this vulnerability in detail in our Q2 2025 report.
• CVE-2025-8088: a vulnerability we analyzed in our previous report, analogous to CVE-2025-6218. The attackers used NTFS streams to circumvent controls on the directory into which files were being unpacked.

As in the previous quarter, we see a rise in the use of archiver exploits, with fresh vulnerabilities increasingly appearing in attacks.

Below are the exploit detection trends for Windows users over the last two years.

Dynamics of the number of Windows users encountering exploits, Q1 2024 – Q4 2025. The number of users who encountered exploits in Q1 2024 is taken as 100% (download)

The vulnerabilities listed here can be used to gain initial access to a vulnerable system. This highlights the critical importance of timely security updates for all affected software.

On Linux-based devices, the most frequently detected exploits targeted the following vulnerabilities:

• CVE-2022-0847, also known as Dirty Pipe: a vulnerability that allows privilege escalation and enables attackers to take control of running applications.
• CVE-2019-13272: a vulnerability caused by improper handling of privilege inheritance, which can be exploited to achieve privilege escalation.
• CVE-2021-22555: a heap overflow vulnerability in the Netfilter kernel subsystem.
• CVE-2023-32233: another vulnerability in the Netfilter subsystem that creates a use-after-free condition, allowing for privilege escalation due to the improper handling of network requests.

Dynamics of the number of Linux users encountering exploits, Q1 2024 – Q4 2025. The number of users who encountered exploits in Q1 2024 is taken as 100% (download)

We are seeing a massive surge in Linux-based exploit attempts: in Q4, the number of affected users doubled compared to Q3. Our statistics show that the final quarter of the year accounted for more than half of all Linux exploit attacks recorded for the entire year. This surge is primarily driven by the rapidly growing number of Linux-based consumer devices. This trend naturally attracts the attention of threat actors, making the installation of security patches critically important.

Most common published exploits

The distribution of published exploits by software type in Q4 2025 largely mirrors the patterns observed in the previous quarter. The majority of exploits we investigate through our monitoring of public research, news, and PoCs continue to target vulnerabilities within operating systems.

Distribution of published exploits by platform, Q1 2025 (download)

Distribution of published exploits by platform, Q2 2025 (download)

Distribution of published exploits by platform, Q3 2025 (download)

Distribution of published exploits by platform, Q4 2025 (download)

In Q4 2025, no public exploits for Microsoft Office products emerged; the bulk of the vulnerabilities were issues discovered in system components. When calculating our statistics, we placed these in the OS category.

Vulnerability exploitation in APT attacks

We analyzed which vulnerabilities were utilized in APT attacks during Q4 2025. The following rankings draw on our telemetry, research, and open-source data.

TOP 10 vulnerabilities exploited in APT attacks, Q4 2025 (download)

In Q4 2025, APT attacks most frequently exploited fresh vulnerabilities published within the last six months. We believe that these CVEs will remain favorites among attackers for a long time, as fixing them may require significant structural changes to the vulnerable applications or the user’s system. Often, replacing or updating the affected components requires a significant amount of resources. Consequently, the probability of an attack through such vulnerabilities may persist. Some of these new vulnerabilities are likely to become frequent tools for lateral movement within user infrastructure, as the corresponding security flaws have been discovered in network services that are accessible without authentication. This heavy exploitation of very recently registered vulnerabilities highlights the ability of threat actors to rapidly implement new techniques and adapt old ones for their attacks. Therefore, we strongly recommend applying the security patches provided by vendors.

C2 frameworks

In this section, we will look at the most popular C2 frameworks used by threat actors and analyze the vulnerabilities whose exploits interacted with C2 agents in APT attacks.

The chart below shows the frequency of known C2 framework usage in attacks against users during Q4 2025, according to open sources.

TOP 10 C2 frameworks used by APTs to compromise user systems in Q4 2025 (download)

Despite the significant footprints it can leave when used in its default configuration, Sliver continues to hold the top spot among the most common C2 frameworks in our Q4 2025 analysis. Mythic and Havoc were second and third, respectively. After reviewing open sources and analyzing malicious C2 agent samples that contained exploits, we found that the following vulnerabilities were used in APT attacks involving the C2 frameworks mentioned above:

• CVE-2025-55182: a React2Shell vulnerability in React Server Components that allows an unauthenticated user to send commands directly to the server and execute them from RAM.
• CVE-2023-36884: a vulnerability in the Windows Search component that allows the execution of commands on a system, bypassing security mechanisms built into Microsoft Office applications.
• CVE-2025-53770: a critical insecure deserialization vulnerability in Microsoft SharePoint that allows an unauthenticated user to execute commands on the server.
• CVE-2020-1472, also known as Zerologon, allows for compromising a vulnerable domain controller and executing commands as a privileged user.
• CVE-2021-34527, also known as PrintNightmare, exploits flaws in the Windows print spooler subsystem, enabling remote access to a vulnerable OS and high-privilege command execution.
• CVE-2025-8088 and CVE-2025-6218 are similar directory-traversal vulnerabilities that allow extracting files from an archive to a predefined path without the archiving utility notifying the user.

The set of vulnerabilities described above suggests that attackers have been using them for initial access and early-stage maneuvers in vulnerable systems to create a springboard for deploying a C2 agent. The list of vulnerabilities includes both zero-days and well-known, established security issues.

Notable vulnerabilities

This section highlights the most noteworthy vulnerabilities that were publicly disclosed in Q4 2025 and have a publicly available description.

React2Shell (CVE-2025-55182): a vulnerability in React Server Components

We typically describe vulnerabilities affecting a specific application. CVE-2025-55182 stood out as an exception, as it was discovered in React, a library primarily used for building web applications. This means that exploiting the vulnerability could potentially disrupt a vast number of applications that rely on the library. The vulnerability itself lies in the interaction mechanism between the client and server components, which is built on sending serialized objects. If an attacker sends serialized data containing malicious functionality, they can execute JavaScript commands directly on the server, bypassing all client-side request validation. Technical details about this vulnerability and an example of how Kaspersky solutions detect it can be found in our article.

CVE-2025-54100: command injection during the execution of curl (Invoke-WebRequest)

This vulnerability represents a data-handling flaw that occurs when retrieving information from a remote server: when executing the curl or Invoke-WebRequest command, Windows launches Internet Explorer in the background. This can lead to a cross-site scripting (XSS) attack.

CVE-2025-11001: a vulnerability in 7-Zip

This vulnerability reinforces the trend of exploiting security flaws found in file archivers. The core of CVE-2025-11001 lies in the incorrect handling of symbolic links. An attacker can craft an archive so that when it is extracted into an arbitrary directory, its contents end up in the location pointed to by a symbolic link. The likelihood of exploiting this vulnerability is significantly reduced because utilizing such functionality requires the user opening the archive to possess system administrator privileges.

This vulnerability was associated with a wave of misleading news reports claiming it was being used in real-world attacks against end users. This misconception stemmed from an error in the security bulletin.

RediShell (CVE-2025-49844): a vulnerability in Redis

The year 2025 saw a surge in high-profile vulnerabilities, several of which were significant enough to earn a unique nickname. This was the case with CVE-2025-49844, also known as RediShell, which was unveiled during a hacking competition. This vulnerability is a use-after-free issue related to how the load command functions within Lua interpreter scripts. To execute the attack, an attacker needs to prepare a malicious script and load it into the interpreter.

As with any named vulnerability, RediShell was immediately weaponized by threat actors and spammers, albeit in a somewhat unconventional manner. Because technical details were initially scarce following its disclosure, the internet was flooded with fake PoC exploits and scanners claiming to test for the vulnerability. In the best-case scenario, these tools were non-functional; in the worst, they infected the system. Notably, these fraudulent projects were frequently generated using LLMs. They followed a standardized template and often cross-referenced source code from other identical fake repositories.

CVE-2025-24990: a vulnerability in the ltmdm64.sys driver

Driver vulnerabilities are often discovered in legitimate third-party applications that have been part of the official OS distribution for a long time. Thus, CVE-2025-24990 has existed within code shipped by Microsoft throughout nearly the entire history of Windows. The vulnerable driver has been shipped since at least Windows 7 as a third-party driver for Agere Modem. According to Microsoft, this driver is no longer supported and, following the discovery of the flaw, was removed from the OS distribution entirely.

The vulnerability itself is straightforward: insecure handling of IOCTL codes leading to a null pointer dereference. Successful exploitation can lead to arbitrary command execution or a system crash resulting in a blue screen of death (BSOD) on modern systems.

CVE-2025-59287: a vulnerability in Windows Server Update Services (WSUS)

CVE-2025-59287 represents a textbook case of insecure deserialization. Exploitation is possible without any form of authentication; due to its ease of use, this vulnerability rapidly gained traction among threat actors. Technical details and detection methodologies for our product suite have been covered in our previous advisories.

Conclusion and advice

In Q4 2025, the rate of vulnerability registration has shown no signs of slowing down. Consequently, consistent monitoring and the timely application of security patches have become more critical than ever. To ensure resilient defense, it is vital to regularly assess and remediate known vulnerabilities while implementing technology designed to mitigate the impact of potential exploits.

Continuous monitoring of infrastructure, including the network perimeter, allows for the timely identification of threats and prevents them from escalating. Effective security also demands tracking the current threat landscape and applying preventative measures to minimize risks associated with system flaws. Kaspersky Next serves as a reliable partner in this process, providing real-time identification and detailed mapping of vulnerabilities within the environment.

Securing the workplace remains a top priority. Protecting corporate devices requires the adoption of solutions capable of blocking malware and preventing it from spreading. Beyond basic measures, organizations should implement adaptive systems that allow for the rapid deployment of security updates and the automation of patch management workflows.

In early 2025, security researchers uncovered a new malware family named Webrat. Initially, the Trojan targeted regular users by disguising itself as cheats for popular games like Rust, Counter-Strike, and Roblox, or as cracked software. In September, the attackers decided to widen their net: alongside gamers and users of pirated software, they are now targeting inexperienced professionals and students in the information security field.

Distribution and the malicious sample

In October, we uncovered a campaign that had been distributing Webrat via GitHub repositories since at least September. To lure in victims, the attackers leveraged vulnerabilities frequently mentioned in security advisories and industry news. Specifically, they disguised their malware as exploits for the following vulnerabilities with high CVSSv3 scores:

CVE	CVSSv3
CVE-2025-59295	8.8
CVE-2025-10294	9.8
CVE-2025-59230	7.8

This is not the first time threat actors have tried to lure security researchers with exploits. Last year, they similarly took advantage of the high-profile RegreSSHion vulnerability, which lacked a working PoC at the time.

In the Webrat campaign, the attackers bait their traps with both vulnerabilities lacking a working exploit and those which already have one. To build trust, they carefully prepared the repositories, incorporating detailed vulnerability information into the descriptions. The information is presented in the form of structured sections, which include:

• Overview with general information about the vulnerability and its potential consequences
• Specifications of systems susceptible to the exploit
• Guide for downloading and installing the exploit
• Guide for using the exploit
• Steps to mitigate the risks associated with the vulnerability

In all the repositories we investigated, the descriptions share a similar structure, characteristic of AI-generated vulnerability reports, and offer nearly identical risk mitigation advice, with only minor variations in wording. This strongly suggests that the text was machine-generated.

The Download Exploit ZIP link in the Download & Install section leads to a password-protected archive hosted in the same repository. The password is hidden within the name of a file inside the archive.

The archive downloaded from the repository includes four files:

1. pass – 8511: an empty file, whose name contains the password for the archive.
2. payload.dll: a decoy, which is a corrupted PE file. It contains no useful information and performs no actions, serving only to divert attention from the primary malicious file.
3. rasmanesc.exe (note: file names may vary): the primary malicious file (MD5 61b1fc6ab327e6d3ff5fd3e82b430315), which performs the following actions:
   • Escalate its privileges to the administrator level (T1134.002).
   • Disable Windows Defender (T1562.001) to avoid detection.
   • Fetch from a hardcoded URL (ezc5510min.temp[.]swtest[.]ru in our example) a sample of the Webrat family and execute it (T1608.001).
4. start_exp.bat: a file containing a single command: start rasmanesc.exe, which further increases the likelihood of the user executing the primary malicious file.

Webrat is a backdoor that allows the attackers to control the infected system. Furthermore, it can steal data from cryptocurrency wallets, Telegram, Discord and Steam accounts, while also performing spyware functions such as screen recording, surveillance via a webcam and microphone, and keylogging. The version of Webrat discovered in this campaign is no different from those documented previously.

Campaign objectives

Previously, Webrat spread alongside game cheats, software cracks, and patches for legitimate applications. In this campaign, however, the Trojan disguises itself as exploits and PoCs. This suggests that the threat actor is attempting to infect information security specialists and other users interested in this topic. It bears mentioning that any competent security professional analyzes exploits and other malware within a controlled, isolated environment, which has no access to sensitive data, physical webcams, or microphones. Furthermore, an experienced researcher would easily recognize Webrat, as it’s well-documented and the current version is no different from previous ones. Therefore, we believe the bait is aimed at students and inexperienced security professionals.

Conclusion

The threat actor behind Webrat is now disguising the backdoor not only as game cheats and cracked software, but also as exploits and PoCs. This indicates they are targeting researchers who frequently rely on open sources to find and analyze code related to new vulnerabilities.

However, Webrat itself has not changed significantly from past campaigns. These attacks clearly target users who would run the “exploit” directly on their machines — bypassing basic safety protocols. This serves as a reminder that cybersecurity professionals, especially inexperienced researchers and students, must remain vigilant when handling exploits and any potentially malicious files. To prevent potential damage to work and personal devices containing sensitive information, we recommend analyzing these exploits and files within isolated environments like virtual machines or sandboxes.

We also recommend exercising general caution when working with code from open sources, always using reliable security solutions, and never adding software to exclusions without a justified reason.

Kaspersky solutions effectively detect this threat with the following verdicts:

• HEUR:Trojan.Python.Agent.gen
• HEUR:Trojan-PSW.Win64.Agent.gen
• HEUR:Trojan-Banker.Win32.Agent.gen
• HEUR:Trojan-PSW.Win32.Coins.gen
• HEUR:Trojan-Downloader.Win32.Agent.gen
• PDM:Trojan.Win32.Generic

Indicators of compromise

Malicious GitHub repositories
https://github[.]com/RedFoxNxploits/CVE-2025-10294-Poc
https://github[.]com/FixingPhantom/CVE-2025-10294
https://github[.]com/h4xnz/CVE-2025-10294-POC
https://github[.]com/usjnx72726w/CVE-2025-59295/tree/main
https://github[.]com/stalker110119/CVE-2025-59230/tree/main
https://github[.]com/moegameka/CVE-2025-59230
https://github[.]com/DebugFrag/CVE-2025-12596-Exploit
https://github[.]com/themaxlpalfaboy/CVE-2025-54897-LAB
https://github[.]com/DExplo1ted/CVE-2025-54106-POC
https://github[.]com/h4xnz/CVE-2025-55234-POC
https://github[.]com/Hazelooks/CVE-2025-11499-Exploit
https://github[.]com/usjnx72726w/CVE-2025-11499-LAB
https://github[.]com/modhopmarrow1973/CVE-2025-11833-LAB
https://github[.]com/rootreapers/CVE-2025-11499
https://github[.]com/lagerhaker539/CVE-2025-12595-POC

Webrat C2
http://ezc5510min[.]temp[.]swtest[.]ru
http://shopsleta[.]ru

MD5
28a741e9fcd57bd607255d3a4690c82f
a13c3d863e8e2bd7596bac5d41581f6a
61b1fc6ab327e6d3ff5fd3e82b430315

In early 2025, security researchers uncovered a new malware family named Webrat. Initially, the Trojan targeted regular users by disguising itself as cheats for popular games like Rust, Counter-Strike, and Roblox, or as cracked software. In September, the attackers decided to widen their net: alongside gamers and users of pirated software, they are now targeting inexperienced professionals and students in the information security field.

Distribution and the malicious sample

In October, we uncovered a campaign that had been distributing Webrat via GitHub repositories since at least September. To lure in victims, the attackers leveraged vulnerabilities frequently mentioned in security advisories and industry news. Specifically, they disguised their malware as exploits for the following vulnerabilities with high CVSSv3 scores:

CVE	CVSSv3
CVE-2025-59295	8.8
CVE-2025-10294	9.8
CVE-2025-59230	7.8

This is not the first time threat actors have tried to lure security researchers with exploits. Last year, they similarly took advantage of the high-profile RegreSSHion vulnerability, which lacked a working PoC at the time.

In the Webrat campaign, the attackers bait their traps with both vulnerabilities lacking a working exploit and those which already have one. To build trust, they carefully prepared the repositories, incorporating detailed vulnerability information into the descriptions. The information is presented in the form of structured sections, which include:

• Overview with general information about the vulnerability and its potential consequences
• Specifications of systems susceptible to the exploit
• Guide for downloading and installing the exploit
• Guide for using the exploit
• Steps to mitigate the risks associated with the vulnerability

In all the repositories we investigated, the descriptions share a similar structure, characteristic of AI-generated vulnerability reports, and offer nearly identical risk mitigation advice, with only minor variations in wording. This strongly suggests that the text was machine-generated.

The Download Exploit ZIP link in the Download & Install section leads to a password-protected archive hosted in the same repository. The password is hidden within the name of a file inside the archive.

The archive downloaded from the repository includes four files:

1. pass – 8511: an empty file, whose name contains the password for the archive.
2. payload.dll: a decoy, which is a corrupted PE file. It contains no useful information and performs no actions, serving only to divert attention from the primary malicious file.
3. rasmanesc.exe (note: file names may vary): the primary malicious file (MD5 61b1fc6ab327e6d3ff5fd3e82b430315), which performs the following actions:
   • Escalate its privileges to the administrator level (T1134.002).
   • Disable Windows Defender (T1562.001) to avoid detection.
   • Fetch from a hardcoded URL (ezc5510min.temp[.]swtest[.]ru in our example) a sample of the Webrat family and execute it (T1608.001).
4. start_exp.bat: a file containing a single command: start rasmanesc.exe, which further increases the likelihood of the user executing the primary malicious file.

Webrat is a backdoor that allows the attackers to control the infected system. Furthermore, it can steal data from cryptocurrency wallets, Telegram, Discord and Steam accounts, while also performing spyware functions such as screen recording, surveillance via a webcam and microphone, and keylogging. The version of Webrat discovered in this campaign is no different from those documented previously.

Campaign objectives

Previously, Webrat spread alongside game cheats, software cracks, and patches for legitimate applications. In this campaign, however, the Trojan disguises itself as exploits and PoCs. This suggests that the threat actor is attempting to infect information security specialists and other users interested in this topic. It bears mentioning that any competent security professional analyzes exploits and other malware within a controlled, isolated environment, which has no access to sensitive data, physical webcams, or microphones. Furthermore, an experienced researcher would easily recognize Webrat, as it’s well-documented and the current version is no different from previous ones. Therefore, we believe the bait is aimed at students and inexperienced security professionals.

Conclusion

The threat actor behind Webrat is now disguising the backdoor not only as game cheats and cracked software, but also as exploits and PoCs. This indicates they are targeting researchers who frequently rely on open sources to find and analyze code related to new vulnerabilities.

However, Webrat itself has not changed significantly from past campaigns. These attacks clearly target users who would run the “exploit” directly on their machines — bypassing basic safety protocols. This serves as a reminder that cybersecurity professionals, especially inexperienced researchers and students, must remain vigilant when handling exploits and any potentially malicious files. To prevent potential damage to work and personal devices containing sensitive information, we recommend analyzing these exploits and files within isolated environments like virtual machines or sandboxes.

We also recommend exercising general caution when working with code from open sources, always using reliable security solutions, and never adding software to exclusions without a justified reason.

Kaspersky solutions effectively detect this threat with the following verdicts:

• HEUR:Trojan.Python.Agent.gen
• HEUR:Trojan-PSW.Win64.Agent.gen
• HEUR:Trojan-Banker.Win32.Agent.gen
• HEUR:Trojan-PSW.Win32.Coins.gen
• HEUR:Trojan-Downloader.Win32.Agent.gen
• PDM:Trojan.Win32.Generic

Indicators of compromise

Malicious GitHub repositories
https://github[.]com/RedFoxNxploits/CVE-2025-10294-Poc
https://github[.]com/FixingPhantom/CVE-2025-10294
https://github[.]com/h4xnz/CVE-2025-10294-POC
https://github[.]com/usjnx72726w/CVE-2025-59295/tree/main
https://github[.]com/stalker110119/CVE-2025-59230/tree/main
https://github[.]com/moegameka/CVE-2025-59230
https://github[.]com/DebugFrag/CVE-2025-12596-Exploit
https://github[.]com/themaxlpalfaboy/CVE-2025-54897-LAB
https://github[.]com/DExplo1ted/CVE-2025-54106-POC
https://github[.]com/h4xnz/CVE-2025-55234-POC
https://github[.]com/Hazelooks/CVE-2025-11499-Exploit
https://github[.]com/usjnx72726w/CVE-2025-11499-LAB
https://github[.]com/modhopmarrow1973/CVE-2025-11833-LAB
https://github[.]com/rootreapers/CVE-2025-11499
https://github[.]com/lagerhaker539/CVE-2025-12595-POC

Webrat C2
http://ezc5510min[.]temp[.]swtest[.]ru
http://shopsleta[.]ru

MD5
28a741e9fcd57bd607255d3a4690c82f
a13c3d863e8e2bd7596bac5d41581f6a
61b1fc6ab327e6d3ff5fd3e82b430315

Introduction

Imagine you’re cruising down the highway in your brand-new electric car. All of a sudden, the massive multimedia display fills with Doom, the iconic 3D shooter game. It completely replaces the navigation map or the controls menu, and you realize someone is playing it remotely right now. This is not a dream or an overactive imagination – we’ve demonstrated that it’s a perfectly realistic scenario in today’s world.

The internet of things now plays a significant role in the modern world. Not only are smartphones and laptops connected to the network, but also factories, cars, trains, and even airplanes. Most of the time, connectivity is provided via 3G/4G/5G mobile data networks using modems installed in these vehicles and devices. These modems are increasingly integrated into a System-on-Chip (SoC), which uses a Communication Processor (CP) and an Application Processor (AP) to perform multiple functions simultaneously. A general-purpose operating system such as Android can run on the AP, while the CP, which handles communication with the mobile network, typically runs on a dedicated OS. The interaction between the AP, CP, and RAM within the SoC at the microarchitecture level is a “black box” known only to the manufacturer – even though the security of the entire SoC depends on it.

Bypassing 3G/LTE security mechanisms is generally considered a purely academic challenge because a secure communication channel is established when a user device (User Equipment, UE) connects to a cellular base station (Evolved Node B, eNB). Even if someone can bypass its security mechanisms, discover a vulnerability in the modem, and execute their own code on it, this is unlikely to compromise the device’s business logic. This logic (for example, user applications, browser history, calls, and SMS on a smartphone) resides on the AP and is presumably not accessible from the modem.

To find out, if that is true, we conducted a security assessment of a modern SoC, Unisoc UIS7862A, which features an integrated 2G/3G/4G modem. This SoC can be found in various mobile devices by multiple vendors or, more interestingly, in the head units of modern Chinese vehicles, which are becoming increasingly common on the roads. The head unit is one of a car’s key components, and a breach of its information security poses a threat to road safety, as well as the confidentiality of user data.

During our research, we identified several critical vulnerabilities at various levels of the Unisoc UIS7862A modem’s cellular protocol stack. This article discusses a stack-based buffer overflow vulnerability in the 3G RLC protocol implementation (CVE-2024-39432). The vulnerability can be exploited to achieve remote code execution at the early stages of connection, before any protection mechanisms are activated.

Importantly, gaining the ability to execute code on the modem is only the entry point for a complete remote compromise of the entire SoC. Our subsequent efforts were focused on gaining access to the AP. We discovered several ways to do so, including leveraging a hardware vulnerability in the form of a hidden peripheral Direct Memory Access (DMA) device to perform lateral movement within the SoC. This enabled us to install our own patch into the running Android kernel and execute arbitrary code on the AP with the highest privileges. Details are provided in the relevant sections.

Acquiring the modem firmware

The modem at the center of our research was found on the circuit board of the head unit in a Chinese car.

Description of the circuit board components:

Number in the board photo	Component
1	Realtek RTL8761ATV 802.11b/g/n 2.4G controller with wireless LAN (WLAN) and USB interfaces (USB 1.0/1.1/2.0 standards)
2	SPRD UMW2652 BGA WiFi chip
3	55966 TYADZ 21086 chip
4	SPRD SR3595D (Unisoc) radio frequency transceiver
5	Techpoint TP9950 video decoder
6	UNISOC UIS7862A
7	BIWIN BWSRGX32H2A-48G-X internal storage, Package200-FBGA, ROM Type – Discrete, ROM Size – LPDDR4X, 48G
8	SCY E128CYNT2ABE00 EMMC 128G/JEDEC memory card
9	SPREADTRUM UMP510G5 power controller
10	FEI.1s LE330315 USB2.0 shunt chip
11	SCT2432STER synchronous step-down DC-DC converter with internal compensation

Using information about the modem’s hardware, we desoldered and read the embedded multimedia memory card, which contained a complete image of its operating system. We then analyzed the image obtained.

Remote access to the modem (CVE-2024-39431)

The modem under investigation, like any modern modem, implements several protocol stacks: 2G, 3G, and LTE. Clearly, the more protocols a device supports, the more potential entry points (attack vectors) it has. Moreover, the lower in the OSI network model stack a vulnerability sits, the more severe the consequences of its exploitation can be. Therefore, we decided to analyze the data packet fragmentation mechanisms at the data link layer (RLC protocol).

We focused on this protocol because it is used to establish a secure encrypted data transmission channel between the base station and the modem, and, in particular, it is used to transmit higher-layer NAS (Non-Access Stratum) protocol data. NAS represents the functional level of the 3G/UMTS protocol stack. Located between the user equipment (UE) and core network, it is responsible for signaling between them. This means that a remote code execution (RCE) vulnerability in RLC would allow an attacker to execute their own code on the modem, bypassing all existing 3G communication protection mechanisms.

The RLC protocol uses three different transmission modes: Transparent Mode (TM), Unacknowledged Mode (UM), and Acknowledged Mode (AM). We are only interested in UM, because in this mode the 3G standard allows both the segmentation of data and the concatenation of several small higher-layer data fragments (Protocol Data Units, PDU) into a single data link layer frame. This is done to maximize channel utilization. At the RLC level, packets are referred to as Service Data Units (SDU).

Among the approximately 75,000 different functions in the firmware, we found the function for handling an incoming SDU packet. When handling a received SDU packet, its header fields are parsed. The packet itself consists of a mandatory header, optional headers, and data. The number of optional headers is not limited. The end of the optional headers is indicated by the least significant bit (E bit) being equal to 0. The algorithm processes each header field sequentially, while their E-bits equal 1. During processing, data is written to a variable located on the stack of the calling function. The stack depth is 0xB4 bytes. The size of the packet that can be parsed (i.e., the number of headers, each header being a 2-byte entry on the stack) is limited by the SDU packet size of 0x5F0 bytes.

As a result, exploitation can be achieved using just one packet in which the number of headers exceeds the stack depth (90 headers). It is important to note that this particular function lacks a stack canary, and when the stack overflows, it is possible to overwrite the return address and some non-volatile register values in this function. However, overwriting is only possible with a value ending in one in binary (i.e., a value in which the least significant bit equals 1). Notably, execution takes place on ARM in Thumb mode, so all return addresses must have the least significant bit equal to 1. Coincidence? Perhaps.

In any case, sending the very first dummy SDU packet with the appropriate number of “correct” headers caused the device to reboot. However, at that moment, we had no way to obtain information on where and why the crash occurred (although we suspect the cause was an attempt to transfer control to the address 0xAABBCCDD, taken from our packet).

Gaining persistence in the system

The first and most important observation is that we know the pointer to the newly received SDU packet is stored in register R2. Return Oriented Programming (ROP) techniques can be used to execute our own code, but first we need to make sure it is actually possible.

We utilized the available AT command handler to move the data to RAM areas. Among the available AT commands, we found a suitable function – SPSERVICETYPE.

Next, we used ROP gadgets to overwrite the address 0x8CE56218 without disrupting the subsequent operation of the incoming SDU packet handling algorithm. To achieve this, it was sufficient to return to the function from which the SDU packet handler was called, because it was invoked as a callback, meaning there is no data linkage on the stack. Given that this function only added 0x2C bytes to the stack, we needed to fit within this size.

Having found a suitable ROP chain, we launched an SDU packet containing it as a payload. As a result, we saw the output 0xAABBCCDD in the AT command console for SPSERVICETYPE. Our code worked!

Next, by analogy, we input the address of the stack frame where our data was located, but it turned out not to be executable. We then faced the task of figuring out the MPU settings on the modem. Once again, using the ROP chain method, we generated code that read the MPU table, one DWORD at a time. After many iterations, we obtained the following table.

The table shows what we suspected – the code section is only mapped for execution. An attempt to change the configuration resulted in another ROP chain, but this same section was now mapped with write permissions in an unused slot in the table. Because of MPU programming features, specifically the presence of the overlap mechanism and the fact that a region with a higher ID has higher priority, we were able to write to this section.

All that remained was to use the pointer to our data (still stored in R2) and patch the code section that had just been unlocked for writing. The question was what exactly to patch. The simplest method was to patch the NAS protocol handler by adding our code to it. To do this, we used one of the NAS protocol commands – MM information. This allowed us to send a large amount of data at once and, in response, receive a single byte of data using the MM status command, which confirmed the patching success.

As a result, we not only successfully executed our own code on the modem side but also established full two-way communication with the modem, using the high-level NAS protocol as a means of message delivery. In this case, it was an MM Status packet with the cause field equaling 0xAA.

However, being able to execute our own code on the modem does not give us access to user data. Or does it?

The full version of the article with a detailed description of the development of an AR exploit that led to Doom being run on the head unit is available on ICS CERT website.

Introduction

Imagine you’re cruising down the highway in your brand-new electric car. All of a sudden, the massive multimedia display fills with Doom, the iconic 3D shooter game. It completely replaces the navigation map or the controls menu, and you realize someone is playing it remotely right now. This is not a dream or an overactive imagination – we’ve demonstrated that it’s a perfectly realistic scenario in today’s world.

The internet of things now plays a significant role in the modern world. Not only are smartphones and laptops connected to the network, but also factories, cars, trains, and even airplanes. Most of the time, connectivity is provided via 3G/4G/5G mobile data networks using modems installed in these vehicles and devices. These modems are increasingly integrated into a System-on-Chip (SoC), which uses a Communication Processor (CP) and an Application Processor (AP) to perform multiple functions simultaneously. A general-purpose operating system such as Android can run on the AP, while the CP, which handles communication with the mobile network, typically runs on a dedicated OS. The interaction between the AP, CP, and RAM within the SoC at the microarchitecture level is a “black box” known only to the manufacturer – even though the security of the entire SoC depends on it.

Bypassing 3G/LTE security mechanisms is generally considered a purely academic challenge because a secure communication channel is established when a user device (User Equipment, UE) connects to a cellular base station (Evolved Node B, eNB). Even if someone can bypass its security mechanisms, discover a vulnerability in the modem, and execute their own code on it, this is unlikely to compromise the device’s business logic. This logic (for example, user applications, browser history, calls, and SMS on a smartphone) resides on the AP and is presumably not accessible from the modem.

To find out, if that is true, we conducted a security assessment of a modern SoC, Unisoc UIS7862A, which features an integrated 2G/3G/4G modem. This SoC can be found in various mobile devices by multiple vendors or, more interestingly, in the head units of modern Chinese vehicles, which are becoming increasingly common on the roads. The head unit is one of a car’s key components, and a breach of its information security poses a threat to road safety, as well as the confidentiality of user data.

During our research, we identified several critical vulnerabilities at various levels of the Unisoc UIS7862A modem’s cellular protocol stack. This article discusses a stack-based buffer overflow vulnerability in the 3G RLC protocol implementation (CVE-2024-39432). The vulnerability can be exploited to achieve remote code execution at the early stages of connection, before any protection mechanisms are activated.

Importantly, gaining the ability to execute code on the modem is only the entry point for a complete remote compromise of the entire SoC. Our subsequent efforts were focused on gaining access to the AP. We discovered several ways to do so, including leveraging a hardware vulnerability in the form of a hidden peripheral Direct Memory Access (DMA) device to perform lateral movement within the SoC. This enabled us to install our own patch into the running Android kernel and execute arbitrary code on the AP with the highest privileges. Details are provided in the relevant sections.

Acquiring the modem firmware

The modem at the center of our research was found on the circuit board of the head unit in a Chinese car.

Description of the circuit board components:

Number in the board photo	Component
1	Realtek RTL8761ATV 802.11b/g/n 2.4G controller with wireless LAN (WLAN) and USB interfaces (USB 1.0/1.1/2.0 standards)
2	SPRD UMW2652 BGA WiFi chip
3	55966 TYADZ 21086 chip
4	SPRD SR3595D (Unisoc) radio frequency transceiver
5	Techpoint TP9950 video decoder
6	UNISOC UIS7862A
7	BIWIN BWSRGX32H2A-48G-X internal storage, Package200-FBGA, ROM Type – Discrete, ROM Size – LPDDR4X, 48G
8	SCY E128CYNT2ABE00 EMMC 128G/JEDEC memory card
9	SPREADTRUM UMP510G5 power controller
10	FEI.1s LE330315 USB2.0 shunt chip
11	SCT2432STER synchronous step-down DC-DC converter with internal compensation

Using information about the modem’s hardware, we desoldered and read the embedded multimedia memory card, which contained a complete image of its operating system. We then analyzed the image obtained.

Remote access to the modem (CVE-2024-39431)

The modem under investigation, like any modern modem, implements several protocol stacks: 2G, 3G, and LTE. Clearly, the more protocols a device supports, the more potential entry points (attack vectors) it has. Moreover, the lower in the OSI network model stack a vulnerability sits, the more severe the consequences of its exploitation can be. Therefore, we decided to analyze the data packet fragmentation mechanisms at the data link layer (RLC protocol).

We focused on this protocol because it is used to establish a secure encrypted data transmission channel between the base station and the modem, and, in particular, it is used to transmit higher-layer NAS (Non-Access Stratum) protocol data. NAS represents the functional level of the 3G/UMTS protocol stack. Located between the user equipment (UE) and core network, it is responsible for signaling between them. This means that a remote code execution (RCE) vulnerability in RLC would allow an attacker to execute their own code on the modem, bypassing all existing 3G communication protection mechanisms.

The RLC protocol uses three different transmission modes: Transparent Mode (TM), Unacknowledged Mode (UM), and Acknowledged Mode (AM). We are only interested in UM, because in this mode the 3G standard allows both the segmentation of data and the concatenation of several small higher-layer data fragments (Protocol Data Units, PDU) into a single data link layer frame. This is done to maximize channel utilization. At the RLC level, packets are referred to as Service Data Units (SDU).

Among the approximately 75,000 different functions in the firmware, we found the function for handling an incoming SDU packet. When handling a received SDU packet, its header fields are parsed. The packet itself consists of a mandatory header, optional headers, and data. The number of optional headers is not limited. The end of the optional headers is indicated by the least significant bit (E bit) being equal to 0. The algorithm processes each header field sequentially, while their E-bits equal 1. During processing, data is written to a variable located on the stack of the calling function. The stack depth is 0xB4 bytes. The size of the packet that can be parsed (i.e., the number of headers, each header being a 2-byte entry on the stack) is limited by the SDU packet size of 0x5F0 bytes.

As a result, exploitation can be achieved using just one packet in which the number of headers exceeds the stack depth (90 headers). It is important to note that this particular function lacks a stack canary, and when the stack overflows, it is possible to overwrite the return address and some non-volatile register values in this function. However, overwriting is only possible with a value ending in one in binary (i.e., a value in which the least significant bit equals 1). Notably, execution takes place on ARM in Thumb mode, so all return addresses must have the least significant bit equal to 1. Coincidence? Perhaps.

In any case, sending the very first dummy SDU packet with the appropriate number of “correct” headers caused the device to reboot. However, at that moment, we had no way to obtain information on where and why the crash occurred (although we suspect the cause was an attempt to transfer control to the address 0xAABBCCDD, taken from our packet).

Gaining persistence in the system

The first and most important observation is that we know the pointer to the newly received SDU packet is stored in register R2. Return Oriented Programming (ROP) techniques can be used to execute our own code, but first we need to make sure it is actually possible.

We utilized the available AT command handler to move the data to RAM areas. Among the available AT commands, we found a suitable function – SPSERVICETYPE.

Next, we used ROP gadgets to overwrite the address 0x8CE56218 without disrupting the subsequent operation of the incoming SDU packet handling algorithm. To achieve this, it was sufficient to return to the function from which the SDU packet handler was called, because it was invoked as a callback, meaning there is no data linkage on the stack. Given that this function only added 0x2C bytes to the stack, we needed to fit within this size.

Having found a suitable ROP chain, we launched an SDU packet containing it as a payload. As a result, we saw the output 0xAABBCCDD in the AT command console for SPSERVICETYPE. Our code worked!

Next, by analogy, we input the address of the stack frame where our data was located, but it turned out not to be executable. We then faced the task of figuring out the MPU settings on the modem. Once again, using the ROP chain method, we generated code that read the MPU table, one DWORD at a time. After many iterations, we obtained the following table.

The table shows what we suspected – the code section is only mapped for execution. An attempt to change the configuration resulted in another ROP chain, but this same section was now mapped with write permissions in an unused slot in the table. Because of MPU programming features, specifically the presence of the overlap mechanism and the fact that a region with a higher ID has higher priority, we were able to write to this section.

All that remained was to use the pointer to our data (still stored in R2) and patch the code section that had just been unlocked for writing. The question was what exactly to patch. The simplest method was to patch the NAS protocol handler by adding our code to it. To do this, we used one of the NAS protocol commands – MM information. This allowed us to send a large amount of data at once and, in response, receive a single byte of data using the MM status command, which confirmed the patching success.

As a result, we not only successfully executed our own code on the modem side but also established full two-way communication with the modem, using the high-level NAS protocol as a means of message delivery. In this case, it was an MM Status packet with the cause field equaling 0xAA.

However, being able to execute our own code on the modem does not give us access to user data. Or does it?

The full version of the article with a detailed description of the development of an AR exploit that led to Doom being run on the head unit is available on ICS CERT website.