Business Email Compromise (BEC) operates on a familiar playbook. Threat actors breach a mailbox, silently monitor operations, map approval chains, and ultimately exploit that access to divert funds or exfiltrate sensitive assets.
This dynamic is central to our analysis as we kick off a series around Rapid7's collaborative research with Zimbra; upcoming installments will explore technical details and broader findings based within the Zimbra Collaboration Suite. Our investigation disrupted the traditional BEC model in unexpected ways. We uncovered over 50 vulnerabilities, and found that several allow attackers not just to observe environments, but to actively rewrite them by impersonating senders without credentials, controlling inbox visibility, and altering shared documents and calendars.
Business Email Compromise in action: Digital abuse of trust
None of this is theoretical for Zimbra. But donβt take my word for it, just ask Russia. CISA keeps putting Zimbra bugs into the Known Exploited Vulnerabilities catalog, and the last three years make the point on their own:
CVE-2024-45519, command injection in the postjournal service, unauthenticated command execution. Proofpoint saw attackers stuffing base64 payloads into CC fields on September 28, 2024. CISA added it to KEV on October 3.
CVE-2025-27915, stored XSS in the Classic Web Client, triggered by a crafted .ICS attachment. It is used as a zero-day against Brazilian military targets to steal mail and quietly set forwarding filters. It went into KEV in October, 2025.
CVE-2026-73570, unauthenticated command injection through SNMP notification handling. CISA added it on August 21 of this year and gave federal agencies three days. Shadowserver has been counting somewhere north of 260 compromised instances while hunting for exploitation artifacts.
Go back further and the pattern holds. Rapid7 tracked widespread exploitation of CVE-2022-27925 and CVE-2022-37042 in 2022, a path traversal chained with an authentication bypass that let attackers drop a JSP shell on a Zimbra server without credentials. Google's Threat Analysis Group later documented four separate threat groups working the same zero-day known as CVE-2023-37580. Each of these groups went after email, credentials, and authentication tokens. Attackers figured out a long time ago that the system sitting in the middle of everyone's communication is worth the effort. So when you find a set of bugs that let you write to that system instead of only reading from it, data theft stops being the interesting part.
Send an email as your CFO without ever touching their password, and you have the front half of a very convincing BEC. Keep control of the mailbox afterward and you have the back half, too. Here, the attacker has a strategic choice. They can delete the sent message to hide their tracks, effectively wiping the trail of the fraud OR they can choose to leave the message in the Sent Items folder. By doing so, they ensure the CFO sees 'evidence' of the email they supposedly sent, creating a gaslighting scenario where the victim is left questioning their own actions. Whether the attacker cleans up or leaves the trail, they are shaping the organizationβs perception of reality. In the ensuing investigation, where Finance sees a sent request and the CFO sees no such activity, the organization is trapped in a conflict of evidence. At that point, BEC looks less like traditional fraud and more like a psychological operation.
Documents make it worse, as Zimbra is not just a mail server. The collaboration side holds the files employees actually use to make decisions. An attacker who can plant a fake HR memo or financial summary in an executive's enterprise drive, and make it look like it came from a peer they trust, is starting from a much better position than someone attaching a PDF to a cold email.
Say a document shows up from HR about a confidential restructuring, and a few days later an email from a trusted executive references it. Neither piece has to carry the whole deception, as each one props up the other.
Calendar warfare and manufactured enterprise reality
Then there is the thing I have started calling βcalendar warfare.β Meetings can be modified or deleted without generating the notification trail users expect to see. RSVP status can also be flipped. Maybe a key executive is changed from Accepted to Declined and leadership might reschedule, or move ahead without them, or read the whole thing as a deliberate opt-out.
It works in the other direction too. An "Emergency Board Meeting" lands on an executive's calendar with a believable organizer, a popup reminder, and a malicious Zoom link. When the reminder fires, the victim is not sizing up a suspicious email that arrived thirty seconds ago. They are joining a meeting that has been sitting in their calendar for two days. And the calendar is not some exotic attack surface nobody has thought of. If we look back at CVE-2025-27915, the delivery vehicle was a calendar invite.
Stack all of it together now β a financial document appears, a trusted executive emails about it, then a mandatory meeting shows up to discuss it. And the attacker still has the ability to clean up some of what gets left behind. Every artifact the victim checks lives inside a system they have no reason to question, and all of them tell the same fabricated story.
I keep coming back to the phrase 'manufactured enterprise reality'. I have touched on the idea in The Monday Brief, that attackers get to borrow whatever trust an organization has already extended to its own tooling. Zimbra makes it concrete. The platform supplies the credibility, so the attacker does not have to build any.
Collaboration suites quietly became systems of record. Email is the record of who said what. Calendars are the record of who agreed to be where. Classic BEC abuses the trust between two people. The scenario weβve discussed here abuses the machinery those people use to decide who to trust in the first place. Once employees are making real business decisions off fabricated context, stealing data is the least of your problems.
Yesterday β 24 September 2026Rapid7 Cybersecurity Blog
Security teams already have long queues of potential application vulnerabilities. The useful question is what happens next: can they see how a weakness behaves in a running application, reproduce the attack, and give developers enough evidence to fix it?
Dynamic application security testing (DAST) helps answer those questions by testing applications as an attacker encounters them. The IDC MarketScape: Worldwide Dynamic Application Security Testing 2026 Vendor Assessment (Doc #US54119126, September 2026). The IDC MarketScape evaluated 16 vendors and named Rapid7 a Leader.
We believe the result reflects the strength of Rapid7βs DAST capabilities, but the IDC MarketScape also offers a useful view of where the category is heading. DAST has developed beyond traditional web scanning into a source of runtime evidence that can help organizations validate risk across the application layer.
From possible weakness to validated application risk
Code analysis and dependency scanning help teams identify weaknesses before an application is deployed. DAST provides a different view by interacting with the assembled application while it is running. It can show what happens when a particular request reaches the application, how the application responds, and whether a suspected weakness can be reproduced.
This is especially valuable for APIs and AI-backed applications, where risk may emerge through interactions among models, prompts, data, tools, and permissions. Some of these behaviors cannot be fully understood from source code or a dependency manifest. They become visible when the application is exercised under runtime conditions.
DAST therefore has a direct role in continuous threat exposure management (CTEM). Discovery gives teams a view of their assets and possible weaknesses, but that view alone does not tell them where to focus. Validation helps narrow the field by showing which exposures can be reached or exploited and providing evidence that teams can use to take action.
For Rapid7, DAST is exposure management applied to the application layer. Web applications, APIs, and AI-backed endpoints are all part of the attack surface, so they need to be discovered, tested, prioritized, and managed alongside infrastructure, cloud, and other exposures.
Why we believe Rapid7 was named a Leader by IDC
Rapid7βs DAST solution is delivered as part of the Exposure Command portfolio. Its scan engine maps an application, executes attacks against the discovered paths, and validates confirmed findings. Security teams can map a broad area of an application while limiting active attacks to an appropriate set of paths, giving them control over how testing is performed.
Findings are checked against Rapid7 telemetry to help determine which issues warrant closer attention. When a finding needs action, browser-based replay reproduces the original request, the attack request, and the triggering response. Developers receive evidence they can work with, rather than a finding they must first spend time proving.
Authenticated scanning can be difficult to maintain across a changing application portfolio, and a broken login sequence can leave important areas untested. Rapid7βs solution can identify the affected step and support a targeted update without requiring the entire sequence to be recorded again.
The connection with Surface Command adds another useful layer. Newly discovered external assets can be surfaced for application testing, helping teams close the gap between finding an application and understanding the risk it presents
DAST plays a core role within Exposure Command: providing the application-layer validation teams need to prioritize risk and move from findings to remediation.
On September 22, 2026, F5 published a security advisory for CVE-2026-94127, a critical heap-based buffer overflow vulnerability affecting F5 BIG-IP Access Policy Manager (APM). The vulnerability has a CVSS v3.1 score of 9.8. An unauthenticated attacker with network access to an affected virtual server may be able to achieve remote code execution (RCE) by sending specifically crafted traffic.
BIG-IP APM provides identity-aware access control for applications and other corporate resources and can integrate with authentication technologies including OAuth, OpenID Connect, and SAML. CVE-2026-94127 is not exposed in a default configuration: exploitation requires a BIG-IP virtual server with both an APM access policy and an OAuth profile configured. Because affected BIG-IP systems may process traffic at an organization's network edge, organizations using this configuration should prioritize remediation.
The vulnerability affects the data plane and does not expose the BIG-IP control plane. BIG-IP systems operating in Appliance mode are also affected.
F5 lists the following affected release trains and corresponding fixed hotfixes:
BIG-IP 21.1.0: versions prior to Hotfix-BIGIP-21.1.0.2.0.30.22-ENG
BIG-IP 17.5.0: versions prior to Hotfix-BIGIP-17.5.1.9.0.160.12-ENG
BIG-IP 17.1.0: versions prior to Hotfix-BIGIP-17.1.3.5.0.41.14-ENG
As of September 22, 2026, CVE-2026-94127 has been added to the CISA KEV while a publicly available proof of concept was not confirmed.
Mitigation guidance
Organizations running affected F5 BIG-IP deployments should apply the appropriate F5 hotfix as soon as operationally feasible, particularly where a vulnerable APM and OAuth configuration is reachable from untrusted networks.
F5 lists the following remediation versions:
BIG-IP 21.1.0: update to Hotfix-BIGIP-21.1.0.2.0.30.22-ENG or later.
BIG-IP 17.5.0: update to Hotfix-BIGIP-17.5.1.9.0.160.12-ENG or later.
BIG-IP 17.1.0: update to Hotfix-BIGIP-17.1.3.5.0.41.14-ENG or later.
Administrators should first determine whether a BIG-IP APM access policy and an OAuth profile are configured together on a virtual server, since this configuration is required for exposure.
For organizations that cannot immediately apply the applicable update, F5 provides an iRule workaround through F5 Support. Customers should open a support case with F5 to obtain the vendor-provided workaround and follow F5's implementation guidance.
Rapid7 customers
Exposure Command, Vulnerability Management, and Nexpose
Exposure Command, Vulnerability Management, Nexpose customers can assess exposure to CVE-2026-94127 using vulnerability checks expected to be available in todayβs (September 23) content release.
On September 14, 2026, Cisco published a security advisory for CVE-2026-76461, a critical SQL injection vulnerability affecting Cisco AsyncOS Software for Cisco Secure Email Gateway. The vulnerability has a reported CVSS v3.1 base score of 9.8 and could allow an unauthenticated, remote attacker to execute arbitrary commands with root privileges on an affected appliance.
Cisco Secure Email Gateway, formerly known as IronPort Email Security Appliance, is an enterprise email security product that inspects inbound and outbound email for threats including phishing, malware, spam, and business email compromise. Because affected gateways process externally delivered email as part of their normal operation, exploitation does not require access to an administrative interface or authentication. An attacker can reportedly trigger the vulnerability by sending a specially crafted email through a vulnerable gateway.
CVE-2026-76461 was added to CISA's Known Exploited Vulnerabilities (KEV) catalog on the same day as the vendor disclosed the vulnerability, indicating that CVE-2026-76461 was exploited as a zero-day prior to disclosure. Cisco noted that their PSIRT became aware of active exploitation in September 2026. At the time of publication, there is no public proof-of-concept exploit code available, and no attribution for the current threat actor activity.
Mitigation guidance
Organizations running Cisco Secure Email Gateway should prioritize upgrading to a vendor-supplied fixed version on an emergency basis, outside of normal patching cycles.
Affected Version
Fixed Version
15.5 and earlier
15.5.5-014
16.0
16.0.4-302
16.5
16.5.0-780
Given the reported active exploitation and the ability to achieve unauthenticated root-level command execution through malicious email processing, organizations should prioritize patching rather than relying solely on network controls or monitoring. Cisco also strongly recommends that customers migrate to the latest product version, 16.5.0-780.
For the latest remediation guidance, see the vendor advisory.
Indicators of compromise
The following indicators of compromise for CVE-2026-76461 were reported within the Cisco security advisory.
To confirm any attempted exploitation of this vulnerability, review the mail_logs and look for suspicious SQL statements. If the device is part of a cluster, review the logs of each cluster device. The following is a non-exhaustive example of how a malicious SQL statement could be detected in the logs:
cisco-esa> grep -i "COPY.*TO PROGRAM" [IronPort Text Mail Logs Log name - Default: mail_logs]
The presence of any entry in the output may indicate malicious activity.
Rapid7 customers
Exposure Command, InsightVM, and Nexpose
Exposure Command, InsightVM, and Nexpose customers can assess exposure to CVE-2026-76461 with a vulnerability check expected to be available in the September 16 content release.
The managed detection and response (MDR) market has reached a turning point. Weβve gone beyond the baseline of 24/7 monitoring focusing on the speed of detection and moved to a world with a convergence of exposure management and response to deliver measurable, outcome-based defenses of a larger, AI-driven attack surface.
For anyone evaluating MDR right now, the Managed Detection and Response Services Landscape, Q3 2026 report by Forrester is a useful map that lays out where the market is heading. This is a market that has moved beyond "do you cover my telemetry?" to βCan a provider connect and prove that its activity is tied to real reduction in risk?β.Β
Rapid7 was named among the notable providers in this Forrester MDR Landscape. Being included matters to us, but the more interesting story is in what Forrester says about the market itself.
Detection and exposure are becoming one service
One of the report's clearest signals is directional: Forrester writes that "MDR services will converge with exposure and posture improvement.β
That convergence is the whole basis of Rapid7 MDR and our Command Platform strategy. Most MDR services react after an attacker has already broken in. Rapid7 designed its service to anticipate where attackers are likely to succeed and disrupt them earlier. We combine exposure context, detection, and response into a single operational loop, where vulnerability findings and asset risk scoring flow directly into alerts and investigations. This means analysts can cut noise and focus response on the exposures most likely to cause business impact. It's what we mean by exposure-informed, Preemptive MDR: The same context that tells you where you're weak is the context that sharpens how you detect and respond.
For buyers, the practical implication is that old procurement habits are changing. Buyers used to invest in detection from one vendor, exposure management from another, and then hope the two solutions would seamlessly talk to each other. That approach is now turning into a liability.
The market will reward providers that connect these additions to measurable risk reduction rather than bolting on loosely joined SKUs. That's a bar customers should hold every provider to, including Rapid7.
"Make providers prove the investigation, rather than narrate the dashboard"
The second theme is about accountability. In its guidance on working with providers, Forrester is blunt: Buyers should "make providers prove the investigation, rather than narrate the dashboard." A slick activity feed is not evidence that anyone reached the right conclusion. Buyers should ask to see the reasoning behind a disposition, the actions taken, and the controls that keep automation from making unsafe decisions.
This is a healthy pressure on the whole market, and it's a test we welcome. Rapid7 MDR is delivered on Rapid7's own SIEM, which gives customers a direct window into our SOC, including validated threats, the response actions taken, where AI accelerated the work, and where a human analyst stepped in and why. Every action is logged, explainable, and auditable. As agentic AI takes on more of the investigation workload, that transparency becomes the difference between a service you trust and a black box you hope is working. Our approach is deliberately human-led and AI-enhanced: AI scales triage and investigation across large volumes of telemetry, while analysts stay responsible for validation and response decisions.
Accountability also shows up in commercial terms. Rapid7 MDR includes unlimited incident response, so the team stays engaged until an incident is fully remediated rather than stopping when a clock runs out, and gives a concrete answer to the "who owns the outcome?" question.
What to do with the report
If you're evaluating MDR, and have access to Forrester, the report is a strong prompt to rewrite your evaluation criteria. A few questions worth taking into any provider conversation:
Ask how exposure context actually enters investigations. Is it a legitimate input to detection and prioritization, or a separate dashboard?Β
Ask to see a real, redacted case file rather than a metrics summary. Then probe how the provider handles uncertainty and model failure.Β
Clarify the place where accountability sits when a response action carries risk, and get a clear answer on how far the provider remains engaged during an incident.Β
These are the same standards we hold ourselves to, and they map to how we've built our MDR service. If you want to go deeper, our MDR Buyer's Guide walks through what to look for in a partner, and you can compare Rapid7 MDR against other providers or talk to our SOC team directly.
The MDR market is one in which detection, exposure, and response stop being separate purchases and start being one accountable outcome. That's the service we set out to build, and now is a good moment for every security leader to ask whether their current provider is heading the same way.
Source: Forrester, The Managed Detection And Response Services Landscape, Q3 2026, Jeff Pollard with Joseph Blankenship, Emily Doherty, and Michael Belden, September 1, 2026. Forrester does not endorse any company, product, brand, or service included in its research publications and does not advise any person to select the products or services of any company or brand based on the ratings included in such publications. Information is based on the best available resources. Opinions reflect judgment at the time and are subject to change. This report is part of a broader collection of Forrester resources, including interactive models, frameworks, tools, data, and access to analyst guidance. For more information, read about Forresterβs objectivityΒ hereβ―.
On September 10, 2026, GitLab published a critical patch release for GitLab Community Edition (CE) and Enterprise Edition (EE). The release addresses CVE-2026-85706, a critical path traversal vulnerability (CWE-22) in the repository commits API with a CVSSv3.1 score of 10.0. According to GitLab, improper path confinement and missing authentication enforcement could allow an unauthenticated user to read arbitrary files from an affected GitLab server under certain conditions.
On September 11, 2026, CVE-2026-85706 was added to the U.S. Cybersecurity and Infrastructure Security Agency's (CISA) Known Exploited Vulnerabilities (KEV) catalog, based on evidence of active exploitation. CISA set a remediation due date of September 14, 2026, for affected Federal Civilian Executive Branch agencies and marked the vulnerability as subject to forensic triage requirements under Binding Operational Directive 26-04.
Organizations running affected self-managed GitLab instances should remediate CVE-2026-85706 on an emergency basis, outside of normal patch cycles.
Mitigation guidance
A vendor-supplied update is available to remediate CVE-2026-85706. Organizations running affected self-managed GitLab CE or EE instances should upgrade to a fixed version immediately.
Affected GitLab CE/EE versions
Fixed version
All versions from 18.7 before 19.1.8
19.1.8
All versions from 19.2 before 19.2.6
19.2.6
All versions from 19.3 before 19.3.2
19.3.2
GitLab.com is already running a patched version, and GitLab Dedicated customers do not need to take action. Per GitLab, all self-managed deployment types are affected, including Omnibus, source code, and Helm chart deployments.
The updates include database migrations. Single-node installations will experience downtime while the migrations run; multi-node deployments can use GitLab's zero-downtime upgrade procedure. Of the fixed releases, only 19.3.2 includes post-deployment migrations.
The patch release also addresses 17 other vulnerabilities. These include CVE-2026-87719, a critical insecure deserialization vulnerability (CWE-502) in GitLab EE with a CVSSv3.1 score of 9.9. GitLab states that, under certain conditions, an authenticated user with Duo Chat access could obtain Advanced Search instance configurations and sensitive credentials using a specially crafted GraphQL subscription argument. At the time of publication, only CVE-2026-85706 is known to be exploited in the wild.
Given the confirmed exploitation, Rapid7 strongly recommends looking for signs of compromise even after the update has been applied. Organizations subject to CISA's BOD 26-04 should also follow the forensic triage requirements associated with the KEV entry.
For the latest mitigation guidance, please refer to the vendor's security advisory.
Rapid7 customers
Exposure Command, InsightVM, and Nexpose
Exposure Command, InsightVM, and Nexpose customers can assess exposure to CVE-2026-85706 with a vulnerability check available in the September 15 content release.
Another banger from Metasploit with sixteen new modules, including ten exploit modules, with five on the CISA KEV list. Cisco, Papercut, Sonicwall, Jetbrains, and Langflow all have exploit modules, and not to be outdone, we even have a Metasploit scanner to watch the watchers!
New module content (16)
Elasticsearch ingest-attachment Apache Tika XFA XXE Local File Read
Authors: Bourbon Offensive Security Services and Jean-Marie Bourbon
Description: Adds an auxiliary scanner module for CVE-2025-54988/CVE-2025-66516. The module validates an XML External Entity (XXE) vulnerability in Apache Tika's XFA parser exposed through the Elasticsearch attachment ingest processor.
SPIP Unauthenticated Blind SQLi via Date Field Escaping Bypass
Authors: Benoit Hua, Franck Chevalier, Julien Voisin, and ka3n1x
Description: Adds a scanner module to enumerate ports on a host and determine if they're a Metasploit Reverse Handler or not, and if they are, what kind of shell they were going to land.
Description: This introduces native Kerberos authentication relay capabilities to the framework's relay stack. It includes a new auxiliary module (esc8_kerberos) that exploits CVE-2026-20929 by targeting AD CS Web Enrollment (ESC8). The module captures an SMB2 AP-REQ from a coerced client and seamlessly replays the authentication to the target certificate server over HTTP. This chain ultimately allows an attacker to issue a certificate for the coerced victim and obtain a valid Kerberos TGT without requiring their credentials.
Description: Adds a Linux x64 sandboxβevasion module that performs lightweight runtime environment checks and aborts execution when a likely sandbox or VM is detected.
Cisco Secure Firewall Management Center Authentication Bypass RCE
Authors: Arian Eidizadeh, Brandon Sakai, and Cale Black
Description: Adds a native Metasploit exploit module for CVE-2026-20079, an unauthenticated authentication bypass in Cisco Secure Firewall Management Center (FMC).
SonicWall SMA1000 WorkPlace SSRF to Root Remote Code Execution
Description: This adds an exploit module for the recent SonicWall SMA1000 zero-day exploit chain that was disclosed in the first week of September as being exploited in-the-wild. CVE-2026-83548 is an SSRF used to bypass auth. SMA1000-9427 is an RCE with low privileges via CouchDB read/write primitives. CVE-2026-83549 is a command injection in cmsSnmpTrap.sh for RCE with root privs. The patched version 12.5.0-02952 has been verified to successfully remediate this exploit chain.
Description: This introduces a new unauthenticated Remote Code Execution (RCE) exploit module for JetBrains TeamCity, targeting the vulnerability tracked as CVE-2026-63077. The module exploits an unsafe XStream deserialization flaw within the agent polling protocol to deliver and execute a one-shot JSP payload on the server. The module supports both Windows and Linux targets and features built-in cleanup logic to automatically unregister and remove the fake build agent created during the exploitation process.
Description: Adds a new module targeting CVE-2026-19295, an authenticated remote code execution vulnerability impacting Langflow versions 1.10.0 and below.
Description: This adds a new exploit module for CVE-2026-23744, an unauthenticated command execution vulnerability in MCPJam Inspector. The module targets the /api/mcp/connect endpoint. Vulnerable versions accept a JSON serverConfig object containing a command and args array, then use those values to start an MCP server. When MCPJam Inspector is exposed on a routable interface, an unauthenticated remote attacker can abuse this behavior to execute operating system commands as the user running MCPJam Inspector.
Description: Adds an exploit module for the recent PaperCut MF and PaperCut NG exploit chain (CVE-2026-81578 + CVE-2026-82078) that was reported last week as a zero-day being actively exploited in the wild.
Description: Adds a module targeting an unauthenticated remote code execution vulnerability in SPIP <= 4.4.21 via the forum autosave session handler. The action=session endpoint lets any visitor store arbitrary PHP code in a session variable, which is then executed by the template engine when the article page is rendered. No CVE has yet been issued.
Next.js Unauthenticated RCE on Windows Servers
Authors: Avishek Sarkar, Bogyeom Lee, and Maksim Rogov
Description: Adds a module targeting CVE-2026-75604, a Remote Code Execution (RCE) vulnerability in Next.js applications hosted on Windows servers. Specifically crafted requests can execute arbitrary code on the target server running Next.js versions from 13.4.0 up to 15.5.24, and 16.0.0 up to 16.3.3.
#21838Β fromΒ jheysel-r7Β - Fixes payload choosing behaviour when swapping targets to auto-select the most fitting payload which can now also include Java payloads.
#21853Β fromΒ PushpenderrathoreΒ - Three fixes to the core Rex::Proto::DNS forward/cache path that surface once the DNS server is used as a selective poisoner in front of a real upstream resolver
#21861Β fromΒ prithvee07Β - Fixes a recent regression in the vsftpd_234_backdoor module where by updating the module to support ARCH_CMD payloads we inadvertently dropped support for cmd/unix/interact payloads. Both payloads are now supported.
Documentation
You can find the latest Metasploit documentation on our docsite atΒ docs.metasploit.com.
Get it
As always, you can update to the latest Metasploit Framework withΒ msfupdateΒ and you can get more details on the changes since the last blog post from GitHub:
If you are aΒ gitΒ user, you can clone theΒ Metasploit Framework repoΒ (master branch) for the latest. To install fresh without using git, you can use the open-source-onlyΒ Nightly InstallersΒ or the commercial editionΒ Metasploit Pro.
The surge in emerging threat actors directly correlates with the rapid escalation of victim counts and stolen financial resources. Simultaneously, this growth has spurred the proliferation of specialized supply storefronts across social media platforms, dark web channels, and various smaller niche marketplaces. Security teams today face evolving challenges, requiring them to continuously refine monitoring channels, adjust operational strategies, and foster cross-functional internal collaboration to capture actionable intelligence.
With fraud damages anticipated to approach hundreds of billions of USD, security teams must navigate numerous non-compliant channels while ingesting and processing diverse data formatsβsuch as documents, imagery, video, and unformatted textβlinked to organizational assets. The recent introduction of a new Fraud framework by the MITRE organization underscores the critical need to combat fraud and highlights the significant danger these threat actors pose to all organizations. The MITRE organization has been taking a positive step towards standardizing the fight against fraud, while helping organizations target the relevant directions to look at.Β
These marketplaces supply a range of services in need for the novice fraudster, encompassing server infrastructure, targeted lists, and even support for money laundering facilitated through compromised accounts across various platforms. As larger, well-known marketplaces have been dismantled, smaller, specialized shops are experiencing heightened activity from buyers seeking to engage in fraudulent endeavors.
This blog post undertakes an exploration of these marketplaces and their operational modalities, illuminating the contemporary fraud economy and underscoring the enduring critical nature of robust detection and prevention initiatives.
Fraud-as-a-Service (FaaS)
Fraud is broadly defined as an intentional, dishonest act or misrepresentation of material facts, calculated to deceive others in order to secure an unfair or unlawful gain. Consequently, the Fraud-as-a-Service (FaaS) model encompasses various vendors and digital storefronts that facilitate such activities by providing new tools, instructional guides, and ancillary services for fraudsters.
Online shops and marketplaces, such as Xleet, Blackpass, Infodig and Styx, provide a venue for contemporary fraudsters to acquire the necessary resources for whichever scheme they intend to execute. Users are able to purchase active accounts for online platforms, including major financial institutions, online dating services, and even AI platforms. In addition different offerings may include stolen PII, synthetic identity generator, and ready to use online infrastructure.
To satisfy shifting market demands, threat actorsβalongside malware developers and marketplace administratorsβcontinuously refine their products to optimize future monetization. Novice fraudsters often begin their journey by seeking instructional manuals on various forums or platforms like Styx. Once a strategy is established, they leverage diverse online shops and marketplaces to acquire the necessary infrastructure and credentials. These same venues frequently provide stolen personal or business data, which criminals then exploit during the monetization phase. A common tactic involves business email compromise (BEC) schemes designed to manipulate customers into transferring funds directly to accounts controlled by the fraudster.
Figure 1 - Ad for Infostealer with special detection for financial accounts
β
As companies attempt to protect themselves from being taken advantage of by these fraudsters, they could gather troves of important intelligence about how the malicious actors think, and more importantly gain operational information about breaking fraud networks and protecting their ecosystems. Companies may utilize the available or purchased information into operational decisions, reducing the number of incidents, or at least hinder the fraudsterβs attempts.Β
MITRE Fraud Fighting Framework (F3)
Introduced in early 2026, the MITRE Fraud Fighting Framework (MITRE F3) is designed to help organizations recognize adversarial TTPs, and could help security teams prioritize relevant sources for monitoring through prioritization of attack vectors or vulnerabilities. Due to the large amount of available sources, such a framework could indeed help organizations create the best strategy.
While the framework's structure mirrors traditional MITRE matrices, MITRE F3 expands into domains bridging cybersecurity and financial crime, specifically addressing the monetization stage. Although it introduces a novel perspective on fraud analysis, it does not sufficiently address the necessity of enhanced collaboration between an organization's internal departments.
To obtain meaningful environmental insights, security, fraud, and financial crime teams must maintain constant surveillance of marketplaces and similar forums. Monitoring marketplaces for asset mentions is critical for early detection of threats and new trends targeting new victims.
Key marketplaces and trends
Like other cybercrime-focused shops and forums, our monitored marketplaces also handle external threats targeting their clientele; some even use mirror sites. Similarly to other underground marketplaces, the key players must navigate themselves in an ever changing shattered environment where new marketplaces operate along alternative shopping methods through Telegram and P2P options.
When examining the MITRE framework, we can immediately see many techniques in commonβmostly account takeover (ATO) techniques. Nevertheless, as seen in the different stocks and sellers, the offerings changed with time according to market demands.
There are some notable differences between Styx and the rest of the reported marketplaces, however. Styx operates by offering sellers more space for promoting their own personal shops, available mostly through Telegram.
Figure 2 - Styx marketplace seller page
β
Styx also aims to cultivate a specialized community through their "freemium" model, where premium, high-value content is reserved for users willing to pay significant fees.
Figure 3 - Styx Marketplace Private Section
β
While some of the free manuals have been posted through different cybercrime forums before, they show not only a real attempt by the Styx admins to generate additional income, but also sell ad space for different sellers working outside of the marketplace. These monetization techniques indicate the admins are probably well aware they have many competitors, as they attempt to provide a different shopping experience for their users.
Resource development: Infrastructure
Infrastructure for cybercrime operations has been sold for a long time, offering adversaries illegal access to active domains, cpanels, and more.
One of the leading marketplaces for such items is Xleet, first observed in 2022, which has quickly become a source for large collections of stolen credentials spanning multiple platforms. Distinguishing itself from other monitored marketplaces, Xleet is transparent about its offerings, frequently including evidence like screenshots or even email proof sent to the compromised account's email address.
Figure 4 - Mailer infrastructure available for sale
β
Figure 5 - SMTP infrastructure available for sale
β
Access to SMTP servers could help fraudsters reach larger audiences and evade different email protection and filtering services, thus improving success rate for different schemes. Xleet also offers alleged access to protected networks through Cpanel, web shells, SSH, and RDP connections, as well as VoIP access through their accounts:
Figure 6 - VoIP access available for sale through Xleet
β
BlackPass is another marketplace offering RDP credentials, as well as proxy services used by malicious actors for veiling their location or, as mentioned above, bypassing different restrictions on their IP addresses.
Blackpass, initially named 'Paysell,' emerged as one of the first known online marketplaces dedicated to selling compromised accounts. Estimates suggest this platform has facilitated the sale of hundreds of millions of accounts. Legal documents indicate the marketplace is controlled by Russian cybercriminals, a detail consistent with its product focus: items exclusively targeting Western countries, particularly the US.
Figure 7 - Designated infrastructure for sale on Blackpass
β
All of these vulnerable environments could be part of a bigger scheme run by fraudsters, leading to other techniques being executed like a new vendor set up.
Another marketplace, Infodig, would offer different phone infrastructure in the past as mentioned in one of their opening posts on a cybercrime forum. Foreign or stolen numbers could be used for receiving or intercepting OTP messages, forging IT calls to employees, or self registering new accounts for other services.
Infodig has recently revamped some services offered, including the phone infrastructure, having been removed completely around the end of 2025 during an update the marketplace went through.
Β
Figure 8 - Designated infrastructure for sale on Infodig
β
Styx also offers many options for fraudsters looking for ready to use infrastructure including eSIMs, VoIP services, and compromised VPN accounts. Localized SIM cards could be used by fraudsters for many reasons such as account creation but more importantly as a way to strengthen claims when confronting modern anti-fraud solutions, thus improving scam success rates.
Figure 9 - Styx VoIP and eSIM section
β
The same marketplaces offer additional stolen, forged, and even active company documents for sale including incorporation forms, US tax forms, and other various products connected to shelf companies and stolen PII. These documents allow threat actors to generate troves of mule accounts, shelf corporations, and even combine them into money laundering networks.
AcquiringΒ access
Stolen, self-registered (self-reg), or user-sold accounts are high-demand assets in underground markets. By acquiring pre-existing accounts that have already circumvented anti-fraud protections, threat actors can rapidly deploy them for various criminal operations.
These platforms provide access to a wide range of services, from financial institutions and streaming providers to dating sites and AI-driven website builders. Novice fraudsters often utilize these resources to secure quick profits or to stockpile accounts for future resale.
For example, Blackpass features an extensive account inventory that includes regional banks, neo-banks, and major corporations. Pricing within these markets is fluid; however, self-reg accounts typically represent the most expensive tier due to the significant labor required for their initial setup.
Figure 10 - Self-reg item available for sale
β
Xleet provides an extensive accounts division that covers a broad spectrum of common targets, including gaming, streaming, and dating service profiles. These specific credentials serve as high-value assets for executing various "pig butchering" fraud operations. Furthermore, a notable emerging trend within this marketplace is the significant surge in available credentials for AI platforms, especially those focused on accelerated website creation.
Figure 11 - Streaming accounts for sale, including proof
The newer type of marketplace, active since 2023, features an unorthodox design and much higher prices for their products. Styx holds the usual stock including stolen or self-reg accounts for a large variety of services, including financial institutions, social media accounts, streaming services, and casinos or other gambling sites.
Figure 12 - Styx marketplace
β
The inventory at Infodig is categorized into several distinct sections, featuring stealer logs alongside stolen Financial Information and Personal Identifiable Information (PII), such as Social Security numbers. Their accounts division has recently been going through some technical or supply issues and there are no current accounts available. However the marketplace has revamped their target list section into a new ULP (URL:LOGIN:PASS), offering a new targeted option for large scale ATO operations.
Figure 13 - New ULP section for Infodig
Monetization
Styx has gained notoriety for its support of various "cashout" operations, which are prominently featured in numerous service advertisements throughout the platform.
By functioning as a hybrid of a marketplace and a forum, Styx provides a unique platform where merchants can offer specialized cashout services that exploit financial institutions across different payment rails. These merchants utilize various business accounts to assist fraudsters in laundering illicit funds through established methods, including payroll schemes, ACH transfers, and refund scams targeting multiple banks and geographic regions.
Figure 14 - Styx marketplace cashout ad
β
Beyond explicit solicitations for these services, marketplaces provide a variety of other products that are frequently exploited for money laundering. The exploitation of online gambling platforms remains a prevalent tactic for fraudsters, particularly as new regulations across the US lead to more states and companies entering the market. By acquiring stolen or synthetic PII, malicious actors can establish new gambling accounts to facilitate the laundering of illicit funds through techniques like chip dumping and minimal gameplay.
Conclusion
The fraud economy is changing at a fast pace with new techniques and players entering the field every day. By examining the different marketplaces portrayed in this blog post, we can see that they all react and appeal to different market needs.Β
The change seen through available items across shops are a clear indication of this, as marketplaces pivot towards a larger crowdβone lacking the deep technical knowledge of the earlier fraudsters and carders. The different marketplaces allow every new fraudster to purchase their entire infrastructure for the fraud kill chain, from target lists, servers, and even support for laundering illegal income. Other online services include rapid AI creation of phishing threats, or other forms of abuse of legitimate service through stolen credentials. Marketplaces are not solely made for direct use and other threat actors view them as a major supplier for their shops as well, due to their fixed prices for items with prices which could easily be inflated through their personal shops as seen below:
Figure 15 - Specialized shop for streaming accounts
β
Figure 16 - Specializing account shop on Telegram
β
As fraud communities and groups become increasingly fragmented, the industry continues to splinter into smaller shops. These new, smaller marketplaces often require an invitation or administrator approval to join, a tactic designed to impede investigations and extend the lifespan of their fraudulent products. This shift to smaller shops also benefits merchants, allowing them to keep 100% of their profits instead of sharing them with marketplace administrators. Targeted companies should continue to monitor the marketplaces as they continue to function as an important link in the fraud supply chain. Threat actors are very aware and understand a major part of every business is the profit, therefore financial crime services and associated accounts are continuing to evolve.Β Β
Nevertheless, underground marketplaces will continue to operate as an important part of the cybercrime economic system. Smaller merchants may use these larger stores as suppliers for their smaller shops, as second income or even double or triple their income by selling the same stock in multiple locations. However companies should not only be aware of these underground βmallsβ, and regularly monitor them for any suspicious findings, but take a more proactive approach. The evolving nature of fraud demands a stronger reaction from organizations as well as cooperation from security, financial crime, and compliance teams for proactive measures against these threats.
Targeted companies, especially financial institutions or gambling providers, should actively investigate stolen accounts and gather vital intelligence for protecting themselves in the future, making it more difficult for threat actors to abuse their payment rails, brands, and customers.Β
What organizations should do
To safeguard both their infrastructure and clients, security teams must move beyond monitoring disparate data streams and actively align with internal fraud and financial crime units to cultivate actionable intelligence. Because illicit merchants rely on marketing their offerings, security analysts should actively communicate with threat actors, purchase account samples, as well as analyze images or videos to map threat actor networks, verify operational legitimacy, and finally deploy targeted security countermeasures. Threat actors are threatening organizations with more than just data exfiltration, with compliance or financial crime requirements, companies become more vulnerable to newer forms of threats, not commonly associated with security teams, but initiating through cybercrime sources.
By proactively identifying leaked assets, correlating them to their own environments, and responding quickly through credential resets, and fraud monitoring, organizations can significantly reduce both financial losses and downstream risks such as ATO, and money laundering.
If your scan engine already holds credentials for a host, it can ask that host which ports are open instead of probing for them.
Every scan begins with the same question: which ports on this host are open? Everything after it, from identifying services to checking for vulnerabilities to evaluating policy, depends on the answer being right. The traditional answer comes from the outside: the scan engine sends traffic to a range of ports and infers each port's state from how the host responds. That approach is the industry standard, and it works well when a clear network path exists between the engine and the host. Hardened hosts can stay silent rather than replying, which forces the engine to wait out timeouts. Rate limiting and intrusion prevention can throttle a burst of probes, and genuinely open ports go missing when they do. Large port ranges take time to cover thoroughly, and that time comes out of your scan window.
There is a more direct route on any host where the scan engine already holds valid credentials: ask the host itself. This is credentialed discovery, so a credential that matches the host is the precondition for everything that follows. The engine connects to the port that credential uses, authenticates with a credential you already manage, and the host's operating system returns an authoritative list of the ports it is listening on. That list covers both TCP and UDP ports. There is no probing, no inference, and nothing to wait out.
Three things to know before enabling pre-port discovery
Pre-port discovery can report ports that a firewall or other network control stops your scan engine from reaching, and on those hosts you get fewer results and a longer scan.
SSH and the Scan Assistant are tried on their standard ports, TCP 22 and TCP 21047, unless you set a different port on the credential's restriction.
Credential coverage decides which hosts benefit, and a host with no matching credential falls back to a network port scan.
A network port scan works by inference. The engine sends traffic to each port in a configured range and reads the host's response, or its silence, as evidence about that port's state. Inference is the whole method, and its accuracy depends on the path between the engine and the host behaving predictably.
Several common conditions break that assumption. A hardened host that drops unsolicited traffic instead of refusing it gives the engine nothing to work with, so the engine waits for a timeout and then records an ambiguous result. Rate limiting and intrusion prevention are built to react to exactly the traffic pattern a port scan produces, and a throttled probe looks the same to the engine as a closed port. Wide port ranges make both problems worse, because every additional port is another probe, another possible timeout, and more scan time.
The outcome is a picture that can be partial on one scan and different on the next, on the hosts where an accurate picture matters most.
If you already have credentials, ask the host
Credentialed pre-port discovery replaces that inference with a question, and it is available from version 8.58. The engine connects to the port a credential uses, authenticates, and reads the list of listening ports from the host. For any host where that succeeds, the engine skips the network port scan and moves straight to examining the ports the host reported. That is what pre-port discovery means: discovering ports before, and in place of, the network port scan.
There is nothing new to deploy, because pre-port discovery reuses the credentials you already configure for authenticated scanning. You do not have to choose a method: when more than one credential fits a host, the engine prefers the Scan Assistant, then SSH, then a direct Windows connection, and it uses the first one that authenticates.
A host with no matching credential, or one where authentication does not succeed, falls back to a network port scan automatically, and that fallback is not reported as an error.
The option is a per-template checkbox under Asset Discovery, and it is off by default. Everything after port discovery is unchanged: fingerprinting, vulnerability checks, and policy evaluation run as they do today. The configuration guide has the console and REST API steps.
Pre-port discovery's trade-off, stated plainly
A host reports what it is listening on, and it has no way of knowing what sits between it and your scan engine. A network port scan never ran into that, because it only ever reported a port it could actually reach. Pre-port discovery trades that outside-in view for the host's authoritative inside-out view, and the trade has a cost worth understanding first.
After discovery, the engine still connects to each reported port to identify the service on it. A port the engine cannot reach has to time out before the engine moves on. Three things follow on that host: no service is identified on the unreachable port, the scan takes longer, and the engine can read repeated connection failures as a sign that the host has stopped responding. In that case it stops examining the host early and reports a finding saying the host scan was terminated because of excessive connection errors.
The finding describes the engine's experience of the host, not the health of the host. The port is genuinely open, and the host answered every question pre-port discovery asked it. The troubleshooting documentation covers what can block the path and how to test reachability from the engine.
Who should turn on pre-port discovery?
Pre-port discovery is a good fit where the scan engine has broad network reachability to the hosts it scans, and where you already use SSH, Scan Assistant, or Windows credentials for authenticated scanning. It pays off most on hardened or rate-limited hosts and on large port ranges, which are the cases where a network port scan has been slow or inconsistent. A responsive host on a fast network may show little difference.
Approach it with more care where the engine is deliberately segmented from the hosts it scans and allowed through on only specific ports, or where the firewall rules between the engine and those hosts are restrictive or not fully known. In those environments, confirm reachability first, or keep using the network port scan.
Because this is a per-template setting, both approaches can coexist: a pre-port discovery template for the estate your engine can reach broadly, and a standard template for the hosts that segmentation deliberately keeps at a distance.
Try it on one template
One template at a time is the easiest way to judge the difference. Enable pre-port discovery on a single template, scan a representative group of hosts with it, and compare the results against what those same hosts returned before. If the port lists and the scan times look the way you expect, widen it from there. The configuration and troubleshooting guide has the details.
Further reading
Credentialed pre-port discovery: How to enable it in the console and over the REST API, how it picks a credential and a port, what your template's port settings still control, and what to check when a host does not behave the way you expect.
Microsoft is publishing 974 own-product vulnerabilities on September 2026 Patch Tuesday, including 723 vulnerabilities in Windows. Along with Microsoft fixes for 25 non-Microsoft CVEs, that brings the total number of vulnerabilities on the table today to 999. Whether this is the biggest Patch Tuesday ever depends on how we count, but this is by far the most CVEs that Microsoft has ever published in a single day. As Rapid7 noted last month, there is no reason to suppose that Patch Tuesday will ever return to the lower volumes we saw prior to 2026. Microsoft is aware of exploitation in the wild for two of the vulnerabilities published today.
Windows ALPC: zero-day EoP
The eternal game of elevation of privilege whack-a-mole between Microsoft and attackers continues. This month, the battle is centered on the Windows Advanced Local Procedure Call (ALPC) mechanism, a kernel capability that facilitates inter-process communication. Microsoft is aware of exploitation in the wild already. Successful abuse of the flaw underlying CVE-2026-85880 grants an attacker SYSTEM via a buffer overflow that enables an out-of-bounds write, and as we all know by now, this is exactly what would happen during the first five minutes of a technically accurate horror movie about ransomware. We can infer one silver lining here: since neither Server 2025 nor Windows 11 receives patches for CVE-2026-85880, it is likely that Microsoftβs ongoing efforts to level up memory safety by rewriting critical kernel components in Rust are paying off.
Windows Update Stack: zero-day EoP
Attackers disappointed by Microsoftβs move towards memory safety improvements for various critical kernel components need not leave empty-handed today. Microsoft is aware of existing exploitation in the wild for CVE-2026-81963, an elevation of privilege vulnerability in the Windows Update Stack that leads to SYSTEM privileges via improper link resolution. All supported versions of Windows receive a patch, which presumably tightens up controls to prevent the Windows Update Stack from following a malicious link and overwriting a system component with an attacker-controlled imposter. The relatively pedestrian CVSS v3 base score of 7.8 is no reason for less concern, since no serious attacker will bother developing an intricate one-shot RCE when a two-stage attack chain consisting of low-privileged local access coupled with elevation of privilege will achieve the same ultimate goal much more easily.
Living on the Edge: browser advisory uncertainty
For the second month in a row, Microsoft does not appear to have published any desktop browser security advisories between the start of the month and Patch Tuesday. Microsoft Edge is built on top of Googleβs open-source Chromium project, and on September 3, 2026, Google Chrome patched CVE-2026-85046, an exploited-in-the-wild zero-day vulnerability in the V8 JavaScript engine relied upon by both Edge and Chrome. So, is Microsoft Edge falling dangerously behind Google Chrome? Well, maybe. In this specific case, the Edge stable channel did receive a patch a day earlier than Chrome on September 2, 2026, and we know this because the Edge release notes mention it. However, almost a week later, Microsoft still hasnβt published a security advisory for CVE-2026-85046, and until that URL returns something better than a 404, that will remain true. In short: if youβre patched, you are protected, but if you rely on advisories to know which vulns exist, you could miss this zero-day vulnerability altogether. Only Microsoft knows why this advisory is missing, but there is no reason to suppose that Microsoft is somehow immune to the pressures that come along with the vast increase in vulnerability volume. A patch without an advisory is perhaps marginally better than an advisory without a patch, but keeping track of exposures without reliable advisory materials is not straightforward. Chrome patched 11 other vulnerabilities at the same time as CVE-2026-85046, but itβs not yet clear if those are patched in Edge. Until Microsoft sets the record straight, the only safe assumption is that these vulnerabilities (e.g. CVE-2026-85045) remain unpatched in Edge.
Microsoft lifecycle update
The next Microsoft product lifecycle changes with broad impact occur on October 14, 2026, when Windows 11 24H2 Home & Pro reach end of servicing, and Windows Server 2022 moves to extended support, with free critical security updates continuing, but no further feature development. At the same time, the final curtain falls for Windows Server 2012 and 2012 R2 with the expiry of the third and final year of cash-for-updates Extended Security Update (ESU) program for these aging workhorses. Office 2021 also moves beyond support, including the Long-Term Servicing Channel, with no ESU available in that case. Also in October, Exchange Server 2016 and 2019 will join the βno ESUβ club, after two previous six-month reprieves. Presumably, Microsoft really means it this time.
An information disclosure issue in the zipfileInflate function in the zipfile extension in SQLite v3.51.1 and earlier allows attackers to obtain heap memory via supplying a crafted ZIP file.
An information disclosure issue in the zipfileInflate function in the zipfile extension in SQLite v3.51.1 and earlier allows attackers to obtain heap memory via supplying a crafted ZIP file.
An information disclosure issue in the zipfileInflate function in the zipfile extension in SQLite v3.51.1 and earlier allows attackers to obtain heap memory via supplying a crafted ZIP file.
While conducting research into a recent N-able N-central authentication bypass vulnerability (CVE-2026-18577), Rapid7 Labs discovered two new vulnerabilities affecting the latest version of N-central. When chained together, these two vulnerabilities allow a remote unauthenticated attacker to bypass authentication and create a new attacker-controlled System administrator account on an affected server.
Both CVE-2026-86206 and CVE-2026-86207 have been patched by the vendor via N-central 2026.3 Hotfix 3.
Product description
N-able N-central is an enterprise-grade Remote Monitoring and Management (RMM) platform designed for Managed Service Providers (MSPs) and IT departments to monitor, manage, and secure complex, large-scale networks from a centralized dashboard.
Credit
These vulnerabilities were discovered by Stephen Fewer, Senior Principal Security Researcher at Rapid7, and are being disclosed in accordance with Rapid7's vulnerability disclosure policy.
Technical analysis
CVE-2026-86206
N-central exposes its management interface (TCP 8443 by default) through Envoy, an edge proxy. Envoy passes accepted requests to Jetty, the Java web server that hosts N-central's application. The application gives requests from the loopback address (i.e. 127.0.0.1) more access than requests from a remote system. This design depends on Envoy, Jetty, and the N-central access filter all agreeing on which application path the client requested and whether the client is really local. The following request can make them disagree about both of these things:
POST /dms;/services/ServerUI HTTP/1.1
Forwarded: for="127.0.0.\1"
Content-Type: text/xml; charset=utf-8
SOAPAction: ""
The semicolon in the URI and backslash in the Forwarded value introduce a discrepancy when processing the request that leads to an access control bypass. Looking at Figure 1 below, we can see an overview of how these two values are processed during an incoming malicious request.
Figure 1: Processing a malicious request.
The semicolon gets the request past Envoy
The Envoy proxy rules come from the n-central-proxy-4.5.6-5 package. In /etc/opt/envoy/lds_intermediate.yaml, shown below (and edited for brevity), the management listener returns HTTP 403 for paths beginning with /dms/services or /internal/dms. A final catch-all rule sends other paths to the DMS application.
Envoy compares those prefixes with the path it received. The path /dms;/services/ServerUI does not begin with /dms/services, because the next character after /dms is a semicolon. It therefore reaches the catch-all route, passing the request from Envoy to Jetty.
Jetty interprets the path differently. The shipped jetty-http-9.4.56.v20240826.jar contains org.eclipse.jetty.http.HttpURI, and org.eclipse.jetty.util.URIUtil. Together, these classes treat text beginning with a semicolon as a path parameter and remove it when producing the decoded path used for servlet dispatch. As a result, Jetty turns /dms;/services/ServerUI into /dms/services/ServerUI. That decoded path then matches the Axis SOAP servlet mapping in /opt/nable/webapps/ROOT/WEB-INF/web.xml.Β
Similarly, the same technique can be used to target the SOAP service via /internal;/dms/services2/ServerUI2. Jetty decodes it to /internal/dms/services2/ServerUI2, which matches the CXF SOAP servlet mapping. A single semicolon is sufficient to create the routing disagreement.
Reaching these servlet mappings puts the request at the protected SOAP interfaces that an exploit can leverage to establish an application session and later manage privileged objects, but the semicolon trick alone does not authorize the request. Without the crafted Forwarded header, Jetty retains the client's real remote address and N-central's ServletPathFilter denies access. Conversely, the header trick alone cannot help a request to the ordinary /dms/services/ServerUI or /internal/dms/services2/ServerUI2 path: Envoy returns HTTP 403 without forwarding that request to Jetty.Β
As such, an exploit needs both discrepancies; the semicolon to pass Envoy's path check and the header to pass N-central's local-request check.
The header makes the remote client look local
The Forwarded header tells an application about the original client behind a proxy. In a malicious request, the for value is quoted and contains a quoted-pair (\1):
Forwarded: for="127.0.0.\1"
Under the HTTP quoted-string grammar, the backslash escapes the following character. Jetty's ForwardedRequestCustomizer, from jetty-server-9.4.56.v20240826.jar, applies that rule. It removes the backslash, reads the value as 127.0.0.1, and exposes that value to N-central as the request's remote address.
N-central then parses the original header a second time. Its parser is in com.nable.util.LocalHostUtils, from /opt/nable/webapps/ROOT/WEB-INF/lib/dmsservice-11.0.1-SNAPSHOT.jar. This parser removes the surrounding quotes but does not remove the backslash. It therefore checks 127.0.0.\1.
That string is not a valid IP address. LocalHostUtils.xffCheck() rejects an invalid value found in X-Forwarded-For, but its Forwarded branch rejects only values that it successfully recognizes as loopback. The below (abridged) decompilation shows the relevant branch:
When given the header value 127.0.0.\1, the isLoopbackAddress() call (at [1]) returns false (at [2]) because the value is invalid. The loop therefore continues and xffCheck() returns true (at [3]). In other words, an invalid Forwarded header value causes xffCheck to fail open. The final decision occurs in com.nable.server.ServletPathFilter, shown below.
The first check asks whether a forwarding header is trying to claim a loopback address (at [4]). N-central's parser sees the invalid value 127.0.0.\1, does not recognize it as loopback, and allows it. The second check asks whether Jetty's remote address is local (at [5]). Jetty has already converted the same header value to 127.0.0.1, so this check succeeds. The filter returns true (at [6]) before consulting the normal remote-path allowlist.
CVE-2026-86207
By leveraging CVE-2026-86206 to reach the protected URI /dms/services/ServerUI, a SessionID returned by the Session.Hello SOAP operation (See the prior work by Horizon3 on leveraging the legacy SOAP API) can be generated. However, this SessionID is only a pre-login session. It proves that the request reached the local-only SOAP API via the access control bypass, but it does not yet identify an authenticated user. A separate authentication bypass vulnerability, in how legacy two-factor authentication operates, allows a pre-login session to become an authenticated session.
The method com.nable.server.ui.UserTwoFactorLogin, from dmsservice-11.0.1-SNAPSHOT.jar (shown below), binds a requested user ID (e.g. the builtin N-able Administrator accountβs well known ID 1) to the session (at [1]) before it attempts legacy two-factor authentication (at [2]) . A normal authentication rejection removes that binding (at [4]), but if an exception occurs, this binding is left in place (at [3]).
N-central supports two distinct second-factor systems: legacy, profile-based authentication using an external AuthAnvil or RSA SecurID server, and native time-based one-time password (TOTP) βTwo-Step Verificationβ using an authenticator application. Despite overlapping 2FA/MFA terminology in N-ableβs documentation, com.nable.server.ui.UserTwoFactorLogin implements the former profile-based mechanism; it does not enforce the userβs native TOTP setting.
In a default installation, legacy two-factor processing raises an exception for several builtin identities used by N-central, as each of these identities lack a single legacy AuthAnvil or RSA 2FA profile association required by UserTwoFactorLogin. Specifically the following built-in identities can be leveraged via their known ID numbers.
User ID 1 (N-able Administrator)
User ID 50 (Product Administrator)
User ID 51 (N-able Support)
By creating a new pre-login session for any one of the above IDs, a SOAP call to User.TwoFactorLogin with a dummy password will achieve the authentication bypass, converting the pre-login session to a privileged SOAP session for that user. By using additional calls to the ServerUI2 SOAP endpoint, a new attacker-controlled System user account can be created.
Remediation
The vendor-supplied release of N-central 2026.3 Hotfix 3 (version 2026.3.1.13) remediates both CVE-2026-86206 and CVE-2026-86207. All versions of N-central prior to 2026.3.1.13 are vulnerable. Customers running affected on-premise N-central environments are urged to apply the latest update on an urgent basis, outside of normal patching cycles.
Customers using hosted N-central environments do not need to take action as the vendor has applied the needed updates.
Exposure Command, InsightVM and Nexpose customers will be able to assess their exposure to both CVE-2026-86206 and CVE-2026-86207, with authenticated vulnerability checks expected to be available in the September 8 content release.Β
Disclosure timeline
August 27, 2026: Rapid7 makes initial outreach to N-able who respond the same day.
August 28, 2026: Rapid7 provides a detailed technical analysis and exploit script to N-able, along with a proposed timeline for a coordinated disclosure.
September 5, 2026: N-able release N-central 2026.3 HF3 which fixes two of the vulnerabilities (CVE-2026-86206, CVE-2026-86207) reported by Rapid7.
September 7, 2026: Rapid7 contacts N-able requesting clarity on several issues. N-able responds the same day with requested information.
September 8, 2026: This disclosure for CVE-2026-86206 and CVE-2026-86207.
A new Linux toolkit, identified by Rapid7 Labs, has been targeting organizations across South Koreaβs automotive and media industries with minimal detection. The campaign made use of a HAProxy instance named βted backdoorβ, alongside trojanized versions of crond, agetty, atd, sshd, and polkitd. This previously undocumented framework enabled threat actors to execute remote commands on compromised servers, inject malicious scripts into web traffic, perform credential harvesting, and engage in long-term surveillance.
The standout feature of this toolkit is its depth of integration with the target environment. The ted backdoor is compiled as part of the victimβs existing HAProxy version 2.8.12. It uses its native filter API, internal memory pools, event scheduler, and process management infrastructure to intercept traffic and hide from monitoring, while genuine load balancing traffic operates as expected.
Operating alongside this are an SSH keylogger, a curl-based RAT, and a stager. The RAT maintains a watchdog thread dedicated to tracking HAProxyβs health, and reporting it back to the operatorβs infrastructure. The earliest uploads on VirusTotal date back to mid-2025 and the involved HAProxy 2.8.12-0fdb194was released on 22 November 2024, establishing this as the earliest possible compilation date for this build.
The toolkit is attributed with medium confidence to DPRK APTs, given that the attacks Rapid7 observed were targeting South Korean media and automotive sectors, likely aiming at long-term espionage, the usage of simple xor-based encryption, custom substitution cipher, and the list of C2s hardcoded is associated to APT37 by ThreatFox and maltrail. Analysis shows that the ted backdoor could be part of a broader framework covering nginx backdoor as well. The ted plugin registers a custom HAProxy filter that hooks the HTTP parser to inspect and log high-value traffic, steal session cookies, and perform a client IP selection to decide whether to inject custom scripts in the webpage being rendered.
Technical analysis
Rapid7 researchers revealed that the toolkit was used in campaigns targeting South Korean automotive and media sectors likely dating back to early 2025. The number of trojanized binaries and functionalities found suggest the scope could be long-term cyber espionage and surveillance. However, gathered evidence does not suffice to establish a timeline nor how the initial access was performed.
At the time of analysis, both victims were running an edge webserver with ports 80, 443, and 25 exposed. Port 443 hosted the Groupware login portal and port 25 exposed a mail server. Either surface represents a plausible initial access vector consistent with documented Kimsuky tradecraft. Since the beginning of 2026 Kimsuky has been observed exploiting RCE vulnerabilities in externally accessible mail servers to compromise South Korean groupware vendors, while Groupware web portals represent the kind of exposed authenticated application that DPRK-nexus actors have repeatedly targeted for credential harvesting and exploitation. The specific entry point and any associated CVE remain unconfirmed pending further forensic evidence.
The scenario shown in Figure 1 assumes the initial access is obtained by exploitation of CVEs related to the Groupware portal.
Figure 1: Attack chain partially reconstructed
β
The threat actor begins by exploiting a vulnerability in the Groupware login portal running on the edge webserver, gaining an initial foothold in the DMZ. From there, they establish persistence and harvest credentials from the compromised edge host (e.g. SSH keylogger), which also doubles as a staging server hosting the trojanized system ELFs.
With a foothold on the edge, the attacker pivots inward and drops the stager onto internal servers. The stager checks for the presence of either crond or HAProxy, and only then deploys CurlRAT retrieving it either from its data section or the edge webserver.Β
In parallel, ted backdoor is dropped onto the HAProxy load balancer. Once active,it establishes its own C2 channel to the external operator infrastructure, enabling data exfiltration, command execution, and script injection. On the victim side, the compromised load balancer silently redirects or serves malicious content to selected clients browsing through it, completing the watering-hole loop.
SSH keylogger
4bb923eb040aa13ca8fd409c31ee4729c60ddff32e350efe1c5a4a9168a065f5 intercepts legitimate users' plaintext passwords and saves them to an encrypted log file under /var/lib/sshd/c8c68e629bba773a10ac80012d10bf19.
Figure 2: hardcoded master passwords in userauth_passwd()
β
After checking that entered credentials are not equal to TAβs master passwords, userauth_passwd() proceeds to encrypt them using a custom substitution cipher recurring throughout the toolkit and base64 encoding.
Figure 3: Substitution cipher used to encrypt credentials
β
Pivoting from the above cipher, instances of polkitd, crond, agetty and atd binaries were identified using a similar encryption algorithm. Crond binaries were found to be delivered by a stager.
CurlRAT Stager
The stager 5db1b6d52faf60b4f32d6fd0c7c938e4d05d29a14c32ded4a9668357c08b6a91 starts by decrypting its configuration strings using a 1-byte XOR, then verifies root privileges and profiles the OS checking system hostname, OS distribution and version IDs, kernel release and version numbers and CPU architecture to select the correct payload to drop. It decrypts the trojanized crond binary in memory, overwrites the system's legitimate daemon, and restarts the service. As shown below, only if HAProxy or cron are running on the system will it proceed to drop the backdoored crond.
Figure 4: Stager configuration
β
Checking for HAProxy presence is done as the binary, named by TA as ted backdoor. It also has RAT capabilities and plays a major role in the campaigns described. The embedded crond versions supported are CentOS 7.7, 7.8, 7.9 and Ubuntu 22.04 and after installing the backdoor, timestomping ensures the crond binary gets the same creation timestamp of /usr/bin/ssh. The stager ends by filtering out keywords such as tmp, wget cron and crond from Linux system logs using a staging file named /tmp/jasper-log, likely to blend in as the JSP (JavaServer Pages) engine in old Apache Tomcat versions, erasing any traces of the installation. The logs affected by the selective erasure are /root/.bash_history and the following under /var/log: messages, audit/audit.log, cmd.log, secure, syslog, auth.log.
09739441ed4599bac2f8159028f772f71e4b25c8badfff95574e56d7384f3dbe and fea1bc36632c71e5a839803469ef60ac47595d36b2c50934ac109ade6df06e61Β are a different variant of the stager that fetches backdoored binaries from a compromised victimβs server without embedding any payloads.
CurlRAT
The Ubuntu version is analyzed below, though CentOS samples follow the same logic except for the filepath used to hide config/staging files.
As for the stager, feeea9d0bf6ae7396d28271baa51ae50df5169ce5d32a516865856f91abc50b3 starts by decrypting configuration strings using a 1-byte XOR key (0x58).
Figure 5: curlRAT configuration
β
The main logic added to crond is executed via two threads. The first thread runs the start_routine function that creates the staging directory snapd under /var/lib, where it attempts to load the victim ID from /var/lib/snapd/g580. If network failures were previously recorded, it reaches out to a secondary domain β img.darklights.store β authenticating with api_token/ecd427ea8330a4ff73618483e00b9b41 and setting the User-token header to the victim ID to fetch updated configuration under /tmp/nimon.unix-docbase.8564479396043450766-db6fb4443bc, where itβs then copied into /var/lib/snapd/g105.
To decrypt the configuration, the first byte of the file initializes the seed of a feedback xor based cipher. Each poll cycle, a config file is fetched from the C2 server over HTTPS (falling back to HTTP on failure) using libcurl, with the victim token embedded in the User-token header. The fetched config is parsed for three single-character delimiters β ! terminates the credential field, # marks the payload section, and * separates arguments β after which the credential field is compared against the local victim token.
If authentication succeeds, a single-character mode byte (ASCII '0' through '5') preceding the delimiter β#β selects one of six handler routines via a jump table. Payloads embedded in the config are decoded through a two-stage pipeline: standard Base64 decoding followed by a rolling cumulative XOR cipher keyed from the decoded header. The C2 task handler sleeps for 43,200 seconds (12 hours) between polls by default, but the operator can activate a fast-poll mode by setting a flag, reducing the interval to 30 seconds. A retry loop calls the handler up to six times per cycle with five-second intervals, failing fast if the first attempt does not succeed. The table below shows the C2 commands accepted.
Mode
Function
Description
0
cmd execution
Base64 + XOR-decodes a command list from the config, executes each line via popen with stderr redirected to stdout, saves output into a 1 MB buffer, and sends the result back.
1
config write
Decodes and writes a new config payload to disk, validates it, and sets the polling interval and fast-poll flag. If the validation fails, the C2 resets to img.monderhouse.space
2
staged payload drop
Issues an authenticated HTTP POST to the C2 host with a task path as the body, streams the response to a temporary file, decompresses and moves it to the final drop path, unlinking the temp.
3
reverse shell
Closes all file descriptors above 2, calls setuid(0) and setreuid(0, 0), forcing both its real and effective user IDs to root, and connects out before handing off to the shell dispatcher.
4
beacon
Populates a 10 KB system-info structure and transmits it as a check-in beacon.
5
PTY shell
A full interactive PTY shell, the payload consists of an ip:port.
Modes 0β2 and 4 use libcurl-based HTTP/HTTPS, hence the name curlRAT. All modes use Base64+XOR encoding/decoding applied to the payload. The victim ID is obtained by concatenating "cron_3.0pl1-137ubuntu3", system hostname, ipv4 address, and the hardware/OS UUID (read from /sys/class/dmi/id/product_uuid), then applying MD5 hash and converting it to uppercase.
The layer of encryption used for all C2 interactions consists of a feedback xor cipher using an initial random seed (modulo 240 + 10, 0<=seed<=249) and then applying Base64 encoding. The malware encapsulates the encrypted and encoded payload, the service name, and the telemetry type into a formatted application/x-www-form-urlencoded HTTP POST body (name=%s&value=%s&type=%d) which is sent to the C2 and authenticated using an hardcoded API token, including the victim ID in the User-token header.
The second thread acts as the HAProxy watchdog. Before entering the monitoring loop, it checks for the presence of the file /usr/lib/libvirtlog.so.0 to ensure the target is running in a virtualized environment, otherwise it sleeps 6 minutes and aborts. Then it accesses the MD5 victim ID under /var/lib/snapd/g580 to check if the node is active and compromised. Every hour the watchdog reads the pid at /var/run/haproxy.pid and monitors the status of HAProxy by polling /proc/pid. The status can be one of the following codes:
0 (Started): Process transitioned from stopped to running
1 (Stopped): Process is no longer active in the kernel process table
2 (Restarted): PID file timestamp modified, and a new PID is detected
3 (Reloaded): PID file timestamp modified, but the PID remained identical
The status is then sent to the C2 endpoint βwriteservice_infoβ using the custom crypto layer and the telemetry type set to 0 (Figure 6).
Figure 6: writeinfo_service monitoring HAProxy status
β
The CentOS versions of curlRAT contain the same functionalities, except that functions are masqueraded as atd_ routines to blend in during static analysis.
Figure 7: The two threads running curlRAT logic
β
Below is the table summarizing the main RAT components.
The atd_get_info() is a recon routine likely used to decide which binary trojanized next to ensure persistence on the node. It collects the service name of the compromised machine and sends it to the C2 via the atd_response routine together with Ipv4 address, OS version, and the list of services and listening port (Figure 9).
Figure 9: Recon module output sent to the C2
β
MODE, DELAY and SERVER_URL are parsed from the config file discussed previously. During the campaign observed by Rapid7, the RAT acts as a framework and constitutes the codebase to edit legitimate system daemons. Other trojanized instances found are agetty and polkitd, where we identified a similar pattern lacking the HAProxy monitor: the creation of a thread to run curlRAT, reaching to img.worksongo.store and img.socialteams.store respectively.
atd_encrypt_url and atd_decrypt_url leverages the substitution cipher βE1x0X3f2R5w4g7u6D968kAeCdBPEpDhGJF4IiHHKzJvMtLlOnNcQmPNSjR2UFTUWOVTYIXZZ5aWcQbbeqd7gYf3i8hykGjCmsl9oonrqSp0sVrauKtLwAvBy1xMz=.#,+/--__" shared with the ssh keylogger.
Ted backdoor
The TA recompiled the HAProxy build 2.8.12Β 72e70936f0dbe459142a1d867617c35f8d0cce5d18c6a49e1090a2a5adc8e558 (18MB) to include a custom plugin (named ted_plugin) leaving debug strings naming the backdoor.
Figure 10: ted_plugin compiled as part of the source code
β
Figure 10 shows that the plugin was directly compiled with the rest of HAProxy source code and hooks directly the built-in HTTP parser relying on internal HAProxy structure for searching HTTP request headers.The custom filter defined to capture traffic is loaded via the ted_load_filter_config routine.Β
Figure 11: my_filter_config struct
β
The routine reads the implant's operational configuration from ~/cache/haproxy-1000.cache. Each field is decrypted in two layers: first ngx_decode applies a chained XOR seeded by the file's first byte; then ngx_decrypt_script applies a monoalphabetic substitution whose 67-entry mapping table is built at startup in ted_init_util from βE1x0X3f2R5w4g7u6D968kAeCdBPEpDhGJF4IiHHKzJvMtLlOnNcQmPNSjR2UFTUWOVTYIXZZ5aWcQbbeqd7gYf3i8hykGjCmsl9oonrqSp0sVrauKtLwAvBy1xMz=.#,+/--__" , and held in the ted_dec_dict uthash table keyed by Jenkins hash for O(1) lookup. The config carries the operating mode, all targeting regexes, every script rule with its payload paths and filenames, and the allowed operator keys. IP-based access control lists are loaded from haproxy-1001.cache and haproxy-1002.cache via the same decryption scheme. In other ted backdoor samples, the my_filter_config struct includes regexes to capture cookies as well.
After loading its configuration, it sets up signal handling via ted_register_reload_signal_handler() and saves its C2 pipe underΒ HAPROXY_MWORKER_PP_READ and HAPROXY_MWORKER_PP_WRITE environmental variables to survive reloads and restarts, saving child process activity via ted_extra_log().
Below is the list of functions defined by the ted_plugin:
trace_chn_start_analyze() is hooked via ted_chn_analyze_for_htx_constprop_0() that parses the HTX buffer β the memory region where HAProxy stores parsed, SSL-decrypted HTTP request. If an incoming request matches the endpoint "/favorite_list_2x_m500_ico.jpg" (Figure 13), the malware drops into a Command & Control mode, setting the field flag to 1 in the ted_rep_state structure that tracks the response state.Β
β
Figure 13: Dropping into C2 mode
β
First, it reaches into HAProxy's internal counters to decrement active connection stats, referencing fields from the proxy struct via hardcoded 2.8.12 offsets to clear any trace left: the per-backend beconn/feconn and the global actconn, then 64-bit fields within be_counters (cum_conn, cum_req, bytes_in, bytes_out) guarded against underflow, and 32-bit peak metrics (sps_max, conn_max, cps_max) decremented only when exactly 1. Secondly, it parses a custom hardcoded 14-byte header to obtain the payload length, then creates FIFO pipes via ted_make_pipe_name and ted_create_multi_pipe_file keyed on HAProxy's connection ID under /tmp (e.g. /tmp/t[ID]_w.pipe). If HAProxy is running in master-worker mode (MODE_MWORKER, bit 0x80), the connection ID is written to the pp_w2m pipe so the master process runs the dispatcher; otherwise a detached thread runs ted_pipe_worker_thread locally (Figure 13).
The HTX walk filters on block type 4, which is HTX_BLK_DATA, and writes each block straight into fdPipe with write(). Any short write aborts and closes the pipe. Afterwards to_forward, output, buf.head and buf.data on the request channel are all zeroed. That tells HAProxy there is nothing left to forward, so the attacker's command body never reaches a backend server. The C2 request terminates at the load balancer, and no backend ever logs it.
The C2 dispatcher logic is resumed in the table below.
Command
Description
Opcode '0' (0x30)
Beacon: returns a version banner including build ID (24112201), HAProxy version (2.8.12-0fdb194), master-worker mode status, and chroot path.
Opcode '1' (0x31)
File upload: resolves path via ted_build_correct_path, writes file content via fopen(path, "wb"), and replies 1. Used to upload payload files for the injection path.
Opcode '2' (0x32)
File download: reads a path, stats it, writes the 8-byte size, and streams the contents back with EAGAIN handling.
Opcode '3' (0x33)
Command execution: executes commands via popen; merges stdout/stderr, appends " 2>&1", and streams output back XOR-encrypted.
Opcode '9' (0x39)
Config update: writes new config to ~/cache/haproxy-1000.cache.bak, re-encrypts using chained XOR, validates via ted_load_filter_config, and renames over the active config file if successful.
All five handlers write the same βHTTP/1.0 200 OKβ header with Content-Type: text/html into the read pipe before the body. That's what the response task then relays out via send() on the raw socket, which is why the traffic looks like an ordinary HTTP response on the wire despite never passing through HAProxy's response path. Output back to the operator uses a rolling XOR cipher where each plaintext block is the key used to encrypt the next block with a random 1-byte seed.
If the initial endpoint check does not match "/favorite_list_2x_m500_ico.jpg" and the filter is in capture mode, then traffic is selectively logged and victims are identified based on the capturelist_set field within the my_filter_config struct (Figure 11), containing the list of targeted IPs and subnets. It uses regular expressions to filter the incoming HTTP traffic, waiting for high-value requests (like a user hitting a /login endpoint or an admin panel).
When a victim's request matches the attacker's filters, the backdoor goes to work.
It extracts the victim's source IP, the requested Host, the Referer, and the User-Agent formatting the data in a single-line record using exclamation marks as separators.
Figure 14: Real-time capturing of selected HTTP headers matching specific regexes
β
The execution flow continues based on conf->action; zero means passive logging only, non-zero starts the injection path. A request then has to clear four conditions. It needs a User-Agent, and if agent_pattern is configured that regex has to match. Second, the code scans the User-Agent for the bytes x,6,4, it selects between the two payload paths the matched rule retrieving them ted_script_config struct (path_32 at offset 0x18 and path_64 at 0x20). Third, the script rule list is walked until one ted_script_config entry's URL and referer regexes both match, with a null referer counting as an automatic pass. Thus the operator catches a victim arriving at a specific page from a specific referrer, rather than spraying at everyone hitting a URL.
β
Figure 15: Custom ted structure defined to inject malicious code in the page, and store regex rules and the connection context
β
Fourth, the implant parses Accept-Language splitting on ; and =, pulling four operator-controlled fields: mrt for the 64-byte uid credential, msc for an 8-byte status, mst for an 8-byte score, and a fourth keyword read from off_355407 for a 1024-byte infoblob. Parsing is order-independent and any subset can appear. If mrt yields a key, it must exist in allow_id_set, and that credential overrides IP filtering entirely, letting the operator reach the requested page from anywhere. It also upgrades the log record to the *-prefixed format carrying uid, status,score, and info. With no key, the fallback is IP-based:action == 1requires whitelist membership, action == 2 requires blacklist absence, both checked twice, once with the final octet zeroed for /24 subnet matching and once for the exact host.Β
Once all checks are cleared the chosen file is opened, stored in the per-connection ted_rep_state as fpAppend and nTotal, alongside a script_conf back-reference to the matched rule. The replace byte at offset 0x00 of that rule sets flag to 4 when zero and 2 when non-zero, distinguishing appending content from substituting it. Finally the code sets its filter flag and increments nb_rsp_data_filters or nb_req_data_filters on the stream, which is HAProxy's documented opt-in for body accessβ this time reusing the internal structure of the load balancer to inject code into the page at delivery time.
Figure 16: Hooking the HTTP response
β
Once a victim is marked for injection, two callbacks finish the job on the way out. ted_http_headers_for_htx runs first, and only when the data is on the response side, a state block is initialized during the request, and the transaction flag is set. It rechecks the response against the rule that matched earlier, testing Content-Type and the status line, so a payload is delivered only when the reply is a document worth modifying. It then reshapes the response to fit the incoming file: sets Content-Type, adds a Content-Disposition filename if the rule has one, writes the new body length into the custom length header, deletes Accept-Ranges so the client cannot request byte ranges and spot the size mismatch, and forces the status to 200OK if it was anything else.
ted_http_payload performs the swap. For each body chunk, it takes only as much as the payload file has left, reads that slice from disk, decrypts it with ngx_decrypt_script, and substitutes it through HAProxy's own body-editing calls. When the replacement changes the body length, the code shifts every remaining filter's offset by the difference, so nothing downstream sees an inconsistency. With the rewritten length header and range support stripped, the size change leaves no trace.
trace_http_end handles the leftover bytes. The previous callback can only overwrite bytes that already exist in the response, so when the payload is larger than the original body there is a remainder with nowhere to go. This function runs at the end of the response and appends it. It checks that the state block is in an injection mode, that the headers were already rewritten, and that fewer bytes have been delivered than the payload holds. If so, it measures the free space left in the response buffer, reads exactly that much from the payload file, decrypts it with ngx_decrypt_script, and appends it as a new data block, bumping the channel's output count to match.Β
The result is that a payload of any size can be delivered across as many passes as it takes, using HAProxy's own scheduler to drive the process.
To ensure persistence, curlRAT is integrated and hidden as libc routines.
Figure 17: ted backdoor including curlRAT configuration a8bfab4de81a1acb04aacdf757346946b0f5e30f0c9f402004016d0e425119c7
β
Attacker infrastructure
The observed infrastructure follows a consistent pattern: Domains are registered under low-cost commodity TLDs β.store, .space, .site, .autos β and use subdomain schemes mimicking image-serving CDN endpoints (img.) They then blend payload delivery traffic into normal web browsing. The naming convention across suggests a shared registration workflow rather than ad-hoc infrastructure. Theimg.responsive.pstatic.autos mimics Naver'spstatic.net static content domain, a South Korean web platform, which combined with the watering-hole delivery model adopted by the ted backdoor is consistent with targeting of Korean-speaking users.
Attribution
At the time of the analysis, compromised servers had exposed the Groupware login portal on port 443, which is heavily present in Korean enterprise environments. The targeting of regional software (Groupware), mimicking Naver's static content domain, usage of simple xor and substitution ciphers and the watering-hole model already documented in the Operation Code on Toast (APT37)and Operation Synchole (Lazarus),allows medium confidence attribution to DPRK APT. The list of C2s hardcoded is associated with APT37 by ThreatFox and maltrail.
The campaign's timeline and delivery mechanism overlap with Operation SyncHole, a concurrent Lazarus campaign documented by Kaspersky running from November 2024 through February 2025, in which Lazarus compromised South Korean media sites to redirect visitors to pages serving malicious JavaScript payloads. APT37 and Lazarus Group are distinct North Korean state-sponsored threat clusters assessed by Mandiant to operate under different DPRK agencies β APT37 under the Ministry of State Security, Lazarus under the Reconnaissance General Bureau β though both conduct cyber espionage targeting South Korean entities. Lazarus has been observed to deploy backdoored open-source programs to deliver malware and use feedback XOR + base64 to interact with the C2 by Kaspersky. As of July 2026, similar suspected initial access has been reported by ENKI WhiteHat, suggesting that if a vulnerability in South Korean mail appliances exists, the exploitation could still be ongoing and leveraged by DPRK APTs.
Further evidence is necessary to make a more definitive assessment. Moreover, the presence ofngx_* prefixed routines within the ted backdoorsuggest code reused from an nginx backdoor. The ngx_* prefixed routines were observed during the latest Funnull campaign, where (similar to our case) a custom nginx filter was registered to hook HTTP traffic, and simple XOR encryption was applied to the configuration file. However, other than a similar naming convention, no significant code-level overlaps exist to support a stronger linkage.
Conclusion
ted backdoor and curlRAT were designed to persist during long-term espionage operations with the ability to steal cookie sessions, credentials, redirect selected users, conduct drive-by download attacks, and hide evidence of the tampered page to a specific range of IPs to evade detection. Defenders should treat any edge component managing user traffic, SSL, or runtime modules with the same strict security standards as their main application servers. Relying on the component's own logs is not enough; securing these systems requires independent network correlation, memory behavioral analysis, and binary integrity checks.
MITRE ATT&CK techniques
Tactic
Technique
Detail
Component
Initial access
[T1190]Β Exploit public-facing application
HAProxy filter API abused as injection point; watering-hole payload delivery via compromised load balancer
ted backdoor
Execution
[T1059.004] Unix shell
popen() used for one-shot command execution per opcode '3'; PTY shell spawned per opcode '5'; reverse shell per opcode '3' in CurlRAT
ted backdoor, CurlRAT
Execution
[T1106] Native API
pthread_create / pthread_detach for detached shell threads; HAProxy pool_alloc / task_wakeup for async response scheduling
Response body replaced or appended with decrypted payload script via HAProxy data filter callbacks; Content-Type, Content-Length, Content-Disposition rewritten; 200 OK forced; Accept-Ranges stripped
ted backdoor
Collection
[T1119] Automated collection
Passive capture logs timestamped records per matched request; expanded * records written when Accept-Language mrt key present
ted backdoor
C2
[T1071.001] Application layer protocol: web protocols
ted C2 tunnelled as HTTP through load balancer; CurlRAT polls C2 over HTTPS with libcurl fallback to HTTP; all payloads as application/x-www-form-urlencoded POST
CurlRAT, ted backdoor
C2
[T1132.001]Β Data encoding: standard encoding
All CurlRAT C2 payloads Base64-encoded after feedback XOR; ted pipe protocol uses raw bytes with rolling XOR session key
CurlRAT, ted backdoor
C2
[T1102] Web service
CurlRAT falls back to secondary C2 img.monderhouse.space on config validation failure; img.darklights.store used as backup config host
CurlRAT
C2
[T1572] Protocol tunnelling
Interactive shell tunnelled through HAProxy HTTP pipeline via named FIFOs; response exfiltrated via raw send() on TCP socket bypassing HAProxy logging
ted backdoor
C2
[T1568] Dynamic resolution
CurlRAT victim ID derived from hostname + IP + hardware UUID + cron version string, MD5'd and uppercased; used as User-token header in all C2 requests
CurlRAT
Exfiltration
[T1041] Exfiltration over C2 channel
SSH credentials exfiltrated via CurlRAT C2; session capture logs written by ted; CurlRAT mode 0 streams command output back over same channel
Stager, CurlRAT, ted backdoor, SSH keylogger
Exfiltration
[T1560] Archive collected data
SSH keylogger output encrypted with substitution cipher before writing; CurlRAT applies feedback XOR + Base64 to all outbound data
On September 1, 2026, SonicWall disclosed two vulnerabilities affecting SonicWall SMA1000 appliances that the vendor says are being actively exploited in the wild. The vulnerabilities, CVE-2026-83548 and CVE-2026-83549, can be chained to achieve unauthenticated remote code execution (RCE) on affected appliances.
CVE-2026-83548 is a critical pre-authentication server-side request forgery (SSRF) vulnerability in the SMA1000 Appliance Work Place interface. The flaw has a CVSS v3.1 base score of 10.0 and can allow a remote, unauthenticated attacker to access sensitive functionality and perform unauthorized operations through an unintended alternate access path.
CVE-2026-83549 is a high-severity OS command injection vulnerability in the Appliance Management Console (AMC). On its own, exploitation requires an authenticated administrator and specific system conditions. Although, by leveraging the SSRF vulnerability CVE-2026-83548 an attacker could potentially exploit CVE-2026-83549 to execute arbitrary OS commands without prior authentication.
SonicWall SMA1000 appliances are enterprise secure remote access gateways used to provide employees and other authorized users with access to internal applications and resources. Their role as network-edge systems makes successful exploitation particularly concerning, since affected Work Place interfaces may be exposed directly to the internet as part of normal deployment.
SonicWall has confirmed active exploitation of both vulnerabilities in the wild, and both CVE-2026-83548 and CVE-2026-83549 have been added to CISA's Known Exploited Vulnerabilities (KEV) catalog. No public proof-of-concept exploit, indicators of compromise (IOCs), or attribution for the current activity were identified in the research available at the time of publication.
The vulnerabilities affect SMA1000 Models - 6210, 7210, 8200v running the following versions:
Vulnerable Versions
Fixed Versions
12.4.3-03453 platform-hotfix and earlier
12.4.3-03526 (platform-hotfix) and higher versions
12.5.0-02835 platform-hotfix and earlier
12.5.0-02952 (platform-hotfix) and higher versions.
Mitigation guidance
Organizations operating affected SonicWall SMA1000 appliances should prioritize applying SonicWallβs updated platform hotfixes immediately. Because exploitation was occurring before public disclosure, organizations should not rely solely on patching to determine whether an appliance has already been compromised.
SonicWall recommends upgrading affected appliances to:
12.4.3-03526 platform-hotfix, for systems on the 12.4.3 branch
12.5.0-02952 platform-hotfix, for systems on the 12.5.0 branch
Affected Product/Component:
SonicWall SMA1000 Appliance Work Place and Appliance Management Console
Version 12.4.3-03453 platform-hotfix and earlier are affected.
Version 12.5.0-02835 platform-hotfix and earlier are affected.
SonicWall additionally recommends that customers contact SonicWall Technical Support for assistance reviewing appliances for indicators of compromise.
If evidence of compromise is identified, SonicWall recommends:
Re-imaging affected hardware appliances or re-deploying affected virtual appliances.
Given the confirmed exploitation of these vulnerabilities, organizations should treat potentially exposed appliances running vulnerable software as a priority for investigation as well as remediation.
Please read the SonicWall security advisory for the latest vendor guidance.
Rapid7 customers
Exposure Command, InsightVM, and Nexpose
Exposure Command, InsightVM, and Nexpose customers can assess exposure to CVE-2026-83548 and CVE-2026-83549 in the SMA1000 Appliance series with vulnerability checks expected to be available in the September 3rd content release.
On August 27, 2026, PaperCut Software published an urgent security advisory stating that it is investigating active exploitation of a vulnerability affecting PaperCut NG and PaperCut MF. PaperCut has confirmed customer incidents and is treating the issue as a security emergency. At the initial time of disclosure, the vulnerability had not been assigned a CVE identifier, and PaperCut had not publicly disclosed a CVSS score, vulnerability class, authentication requirements, or the technical details of the exploit path. However on August 28, the vendor assigned CVE-2026-81578 and CVE-2026-82078 for the two vulnerabilities that make up the exploit chain.
CVE ID
Description
CWE
CVSSv4
CVE-2026-81578
Authentication Bypass
CWE-306 Missing authentication for critical function.
PaperCut NG and PaperCut MF are print management platforms commonly deployed within enterprise, education, and other organizational environments. Because the PaperCut Application Server provides web-accessible administrative and application functionality, organizations with servers exposed to the public internet should prioritize remediation and access restriction.
PaperCut stated in its advisory that information supplied by a university customerβs security team and digital forensics and incident response team enabled its security response team to reproduce the vulnerability in PaperCut NG and PaperCut MF. On August 28, 2026 at 02:10 AEST, PaperCut released emergency patches for PaperCut NG and PaperCut MF versions 25 and 26, followed later the same day with patches for version 24.
PaperCut has been targeted in the past; in 2023, CVE-2023-27350 was broadly exploited in the wild by multiple threat-actor groups, including ransomware operators. This prior history increases the urgency organizations should address this new zero-day with.
PaperCut currently considers all versions of PaperCut NG and PaperCut MF potentially impacted. Customers operating internet-accessible PaperCut Application Servers should take immediate action even if no suspicious activity has been observed.
On August 31, 2026, both CVE-2026-81578 and CVE-2026-82078 were added to the U.S. Cybersecurity and Infrastructure Security Agencyβs (CISA) list of known exploited vulnerabilities (KEV), based on evidence of active exploitation. A Metasploit module is now available to validate exposure to the exploit chain.
Technical overview
The vulnerability is an authentication bypass that lets attackers invoke privileged PaperCut components. This can be leveraged to reconfigure an external database lookup. When this lookup is triggered, malicious SQL can be executed, resulting in remote code execution.
PaperCut uses the Apache Tapestry framework, whose "complex direct" request format can identify one page to display and a different page containing the component to execute. PaperCut validates access only to the displayed page. By selecting either the public Error page or Exception page for display, an attacker can bypass authentication while invoking administrative components belonging to ConfigEditor or UserList. Additionally, the first emergency patch could be bypassed by using the Home page for display, however the newest version of the vendor patch correctly remediates this bypass.
The attack uses HTTP POST requests to the following URIs (Note that the path segment with the value 1 shown below can be any value for this path segment, and the Error path segment may also be the Exception or Home path segment):
The first two URIs provide unauthenticated access to PaperCut's configuration editor. The third can invoke a user or card search that triggers the configured external database lookup.
An attacker first uses the ConfigEditor requests to modify four external user-lookup settings:
These settings normally allow administrators to connect PaperCut to an external card database. After bypassing authentication, however, the attacker can configure them with a malicious JDBC connection and a malicious SQL statement.
By leveraging PaperCut's bundled Apache Derby database driver and supplying a Derby CALL statement that activates its foreignViews feature, Derby opens an attacker-controlled H2 JDBC URL. H2 processes an inline INIT statement that creates a JavaScript-backed database trigger. PaperCut includes the Nashorn JavaScript engine, allowing that trigger to start an operating-system process. However it is expected that other mechanisms to execute an arbitrary command can also be used instead of Nashorn. Finally, the attacker submits a search through the forged UserList request. This activates the external lookup and executes the malicious SQL.
Mitigation guidance
Organizations running PaperCut NG or PaperCut MF should prioritize patching on an emergency basis, particularly where the PaperCut Application Server is accessible from the public internet.
PaperCut has released emergency patches for PaperCut NG and PaperCut MF versions 24, 25 and 26.Β
Updated on September 1, 2026: Note that the vendor has released a third version of the emergency patch. Any organization that has applied either the original first version or the second version of the emergency patch is not fully protected, and must apply the third emergency patch immediately.
The vendor notes that these builds have not undergone their normal release process and are intended as emergency fixes for customers with public-facing servers that cannot otherwise sufficiently mitigate exposure.
PaperCut recommends that administrators immediately restrict web access to trusted IP addresses only, such as internal corporate network ranges. Firewall rules, network access controls, reverse-proxy restrictions, or equivalent measures should be used to prevent untrusted internet hosts from reaching PaperCut web interfaces.
Please read the PaperCut security advisory for the latest remediation guidance, updated indicators of compromise, and additional release information.
Artifacts/Evidence Sources and IOCs
For detection and forensic analysis, PaperCut has identified several preliminary artifacts and evidence sources that may indicate compromise.
Application activity: Alerts from intrusion-detection, endpoint-security, or network-monitoring products involving the PaperCut Application Server, particularly suspicious post-exploitation activity associated with pc-app.exe.
Log integrity: Missing, unexpectedly truncated, or deleted PaperCut server.log files.
PaperCut server.log entries:
ERROR No suitable driver found for jdbc:no:x
ERROR DatabaseUtils - Database error looking up cardID: VALUES CAST
PaperCut has not yet published validated network-based indicators such as malicious IP addresses, domains, or URLs.
The vendor specifically warns that the absence of these indicators should not be interpreted as evidence that a system has not been affected.
Rapid7 customers
Exposure Command, InsightVM, and Nexpose
Exposure Command, InsightVM, and Nexpose customers can assess exposure to this new PaperCut zero-day, with an authenticated vulnerability check expected to be available in the August 28 (todayβs) content release.
Updates
August 28, 2026: Initial publication.
August 28, 2026: Updated to reflect new emergency patches and CVE ID assignment. Updated remediation to include the new v24 patches. Updated Technical Overview to indicate first patch bypass.
August 31, 2026: Updated the Overview to note that both CVEs were added to the CISA KEV list, and the availability of a Metasploit module.
September 1, 2026: Updated the Remediation section to reflect the vendor's new emergency patch (release 3).
Despite modern verification controls, identity theft remains one of the most pervasive threats to both individuals and enterprise organizations. U.S. Federal Trade Commission statistics show over 1 million identity theft reports annually, with related fraud and imposter scams accounting for billions in financial losses each year. While stolen credit cards enable rapid, short-term monetization, Social Security numbers (SSNs) represent a far more permanent and dangerous tier within the cybercrime ecosystem, because unlike payment cards, they cannot simply be deactivated.Β Once exposed, an SSN can supportΒ enabling unauthorized lines of credit, synthetic identity fraud, and sophisticated tax scams.
When exposed identity data belongs to corporate executives, board members, and other high-profile employees, the risk can extend beyond the individual. Threat actors target these high-profile individuals not just for their premium credit profiles, but to leverage their compromised identities for executive impersonation, corporate espionage, and downstream extortion. Rapid7βs recent alert telemetry underscores the severity of this targeted exposure: since early 2026 alone, we identified 476 instances of compromised SSN records across 395 unique corporate personnel. Over 73% of these exposures directly targeted top-level leadership, with C-suite executives comprising 44.6% of affected profiles and Presidents making up another 28.6%. Unsurprisingly, given the geographical nature of SSNs, 95.6% of these leaks stemmed from U.S.-headquartered organizations, concentrated heavily in high-value sectors like Financials (over 25%) and Industrials (17%).
In this blog, we explore the operational mechanics of the underground identity economy, focusing on three dominant SSN marketplaces tracked by Rapid7: Xilo, Bankom, and PeopleFinder, which together account for 81.5% of all executive SSN leaks in our dataset (led by Xilo at 40.8%, Bankom at 21.8%, and PeopleFinder at 18.9%). Using Rapid7 alert telemetry from the past year, we look at the profiles of affected corporate executives, how these marketplaces operate,Β and highlight how proactive dark web monitoring can mitigate upstream identity exposure before it is weaponized.
Why stolen SSNs retain their value
Not all stolen data retains its value for the same length of time. Leaked credentials can be reset, payment cards can be cancelled, and session tokens eventually expire. While these data types remain highly sought after by cybercriminals, their usefulness often depends on acting quickly before the victim or service provider invalidates them.
SSNs differ as they are effectively permanent, serving as a core identity attribute. Once exposed, they can remain valuable for years, enabling a wide range of fraud schemes long after the original breach. When combined with other personally identifiable information (PII), such as a victim's name, date of birth, address, phone number, and employment history, an SSN becomes the foundation of a comprehensive identity profile that can be bought, sold, and repeatedly abused across the criminal ecosystem.
These identity profiles enable far more than traditional identity theft. Threat actors use them to open fraudulent financial accounts, create synthetic identities, bypass identity verification processes, file fraudulent tax or government benefit claims, and support highly targeted social engineering campaigns. Rather than serving a single purpose, a complete identity record becomes a reusable asset that can be monetized multiple times by different threat actors.
For corporate executives and other high-profile employees, exposed identity data can also create risk for the organization they represent. Publicly available information, from regulatory filings to corporate biographies and social media, can be combined with stolen identity data to build highly detailed profiles. These enriched records increase the credibility of phishing, business email compromise (BEC), and executive impersonation attacks, allowing threat actors to target not only the individual but also the organization they represent.
This durability has fueled a thriving underground economy where identity records are treated as searchable, reusable inventory rather than one-time commodities. The marketplaces examined in this research demonstrate just how mature and accessible this ecosystem has become.
Anatomy of an SSN marketplace
While platforms like Xilo, Bankomat, and PeopleFinder present a highly organized, user-friendly storefront, they operate strictly as downstream clearinghouses rather than original creators of their inventory. The vast supply of SSNs flooding these networks relies on a distinct, multi-tiered underground supply chain. The massive volume driving these platforms is primarily fueled by large-scale institutional network breaches, where wholesale hackers compromise data aggregators, healthcare systems, and financial providers. These massive SQL databases are sold in bulk on deep-web forums, where marketplace administrators purchase, parse, and upload them into their searchable storefronts. According to annual telemetry from the Identity Theft Resource Center, billions of individual data records are exposed annually through these mega-breaches, accounting for the vast majority of the inventory available online.
Another source of identity data comes from infostealer malware and targeted phishing campaigns. While mass breaches provide wholesale numbers, infostealers scrape highly contextual local data, such as saved browser forms and PDF documents like tax returns or corporate onboarding paperwork stored on unmanaged personal devices. When these localized logs are parsed by marketplace administrators, they yield the fresh, high-value identity profiles that allow buyers to target specific corporate leaders.
Although these platforms tap into a similar upstream supply chain, how they package and monetize this data varies significantly. To stand out in a maturing, highly competitive cybercrime market, each marketplace focuses on its own operational niche, ranging from ultra-low pricing and identity enrichment features to multi-asset carding integration and legacy data consistency. The following sections provide a deep dive into each marketplace, highlighting their specific functionalities, user interfaces, and distinct market advantages.
XiloΒ
Xilo has been active since at least March 2025. The marketplace is hosted as a Tor hidden service, while also maintaining mirror sites on the clear web to improve accessibility and resilience.
Users can search for specific individuals by name, state, country (US or Canada), or year of birth (Figure 1). They can also request records that include phone numbers and email addresses in addition to the victim's SSN. This can increase the value of the records by reducing the need for threat actors to source additional PII elsewhere. During our analysis, however, we did not identify any records that included email addresses, while records containing phone numbers were available at the same price as standard SSN records. Search results can also be sorted by price, although the cost appears to be fixed at $0.25 per SSN record.
Figure 1 β Xilo search interface
β
Search results typically display the victim's full name, physical address, and date of birth before purchase. This information alone can help threat actors identify specific individuals for targeted campaigns, while the SSN is revealed only after the purchase is completed (Figure 2).
Figure 2 β Xilo search results
β
In addition to standard searches, Xilo offers a reverse lookup service that accepts an SSN or phone number and returns additional PII, including the victim's full name and phone number (Figure 3). This service costs $0.50 per lookup, suggesting that enriching an existing identity profile is considered more valuable than purchasing an SSN alone. Threat actors can use this functionality to expand records obtained through the standard search, increasing the amount of PII associated with a single individual and, consequently, the potential for identity fraud.
Figure 3 β Xilo reverse search
β
The marketplace is supported by a Telegram channel used to announce technical updates and new domains. Although activity on the channel has been relatively limited, it has attracted more than 500 subscribers, providing an indication of interest in the service. Like many established cybercriminal services, Xilo appears prepared for domain disruptions by maintaining alternative access points and communicating them through Telegram, adopting the kind of resilience and service-continuity practices more commonly associated with legitimate online services.
Xilo accepts several cryptocurrencies, including Bitcoin, Litecoin, Monero, Ether, and Tether (USDT). Support for USDT is relatively uncommon among underground marketplaces and may reflect the marketplace's focus on US-based identity data. The minimum deposit is just $1, lowering the barrier to entry for new users, while bonuses are offered for deposits exceeding $100 to encourage larger account balances.
Beyond its own infrastructure, Xilo actively advertises on well-known cybercrime forums, including XSS, as well as carding communities such as WWH-Club and Altenens (Figure 4). This marketing strategy is common among underground marketplaces seeking to expand their customer base. More notably, Xilo's presence on carding-focused forums highlights the close relationship between stolen payment data and identity information, illustrating how different segments of the cybercrime ecosystem increasingly overlap and complement one another.
Figure 4 β Xilo advertisement on Altenens
Bankomat
Active since at least March 2022, Bankomat is one of the more established marketplaces operating in the underground identity theft ecosystem. The platform is accessible as a Tor hidden service while maintaining multiple clear web domains to improve availability. Its emergence coincided with the shutdown of several prominent carding and PII marketplaces, including Joker's Stash and SSNDOB Marketplace, suggesting that Bankomat sought to capitalize on the resulting gap by combining identity data sales with traditional carding services.
The marketplace prominently lists its active domains and encourages users to save its onion address, describing it as the most reliable way to access the service. This reflects an awareness of the operational challenges faced by long-running underground marketplaces, particularly the risk of domain seizures and takedowns. By maintaining multiple access points and actively directing users toward its Tor service, Bankomat demonstrates the operational maturity needed to retain its customer base despite infrastructure disruptions.
Users can search for individuals by first and last name, combined with an additional identifier such as state, city, ZIP code, or date of birth (Figure 5). The search functionality is free, allowing users to identify potential victims before deciding whether to purchase a record. Search results display the victim's full name, date of birth, and physical addresses, while the SSN is revealed only after purchase at a fixed cost of $4 per record. Unlike Xilo, however, Bankomat does not offer additional identity enrichment services or the ability to purchase supplementary PII directly through the platform.
Figure 5 β Bankomat search bar
β
Beyond SSN records, Bankomat also functions as a traditional carding marketplace by offering stolen payment card details for sale, obtained through third-party sellers. The platform supports card validation services, including Viper and 4chk, allowing buyers to verify whether stolen payment cards remain active before using or reselling them. Similar functionality is offered by established carding marketplaces, such as Findsome and UltimateShop.
This combination of identity records, payment card data, and validation tools positions Bankomat as a one-stop marketplace for financially motivated threat actors. Rather than sourcing stolen identities and payment data from separate platforms, buyers can acquire multiple data types associated with the same victim through a single service. While SSN records cost $4, stolen payment card details are typically advertised for approximately $10, suggesting that Bankomat places greater commercial emphasis on its carding business, likely reflecting both higher profit margins and sustained demand within the underground economy (Figure 6).
Figure 7 β PeopleFinder SSN listings
β
Bankomat currently accepts payments exclusively in Bitcoin, in contrast to newer marketplaces that increasingly support a wider range of cryptocurrencies to appeal to a broader customer base.
PeopleFinder
Active since at least February 2023, PeopleFinder is a successor to the SSNDOB Marketplace, whose primary domains were seized by law enforcement in June 2022. Following that takedown, the service re-emerged through a network of lookup mirrors using clear-web-sounding domain names such as βPeopleFinder.β The connection is also visible in the source code, where the front-end login page retains the original βssndobβ title text and logo. Through this infrastructure, the platform provides access to the same legacy database of more than 24 million compromised U.S. PII records.
To maintain a steady customer stream, PeopleFinder actively advertises its database on high-profile cybercrime and carding forums like WWH-Club and Exploit. This deliberate marketing keeps the service highly visible to financially motivated threat actors seeking verification tools for downstream fraud.
The layout itself is highly streamlined, featuring a basic search bar that closely mirrors Bankomat's interface. Users can search the platform's database by name, date of birth, or physical address completely free of charge. The initial search output displays the victim's full name, date of birth, and associated physical addresses, allowing a threat actor to confirm they have targeted the correct corporate executive before paying for the record (Figure 7).
Figure 7 β PeopleFinder SSN listings
To reveal the hidden SSN, users must pay a fixed cost of $1.50 per lookup, putting its pricing structure right between Xilo and Bankomat. This strict, hyper-commoditized focus solely on core SSN details directly mirrors the operational blueprint of the original SSNDOB model. Rather than expanding into supplementary data types like phone numbers or credit cards, the operators chose to preserve their highly efficient, legacy pay-per-lookup infrastructure. The platform relies exclusively on Bitcoin transactions.
What Rapid7 telemetry reveals about the executive threat landscape
By monitoring dark web SSN marketplaces, Rapid7 actively alerts clients when leaked records of their executives or designated employees are discovered.
Since the beginning of 2026, our telemetry has identified 476 instances of compromised SSN records, representing 395 unique individuals, as several monitored personnel were affected by multiple exposures. Within this sample, most of the leaked SSNs were recorded in Xilo (40.8%), followed by Bankom (21.8%) and PeopleFinder (18.9%) (Figure 8).
Figure 8 β The sample distribution of leaked SSNs by marketplace
β
Given that SSNs are issued within the United States, the overwhelming majority of compromised records in our dataset, 95.6%, were linked to organizations headquartered in the U.S., with others located in Spain, Canada, and Japan, trailing significantly behind (Figure 9).
Figure 9 β The sample distribution of leaked SSNs by country
β
Financials represented the largest sector in our sample, accounting for more than a quarter of organizations whose monitored executives appeared in leaked SSN records, followed by Industrials at 17% (Figure 10). One possible reason for the concentration in Financials is the volume and sensitivity of customer and employee data these organizations hold, including PII and tax-related information, which can make exposed identities particularly valuable to threat actors. Industrials may also present attractive targets because of their interconnected supply chains, where compromised identities can potentially support broader fraud, impersonation, or access attempts across partner ecosystems.
Figure 10 β The sample distribution of leaked SSNs by sector
β
A closer analysis of the roles of targeted personnel reveals that C-suite executives (such as Chief Executive Officers and Chief Financial Officers) make up the largest portion at 44.6%. Presidential positions represent the second-largest segment at 28.6%, while functional management and administrative roles account for 13.9% of the compromised profiles.
These findings may reflect a natural monitoring bias, since organizations are more likely to prioritize senior personnel whose compromise poses a greater security risk. Even with that caveat, the concentration among senior leadership reinforces why executive identity exposure deserves specific attention.
Compromised executive PII can support targeted phishing, impersonation, and other social engineering campaigns against both the individual and the organization they represent.
Board Trustees, Directors of the Board, State Senators, Vice Chairs
18
4.6%
Total Unique Individuals
395
100.0%
From detection to action: Responding to exposed executive PII
Because SSNs cannot simply be reset after exposure, organizations need a way to identify compromised executive PII early and determine what action can reduce the resulting risk.
These alerts are triggered using customer-defined assets, specifically the names of designated VIPs. When a potential match is flagged, Rapid7 analysts conduct preliminary OSINT verification, checking biographical details such as the VIP's date of birth and primary locations, to confirm the listing's accuracy before issuing an alert to the customer.
Once alerted, customers can choose to purchase the exposed SSN record directly through the "Ask-an-Analyst" service using their allocated dark web purchase credits (Figure 11). This capability allows security teams to inspect the full record, verify whether the exposed SSN is genuine, and determine whether additional protective measures are necessary for the affected executive. Furthermore, on platforms like Xilo, purchasing the listing removes the record from the marketplace entirely, actively taking it off the shelf before other threat actors can acquire it.
Figure 11 β Rapid7 Platform alert about the leaked details of a company executive
Conclusion and strategic defense actions
The illicit marketplaces examined by Rapid7 show how cheaply and efficiently stolen identity data can now be searched, purchased, and enriched. For executives and other high-profile employees, an exposed SSN can remain useful to threat actors long after the original compromise and may support identity fraud, social engineering, executive impersonation, or business email compromise. Because that information cannot simply be reset, organizations should treat executive identity exposure as an ongoing security risk.
To reduce that risk, executive protection and security teams should consider the following actions:
Monitor executive exposure on the dark web: Use digital risk protection capabilities configured with executive names, known locations, titles, and other relevant identifiers to detect compromised PII across illicit marketplaces and underground channels.
Use removal or takedown options where available: Where supported, work with security providers to acquire or remove exposed identity records before they are purchased and reused by other threat actors.
Reduce executivesβ public digital footprint: Review public records, data-broker listings, corporate biographies, and social media profiles to limit unnecessary exposure of information such as dates of birth, home addresses, and phone numbers that can be used to enrich stolen records.
Require out-of-band verification for sensitive requests: Introduce mandatory secondary confirmation for financial transactions, access requests, or administrative changes involving executive accounts to reduce the risk of successful impersonation.
Provide targeted phishing and impersonation training: Give C-suite members, board members, and executive assistants focused guidance on how attackers can combine leaked PII with social engineering to make phishing and impersonation attempts more convincing.
The persistence of SSNs means the risk does not end when the original breach is discovered. Ongoing monitoring, rapid validation, and stronger verification controls can help organizations identify exposure earlier, reduce the value of stolen identity data, and make it harder for threat actors to turn compromised executive information into a wider attack against the business.
On August 19, 2026, a security advisory was published for CVE-2026-19490, a critical authentication bypass vulnerability affecting Citrix NetScaler ADC and NetScaler Gateway. The vulnerability carries a CVSS v4.0 base score of 9.3 and can be exploited remotely by an unauthenticated attacker over the network without user interaction or elevated privileges.
NetScaler ADC and NetScaler Gateway are widely deployed enterprise networking products commonly positioned at or near the network perimeter. NetScaler ADC provides application delivery, traffic management, load balancing, SSL/TLS offloading, and application security capabilities, while NetScaler Gateway provides secure remote access and VPN functionality. Because these systems are frequently deployed in enterprise DMZs and exposed to the public internet, authentication bypass vulnerabilities affecting Citrix products are nearly always exploited by threat actors.
NetScaler ADC and NetScaler Gateway 14.1: Versions prior to 14.1-73.32
NetScaler ADC and NetScaler Gateway 13.1: Versions prior to 13.1-63.21
NetScaler ADC FIPS: Versions prior to 14.1-73.32 FIPS
NetScaler ADC FIPS and NDcPP: Versions prior to 13.1-37.277
As of August 19, 2026, Rapid7 has not observed evidence that CVE-2026-19490 is being exploited in the wild. However, organizations should prioritize patching affected systems on an emergency basis, since Citrix products are high-value targets that tend to quickly see exploitation in the wild.
On September 9, 2026, CVE-2026-19490 was added to the U.S. Cybersecurity and Infrastructure Security Agencyβs (CISA) list of known exploited vulnerabilities (KEV), based on evidence of active exploitation. With active exploitation now occurring, organizations running affected versions of Citrix NetScaler ADC and NetScaler Gateway should remediate these issues on an urgent basis, outside of normal patching cycles.
Mitigation guidance
Organizations running affected NetScaler ADC or NetScaler Gateway appliances should review the official NetScaler advisory and apply the required updates to affected systems on an emergency basis.
Fixed versions for affected products are listed below:
NetScaler ADCβ―and NetScaler Gateway14.1-73.32 and later releases
NetScaler ADCβ―and NetScaler Gateway13.1-63.21 and later releases of 13.1
NetScaler ADC 14.1-FIPS14.1-73.32 FIPS and later releases of 14.1-FIPS
NetScaler ADC 13.1-FIPS and 13.1-NDcPP13.1-37.277 and later releases of 13.1-FIPS and 13.1-NDcPP
According to Citrix, customers can determine whether affected systems are vulnerable to CVE-2026-19490 by inspecting their NetScaler configuration for the following configuration entries. If one or more of the following items are present, and if the systems are running affected versions, the system is likely to be exploitable:
SAML action configuration is in place:
"add authentication samlAction.*"
Auth or VPN vserver is configured:
Β "add authentication vserver .*"
Β "add vpn vserver .*"
For the latest guidance, please refer to the official Citrix advisory.
Rapid7 customers
Exposure Command, InsightVM, and Nexpose
Customers can assess exposure to CVE-2026-19490 on Citrix NetScaler ADC and Gateway using a vulnerability check available in the August 20 content release.
Updates
August 19, 2026: Initial publication.
August 20, 2026: Updated Rapid7 customers section to reflect availability of vulnerability check.
September 11, 2026: Updated Overview to add new CISA KEV reference.
CΓ‘ssio De AlcΓ’ntara is Director, LATAM Sales at Rapid7.
Across Latin America, organizations are embracing cloud, AI, and digital transformation to drive innovation and business growth. These technologies create new opportunities, but also introduce greater complexity and expanding attack surfaces.
In this environment, security leaders are being asked to understand where risk exists across increasingly distributed environments and quickly eliminate blind spots like Shadow IT and Shadow AI β all without adding operational complexity.
To help security leaders and practitioners address this complexity, Rapid7 is excited to announce a new strategic distribution partnership with Licencias OnLine (LOL) across Latin America.
Helping organizations stay ahead of evolving threats
In order to keep day-to-day business operations moving, organizations need security solutions that not only protect critical assets but also support innovation, regulatory compliance, and long-term digital transformation.
Rapid7's AI-powered cybersecurity operations platform helps organizations strengthen cyber resilience by unifying continuous exposure management, AI-driven threat detection and response, and security automation. By connecting security data across endpoint, cloud, identity, and infrastructure environments, organizations leverage one platform to gain the visibility to reduce risk and act with confidence.
A shared commitment to partner success
Success in todayβs fragmented cybersecurity environments depends on a strong ecosystem of partners who can help organizations implement, optimize, and maximize the value of unified security operations.
This is where Licencias OnLine comes in. With a strong, well-established presence across Latin America, deep cybersecurity expertise, and a highly specialized channel ecosystem, Licencias OnLine brings the local knowledge, technical enablement, and operational agility needed to help partners grow their cybersecurity practices and deliver greater value to customers.
Together, Rapid7 and Licencias OnLine will invest in technical training, partner enablement, joint marketing initiatives, and go-to-market programs that help partners expand managed security services, strengthen customer relationships, and accelerate business growth across the region.
Building cyber resilience together
As organizations across Latin America continue to modernize their IT environments, they should have access to security operations that are integrated, intelligent, and designed for today's AI-powered threat landscape.
Rapid7's open platform supports this approach through hundreds of technology integrations that help organizations eliminate security silos, improve visibility across their attack surfaces, and automate response workflows. This enables security teams to reduce operational complexity while improving cybersecurity program maturity.
By combining Rapid7's global cybersecurity innovation with Licencias OnLine's regional expertise and trusted partner network, this new alliance will make it easier for organizations across Latin America to strengthen cyber resilience while enabling partners to see greater success through measurable business outcomes.
We're excited to begin this next chapter together and look forward to supporting our partners as they help customers build stronger, more resilient security operations across the region.
You canβt patch everything. So what do you fix first? Findings in Q2 2026 have changed traditional answers.
The latest Quarterly Threat Landscape Report from Rapid7 Labs shows vulnerability disclosures still surging while attackers use automation and AI-assisted tooling to compress the time between disclosure and exploitation. The gap that patch cycles were built to fill is closing. Speed and volume are overwhelming security teams that have relied on traditional patch cycles and reactive programs. Success going forward canβt be about patching as much as possible -Β it has to be about understanding what matters most and reducing the exposures attackers can actually reach.
Here are the four trends that defined Q2 2026, and what they mean for your security program as you define priorities for Q3 and beyond:
The volume of disclosures hit another milestone
There were 8,539 new high- and critical-severity CVEs (CVSS 7.0β10.0) this quarter- double the number reported in the same quarter last year (4,268). Meanwhile, the number of newly exploited vulnerabilities held roughly steady (40). The takeaway isnβt that exploitation exploded - itβs that disclosure volume is far outstripping what any team can triage.
The report breaks down which of those disclosures are actually reachable and how to triage by exploitability instead of severity score alone.
Initial access keeps getting easier
Nearly two-thirds of exploited vulnerabilities this quarter (62%) required no user interaction - no stolen credentials, no phishing victim, no click. Attackers reach and exploit them on their own, and that share is up nine points year over year (from 53% in Q2 2025). Reinforcing the trend, disclosures of missing-authentication flaws (CWE-306) surged 247% year over year - a fast-expanding pool of internet-facing systems that require no login at all.
This is the quarterβs clearest signal - and the report details exactly which exposures to close first, and how, before the exploitation curve catches up.
Nation-state activity remains persistent
Rapid7 observed continued activity from Iranian, North Korean, and Russian advanced persistent threat (APT) clusters targeting government, finance, healthcare, manufacturing, energy, and telecommunications. Russian campaigns targeted edge infrastructure; Iranian activity included sustained industrial control system (ICS) and operational technology (OT) targeting.
The report maps the specific techniques and sectors each cluster focused on this quarter.
Ransomware stays concentrated but keeps evolving
Qilin led ransomware activity in Q2 with 263 listed victims, and the United States remained the most heavily targeted country - with business services and healthcare among the hardest-hit sectors. Rapid7βs Incident Response team also saw growing use of ClickFix and fake CAPTCHA campaigns, and social engineering through trusted collaboration platforms like Microsoft Teams - techniques that accounted for 31.8% of the incidents we worked.
The report includes the full ransomware leaderboard, the sectors most at risk, and where affiliate activity is expanding next.
Exposure is the real challenge, and the biggest opportunity
The volume is daunting, but the real challenge is keeping pace with attackers. As disclosures keep growing, the organizations that stay ahead wonβt be the ones patching fastest β theyβll be the ones that know what they expose, which assets matter most, where attackers can realistically get in, and how to reduce reachable exposure before it becomes an incident. Thatβs what preemptive security means: not a slogan, but an operating model.
The full Quarterly Threat Landscape Report shows where reachable exposure concentrates this quarter, the four actions Rapid7 Labs recommends, the sector-by-sector breakdown, and the dark-web signals shaping whatβs next. Read it here before you pressure-test your Q3 prioritization.