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July 10, 2025

Crypto Wallets Continue to be Drained in Elaborate Social Media Scam

Darktrace’s latest research reveals that an evolving social engineering campaign continues to target cryptocurrency users through fake startup companies. These malicious operations impersonate AI, gaming, and Web3 firms using spoofed social media accounts and project documentation hosted on legitimate platforms like Notion and GitHub.
Inside the SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Written by
Tara Gould
Threat Researcher
password on computer screenDefault blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog image
10
Jul 2025

Overview

Continued research by Darktrace has revealed that cryptocurrency users are being targeted by threat actors in an elaborate social engineering scheme that continues to evolve. In December 2024, Cado Security Labs detailed a campaign targeting Web 3 employees in the Meeten campaign. The campaign included threat actors setting up meeting software companies to trick users into joining meetings and installing the information stealer Realst disguised as video meeting software.

The latest research from Darktrace shows that this campaign is still ongoing and continues to trick targets to download software to drain crypto wallets. The campaign features:

  • Threat actors creating fake startup companies with AI, gaming, video meeting software, web3 and social media themes.
  • Use of compromised X (formerly Twitter) accounts for the companies and employees - typically with verification to contact victims and create a facade of a legitimate company.
  • Notion, Medium, Github used to provide whitepapers, project roadmaps and employee details.
  • Windows and macOS versions.
  • Stolen software signing certificates in Windows versions for credibility and defense evasion.
  • Anti-analysis techniques including obfuscation, and anti-sandboxing.

To trick as many victims as possible, threat actors try to make the companies look as legitimate as possible. To achieve this, they make use of sites that are used frequently with software companies such as Twitter, Medium, Github and Notion. Each company has a professional looking website that includes employees, product blogs, whitepapers and roadmaps. X is heavily used to contact victims, and to increase the appearance of legitimacy. Some of the observed X accounts appear to be compromised accounts that typically are verified and have a higher number of followers and following, adding to the appearance of a real company.

Example of a compromised X account to create a “BuzzuAI” employee.
Figure 1: Example of a compromised X account to create a “BuzzuAI” employee.

The threat actors are active on these accounts while the campaign is active, posting about developments in the software, and product marketing. One of the fake companies part of this campaign, “Eternal Decay”, a blockchain-powered game, has created fake pictures pretending to be presenting at conferences to post on social media, while the actual game doesn’t exist.

From the Eternal Decay X account, threat actors have altered a photo from an Italian exhibition (original on the right) to make it look like Eternal Decay was presented.
Figure 2: From the Eternal Decay X account, threat actors have altered a photo from an Italian exhibition (original on the right) to make it look like Eternal Decay was presented.

In addition to X, Medium is used to post blogs about the software. Notion has been used in various campaigns with product roadmap details, as well as employee lists.

Notion project team page for Swox.
Figure 3: Notion project team page for Swox.

Github has been used to detail technical aspects of the software, along with Git repositories containing stolen open-source projects with the name changed in order to make the code look unique. In the Eternal Decay example, Gitbook is used to detail company and software information. The threat actors even include company registration information from Companies House, however they have linked to a company with a similar name and are not a real registered company.

 From the Eternal Decay Gitbook linking to a company with a similar name on Companies House.
Figure 4: From the Eternal Decay Gitbook linking to a company with a similar name on Companies House.
Gitbook for “Eternal Decay” listing investors.
Figure 5: Gitbook for “Eternal Decay” listing investors.
Gameplay images are stolen from a different game “Zombie Within” and posted pretending to be Eternal Decay gameplay.
Figure 6: Gameplay images are stolen from a different game “Zombie Within” and posted pretending to be Eternal Decay gameplay.

In some of the fake companies, fake merchandise stores have even been set up. With all these elements combined, the threat actors manage to create the appearance of a legitimate start-up company, increasing their chances of infection.

Each campaign typically starts with a victim being contacted through X messages, Telegram or Discord. A fake employee of the company will contact a victim asking to test out their software in exchange for a cryptocurrency payment. The victim will be directed to the company website download page, where they need to enter a registration code, provided by the employee to download a binary. Depending on their operating system, the victim will be instructed to download a macOS DMG (if available) or a Windows Electron application.

Example of threat actor messaging a victim on X with a registration code.
Figure 7: Example of threat actor messaging a victim on X with a registration code.

Windows Version

Similar to the aforementioned Meeten campaign, the Windows version being distributed by the fake software companies is an Electron application. Electron is an open-source framework used to run Javascript apps as a desktop application. Once the user follows directions sent to them via message, opening the application will bring up a Cloudflare verification screen.

Cloudflare verification screen.
Figure 8: Cloudflare verification screen.

The malware begins by profiling the system, gathering information like the username, CPU and core count, RAM, operating system, MAC address, graphics card, and UUID.

Code from the Electron app showing console output of system profiling.
Figure 9: Code from the Electron app showing console output of system profiling.

A verification process occurs with a captcha token extracted from the app-launcher URL and sent along with the system info and UUID. If the verification is successful, an executable or MSI file is downloaded and executed quietly. Python is also retrieved and stored in /AppData/Temp, with Python commands being sent from the command-and-control (C2) infrastructure.

Code from the Electron app looping through Python objects.
Figure 10: Code from the Electron app looping through Python objects.

As there was no valid token, this process did not succeed. However, based on previous campaigns and reports from victims on social media, an information stealer targeting crypto wallets is executed at this stage. A common tactic in the observed campaigns is the use of stolen code signing certificates to evade detection and increase the appearance of legitimate software. The certificates of two legitimate companies Jiangyin Fengyuan Electronics Co., Ltd. and Paperbucketmdb ApS (revoked as of June 2025) were used during this campaign.

MacOS Version

For companies that have a macOS version of the malware, the user is directed to download a DMG. The DMG contains a bash script and a multiarch macOS binary. The bash script is obfuscated with junk, base64 and is XOR’d.

Obfuscated Bash script.
Figure 11: Obfuscated Bash script.

After decoding, the contents of the script are revealed showing that AppleScript is being used. The script looks for disk drives, specifically for the mounted DMG “SwoxApp” and moves the hidden .SwoxApp binary to /tmp/ and makes it executable. This type of AppleScript is commonly used in macOS malware, such as Atomic Stealer.

AppleScript used to mount the malware and make it executable.
Figure 12: AppleScript used to mount the malware and make it executable.

The SwoxApp binary is the prominent macOS information stealer Atomic Stealer. Once executed the malware performs anti-analysis checks for QEMU, VMWare and Docker-OSX, the script exits if these return true.  The main functionality of Atomic Stealer is to steal data from stores including browser data, crypto wallets, cookies and documents. This data is compressed into /tmp/out.zip and sent via POST request to 45[.]94[.]47[.]167/contact. An additional bash script is retrieved from 77[.]73[.]129[.]18:80/install.sh.

Additional Bash script ”install.sh”.
Figure 13: Additional Bash script ”install.sh”.

Install.sh, as shown in Figure 13, retrieves another script install_dynamic.sh from the server https://mrajhhosdoahjsd[.]com. Install_dynamic.sh downloads and extracts InstallerHelper.app, then sets up persistence via Launch Agent to run at login.

Persistence added via Plist configuration.
Figure 14: Persistence added via Plist configuration.

This plist configuration installs a macOS LaunchAgent that silently runs the app at user login. RunAtLoad and KeepAlive keys are used to ensure the app starts automatically and remains persistent.

The retrieved binary InstallerHelper is an Objective-C/Swift binary that logs active application usage, window information, and user interaction timestamps. This data is written to local log files and periodically transmits the contents to https://mrajhhoshoahjsd[.]com/collect-metrics using scheduled network requests.

List of known companies

Darktrace has identified a number of the fake companies used in this scam. These can be found in the list below:

Pollens AI
X: @pollensapp, @Pollens_app
Website: pollens.app, pollens.io, pollens.tech
Windows: 02a5b35be82c59c55322d2800b0b8ccc
Notes: Posing as an AI software company with a focus on “collaborative creation”.

Buzzu
X: @BuzzuApp, @AI_Buzzu, @AppBuzzu, @BuzzuApp
Website: Buzzu.app, Buzzu.us, buzzu.me, Buzzu.space
Windows: 7d70a7e5661f9593568c64938e06a11a
Mac: be0e3e1e9a3fda76a77e8c5743dd2ced
Notes: Same as Pollens including logo but with a different name.

Cloudsign
X: @cloudsignapp
Windows: 3a3b13de4406d1ac13861018d74bf4b2
Notes: Claims to be a document signing platform.

Swox
X: @SwoxApp, @Swox_AI, @swox_app, @App_Swox, @AppSwox, @SwoxProject, @ProjectSwox
Website: swox.io, swox.app, swox.cc, swoxAI.com, swox.us
Windows: d50393ba7d63e92d23ec7d15716c7be6
Mac: 81996a20cfa56077a3bb69487cc58405ced79629d0c09c94fb21ba7e5f1a24c9
Notes: Claims to be a “Next gen social network in the WEB3”. Same GitHub code as Pollens.

KlastAI
X: Links to Pollens X account
Website: Links to pollens.tech
Notes: Same as Pollens, still shows their branding on its GitHub readme page.

Wasper
X: @wasperAI, @WasperSpace
Website: wasper.pro, wasper.app, wasper.org, wasper.space
Notes: Same logo and GitHub code as Pollens.

Lunelior
Website: lunelior.net, Lunelior.app, lunelior.io, lunelior.us
Windows: 74654e6e5f57a028ee70f015ef3a44a4
Mac: d723162f9197f7a548ca94802df74101

BeeSync
X: @BeeSyncAI, @AIBeeSync
Website: beesync.ai, beesync.cc
Notes: Previous alias of Buzzu, Git repo renamed January 2025.

Slax
X: @SlaxApp, @Slax_app, @slaxproject
Website: slax.tech, slax.cc, slax.social, slaxai.app

Solune
X: @soluneapp
Website: solune.io, solune.me
Windows: 22b2ea96be9d65006148ecbb6979eccc

Eternal Decay
X: @metaversedecay
Website: eternal-decay.xyz
Windows: 558889183097d9a991cb2c71b7da3c51
Mac: a4786af0c4ffc84ff193ff2ecbb564b8

Dexis
X: @DexisApp
Website: dexis.app
Notes: Same branding as Swox.

NexVoo
X: @Nexvoospace
Website: nexvoo.app, Nexvoo.net, Nexvoo.us

NexLoop
X: @nexloopspace
Website: nexloop.me

NexoraCore
Notes: Rename of the Nexloop Git repo.

YondaAI
X: @yondaspace
Website: yonda.us

Traffer Groups

A “traffer” malware group is an organized cybercriminal operation that specializes in directing internet users to malicious content typically information-stealing malware through compromised or deceptive websites, ads, and links. They tend to operate in teams with hierarchical structures with administrators recruiting “traffers” (or affiliates) to generate traffic and malware installs via search engine optimization (SEO), YouTube ads, fake software downloads, or owned sites, then monetize the stolen credentials and data via dedicated marketplaces.

A prominent traffer group “CrazyEvil” was identified by Recorded Future in early 2025. The group, who have been active since at least 2021, specialize in social engineering attacks targeted towards cryptocurrency users, influencers, DeFi professionals, and gaming communities. As reported by Recorded Future, CrazyEvil are estimated to have made millions of dollars in revenue from their malicious activity. CrazyEvil and their sub teams create fake software companies, similar to the ones described in this blog, making use of Twitter and Medium to target victims. As seen in this campaign, CrazyEvil instructs users to download their software which is an info stealer targeting both macOS and Windows users.

While it is unclear if the campaigns described in this blog can be attributed to CrazyEvil or any sub teams, the techniques described are similar in nature. This campaign highlights the efforts that threat actors will go to make these fake companies look legitimate in order to steal cryptocurrency from victims, in addition to use of newer evasive versions of malware.

Indicators of Compromise (IoCs)

Manboon[.]com

https://gaetanorealty[.]com

Troveur[.]com

Bigpinellas[.]com

Dsandbox[.]com

Conceptwo[.]com

Aceartist[.]com

turismoelcasco[.]com

Ekodirect[.]com

https://mrajhhosdoahjsd[.]com

https://isnimitz.com/zxc/app[.]zip

http://45[.]94[.]47[.]112/contact

45[.]94[.]47[.]167/contact

77[.]73[.]129[.]18:80

Domain Keys associated with the C2s

YARA Rules

rule Suspicious_Electron_App_Installer

{

  meta:

      description = "Detects Electron apps collecting HWID, MAC, GPU info and executing remote EXEs/MSIs"

      date = "2025-06-18"

  strings:

      $electron_require = /require\(['"]electron['"]\)/

      $axios_require = /require\(['"]axios['"]\)/

      $exec_use = /exec\(.*?\)/

      $url_token = /app-launcher:\/\/.*token=/

      $getHWID = /(Get-CimInstance Win32_ComputerSystemProduct).UUID/

      $getMAC = /details\.mac && details\.mac !== '00:00:00:00:00:00'/

      $getGPU = /wmic path win32_VideoController get name/

      $getInstallDate = /InstallDate/

      $os_info = /os\.cpus\(\)\[0\]\.model/

      $downloadExe = /\.exe['"]/

      $runExe = /msiexec \/i.*\/quiet \/norestart/

      $zipExtraction = /AdmZip\(.*\.extractAllTo/

  condition:

      (all of ($electron_require, $axios_require, $exec_use) and

       3 of ($getHWID, $getMAC, $getGPU, $getInstallDate, $os_info) and

       2 of ($downloadExe, $runExe, $zipExtraction, $url_token))

}

Inside the SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Written by
Tara Gould
Threat Researcher

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October 23, 2025

Patch Smarter, Not Harder: Now Empowering Security Teams with Business-Aligned Threat Context Agents

Patch Smarter, Not Harder: Now Empowering Security Teams with Business-Aligned Threat Context Agents Default blog imageDefault blog image

Most risk management programs remain anchored in enumeration: scanning every asset, cataloging every CVE, and drowning in lists that rarely translate into action. Despite expensive scanners, annual pen tests, and countless spreadsheets, prioritization still falters at two critical points.

Context gaps at the device level: It’s hard to know which vulnerabilities actually matter to your business given existing privileges, what software it runs, and what controls already reduce risk.

Business translation: Even when the technical priority is clear, justifying effort and spend in financial terms—especially across many affected devices—can delay action. Especially if it means halting other areas of the business that directly generate revenue.

The result is familiar: alert fatigue, “too many highs,” and remediation that trails behind the threat landscape. Darktrace / Proactive Exposure Management addresses this by pairing precise, endpoint‑level context with clear, financial insight so teams can prioritize confidently and mobilize faster.

A powerful combination: No-Telemetry Endpoint Agent + Cost-Benefit Analysis

Darktrace / Proactive Exposure Management now uniquely combines technical precision with business clarity in a single workflow.  With this release, Darktrace / Proactive Exposure Management delivers a more holistic approach, uniting technical context and financial insight to drive proactive risk reduction. The result is a single solution that helps security teams stay ahead of threats while reducing noise, delays, and complexity.

  • No-Telemetry Endpoint: Collects installed software data and maps it to known CVEs—without network traffic—providing device-level vulnerability context and operational relevance.
  • Cost-Benefit Analysis for Patching: Calculates ROI by comparing patching effort with potential exploit impact, factoring in headcount time, device count, patch difficulty, and automation availability.

Introducing the No-Telemetry Endpoint Agent

Darktrace’s new endpoint agent inventories installed software on devices and maps it to known CVEs without collecting network data so you can prioritize using real device context and available security controls.

By grounding vulnerability findings in the reality of each endpoint, including its software footprint and existing controls, teams can cut through generic severity scores and focus on what matters most. The agent is ideal for remote devices, BYOD-adjacent fleets, or environments standardizing on Darktrace, and is available without additional licensing cost.

Darktrace / Proactive Exposure Management user interface
Figure 1: Darktrace / Proactive Exposure Management user interface

Built-In Cost-Benefit Analysis for Patching

Security teams often know what needs fixing but stakeholders need to understand why now. Darktrace’s new cost-benefit calculator compares the total cost to patch against the potential cost of exploit, producing an ROI for the patch action that expresses security action in clear financial terms.

Inputs like engineer time, number of affected devices, patch difficulty, and automation availability are factored in automatically. The result is a business-aligned justification for every patching decision—helping teams secure buy-in, accelerate approvals, and move work forward with one-click ticketing, CSV export, or risk acceptance.

Darktrace / Proactive Exposure Management Cost Benefit Analysis
Figure 2: Darktrace / Proactive Exposure Management Cost Benefit Analysis

A Smarter, Faster Approach to Exposure Management

Together, the no-telemetry endpoint and Cost–Benefit Analysis advance the CTEM motion from theory to practice. You gain higher‑fidelity discovery and validation signals at the device level, paired with business‑ready justification that accelerates mobilization. The result is fewer distractions, clearer priorities, and faster measurable risk reduction. This is not from chasing every alert, but by focusing on what moves the needle now.

  • Smarter Prioritization: Device‑level context trims noise and spotlights the exposures that matter for your business.
  • Faster Decisions: Built‑in ROI turns technical urgency into executive clarity—speeding approvals and action.
  • Practical Execution: Privacy‑conscious endpoint collection and ticketing/export options fit neatly into existing workflows.
  • Better Outcomes: Close the loop faster—discover, prioritize, validate, and mobilize—on the same operating surface.

Committed to innovation

These updates are part of the broader Darktrace release, which also included:

1. Major innovations in cloud security with the launch of the industry’s first fully automated cloud forensics solution, reinforcing Darktrace’s leadership in AI-native security.

2. Darktrace Network Endpoint eXtended Telemetry (NEXT) is revolutionizing NDR with the industry’s first mixed-telemetry agent using Self-Learning AI.

3. Improvements to our OT product, purpose built for industrial infrastructure, Darktrace / OT now brings dedicated OT dashboard, segmentation-aware risk modeling, and expanded visibility into edge assets and automation protocols.

Join our Live Launch Event

When? 

December 9, 2025

What will be covered?

Join our live broadcast to experience how Darktrace is eliminating blind spots for detection and response across your complete enterprise with new innovations in Agentic AI across our ActiveAI Security platform. Industry leaders from IDC will join Darktrace customers to discuss challenges in cross-domain security, with a live walkthrough reshaping the future of Network Detection & Response, Endpoint Detection & Response, Email Security, and SecOps in novel threat detection and autonomous investigations.

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About the author
Kelland Goodin
Product Marketing Specialist

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October 23, 2025

Darktrace Announces Extended Visibility Between Confirmed Assets and Leaked Credentials from the Deep and Dark Web

Darktrace Announces Extended Visibility Between Confirmed Assets and Leaked Credentials from the Deep and Dark Web Default blog imageDefault blog image

Why exposure management needs to evolve beyond scans and checklists

The modern attack surface changes faster than most security programs can keep up. New assets appear, environments change, and adversaries are increasingly aided by automation and AI. Traditional approaches like periodic scans, static inventories, or annual pen tests are no longer enough. Without a formal exposure program, many businesses are flying blind, unaware of where the next threat may emerge.

This is where Continuous Threat Exposure Management (CTEM) becomes essential. Introduced by Gartner, CTEM helps organizations continuously assess, validate, and improve their exposure to real-world threats. It reframes the problem: scope your true attack surface, prioritize based on business impact and exploitability, and validate what attackers can actually do today, not once a year.

With two powerful new capabilities, Darktrace / Attack Surface Management helps organizations evolve their CTEM programs to meet the demands of today’s threat landscape. These updates make CTEM a reality, not just a strategy.

Too much data, not enough direction

Modern Attack Surface Management tools excel at discovering assets such as cloud workloads, exposed APIs, and forgotten domains. But they often fall short when it comes to prioritization. They rely on static severity scores or generic CVSS ratings, which do not reflect real-world risk or business impact.

This leaves security teams with:

  • Alert fatigue from hundreds of “critical” findings
  • Patch paralysis due to unclear prioritization
  • Blind spots around attacker intent and external targeting

CISOs need more than visibility. They need confidence in what to fix first and context to justify those decisions to stakeholders.

Evolving Attack Surface Management

Attack Surface Management (ASM) must evolve from static lists and generic severity scores to actionable intelligence that helps teams make the right decision now.

Joining the recent addition of Exploit Prediction Assessment, which debuted in late June 2025, today we’re introducing two capabilities that push ASM into that next era:

  • Exploit Prediction Assessment: Continuously validates whether top-priority exposures are actually exploitable in your environment without waiting for patch cycles or formal pen tests.  
  • Deep & Dark Web Monitoring: Extends visibility across millions of sources in the deep and dark web to detect leaked credentials linked to your confirmed domains.
  • Confidence Score: our newly developed AI classification platform will compare newly discovered assets to assets that are known to belong to your organization. The more these newly discovered assets look similar to assets that belong to your organization, the higher the score will be.

Together, these features compress the window from discovery to decision, so your team can act with precision, not panic. The result is a single solution that helps teams stay ahead of attackers without introducing new complexities.

Exploit Prediction Assessment

Traditional penetration tests are invaluable, but they’re often a snapshot of that point-in-time, are potentially disruptive, and compliance frameworks still expect them. Not to mention, when vulnerabilities are present, teams can act immediately rather than relying solely on information from CVSS scores or waiting for patch cycles.  

Unlike full pen tests which can be obtrusive and are usually done only a couple times per year, Exploit Prediction Assessment is surgical, continuous, and focused only on top issues Instead of waiting for vendor patches or the next pen‑test window. It helps confirm whether a top‑priority exposure is actually exploitable in your environment right now.  

For more information on this visit our blog: Beyond Discovery: Adding Intelligent Vulnerability Validation to Darktrace / Attack Surface Management

Deep and Dark Web Monitoring: Extending the scope

Customers have been asking for this for years, and it is finally here. Defense against the dark web. Darktrace / Attack Surface Management’s reach now spans millions of sources across the deep and dark web including forums, marketplaces, breach repositories, paste sites, and other hard‑to‑reach communities to detect leaked credentials linked to your confirmed domains.  

Monitoring is continuous, so you’re alerted as soon as evidence of compromise appears. The surface web is only a fraction of the internet, and a sizable share of risk hides beyond it. Estimates suggest the surface web represents roughly ~10% of all online content, with the rest gated or unindexed—and the TOR-accessible dark web hosts a high proportion of illicit material (a King’s College London study found ~57% of surveyed onion sites contained illicit content), underscoring why credential leakage and brand abuse often appear in places traditional monitoring doesn’t reach. Making these spaces high‑value for early warning signals when credentials or brand assets appear. Most notably, this includes your company’s reputation, assets like servers and systems, and top executives and employees at risk.

What changes for your team

Before:

  • Hundreds of findings, unclear what to start with
  • Reactive investigations triggered by incidents

After:

  • A prioritized backlog based on confidence score or exploit prediction assessment verification
  • Proactive verification of exposure with real-world risk without manual efforts

Confidence Score: Prioritize based on the use-case you care most about

What is it?

Confidence Score is a metric that expresses similarity of newly discover assets compared to the confirmed asset inventory. Several self-learning algorithms compare features of assets to be able to calculate a score.

Why it matters

Traditional Attack Surface Management tools treat all new discovery equally, making it unclear to your team how to identify the most important newly discovered assets, potentially causing you to miss a spoofing domain or shadow IT that could impact your business.

How it helps your team

We’re dividing newly discovered assets into separate insight buckets that each cover a slightly different business case.

  • Low scoring assets: to cover phishing & spoofing domains (like domain variants) that are just being registered and don't have content yet.
  • Medium scoring assets: have more similarities to your digital estate, but have better matching to HTML, brand names, keywords. Can still be phishing but probably with content.
  • High scoring assets: These look most like the rest of your confirmed digital estate, either it's phishing that needs the highest attention, or the asset belongs to your attack surface and requires asset state confirmation to enable the platform to monitor it for risks.

Smarter Exposure Management for CTEM Programs

Recent updates to Darktrace / Attack Surface Management directly advance the core phases of Continuous Threat Exposure Management (CTEM): scope, discover, prioritize, validate, and mobilize. The new Exploit Prediction Assessment helps teams validate and prioritize vulnerabilities based on real-world exploitability, while Deep & Dark Web Monitoring extends discovery into hard-to-reach areas where stolen data and credentials often surface. Together, these capabilities reduce noise, accelerate remediation, and help organizations maintain continuous visibility over their expanding attack surface.

Building on these innovations, Darktrace / Attack Surface Management empowers security teams to focus on what truly matters. By validating exploitability, it cuts through the noise of endless vulnerability lists—helping defenders concentrate on exposures that represent genuine business risk. Continuous monitoring for leaked credentials across the deep and dark web further extends visibility beyond traditional asset discovery, closing critical blind spots where attackers often operate. Crucially, these capabilities complement, not replace, existing security controls such as annual penetration tests, providing continuous, low-friction validation between formal assessments. The result is a more adaptive, resilient security posture that keeps pace with an ever-evolving threat landscape.

If you’re building or maturing a CTEM program—and want fewer open exposures, faster remediation, and better outcomes, Darktrace / Attack Surface Management’s new Exploit Prediction Assessment and Deep & Dark Web Monitoring are ready to help.

  • Want a more in-depth look at how Exploit Prediction Assessment functions? Read more here

Committed to innovation

These updates are part of the broader Darktrace release, which also included:

1. Major innovations in cloud security with the launch of the industry’s first fully automated cloud forensics solution, reinforcing Darktrace’s leadership in AI-native security.

2. Darktrace Network Endpoint eXtended Telemetry (NEXT) is revolutionizing NDR with the industry’s first mixed-telemetry agent using Self-Learning AI.

3. Improvements to our OT product, purpose built for industrial infrastructure, Darktrace / OT now brings dedicated OT dashboard, segmentation-aware risk modeling, and expanded visibility into edge assets and automation protocols.

Join our Live Launch Event

When? 

December 9, 2025

What will be covered?

Join our live broadcast to experience how Darktrace is eliminating blind spots for detection and response across your complete enterprise with new innovations in Agentic AI across our ActiveAI Security platform. Industry leaders from IDC will join Darktrace customers to discuss challenges in cross-domain security, with a live walkthrough reshaping the future of Network Detection & Response, Endpoint Detection & Response, Email Security, and SecOps in novel threat detection and autonomous investigations.

Continue reading
About the author
Kelland Goodin
Product Marketing Specialist
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