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May 1, 2025

SocGholish: From loader and C2 activity to RansomHub deployment

In early 2025, Darktrace uncovered SocGholish-to-RansomHub intrusion chains, including loader and C2 activity, alongside credential harvesting via WebDAV and SCF abuse. Learn more about SocGholish and its kill chain here!
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
Christina Kreza
Cyber Analyst
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01
May 2025

Over the past year, a clear pattern has emerged across the threat landscape: ransomware operations are increasingly relying on compartmentalized affiliate models. In these models, initial access brokers (IABs) [6], malware loaders, and post-exploitation operators work together.

Due to those specialization roles, a new generation of loader campaigns has risen. Threat actors increasingly employ loader operators to quietly establish footholds on the target network. These entities then hand off access to ransomware affiliates. One loader that continues to feature prominently in such campaigns is SocGholish.

What is SocGholish?

SocGholish is a loader malware that has been utilized since at least 2017 [7].  It has long been associated with fake browser updates and JavaScript-based delivery methods on infected websites.

Threat actors often target outdated or poorly secured CMS-based websites like WordPress. Through unpatched plugins, or even remote code execution flaws, they inject malicious JavaScript into the site’s HTML, templates or external JS resources [8].  Historically, SocGholish has functioned as a first-stage malware loader, ultimately leading to deployment of Cobalt Strike beacons [9], and further facilitating access persistence to corporate environments. More recently, multiple security vendors have reported that infections involving SocGholish frequently lead to the deployment of RansomHub ransomware [3] [5].

This blog explores multiple instances within Darktrace's customer base where SocGholish deployment led to subsequent network compromises. Investigations revealed indicators of compromise (IoCs) similar to those identified by external security researchers, along with variations in attacker behavior post-deployment. Key innovations in post-compromise activities include credential access tactics targeting authentication mechanisms, particularly through the abuse of legacy protocols like WebDAV and SCF file interactions over SMB.

Initial access and execution

Since January 2025, Darktrace’s Threat Research team observed multiple cases in which threat actors leveraged the SocGholish loader for initial access. Malicious actors commonly deliver SocGholish by compromising legitimate websites by injecting malicious scripts into the HTML of the affected site. When the visitor lands on an infected site, they are typically redirected to a fake browser update page, tricking them into downloading a ZIP file containing a JavaScript-based loader [1] [2]. In one case, a targeted user appears to have visited the compromised website garagebevents[.]com (IP: 35.203.175[.]30), from which around 10 MB of data was downloaded.

Device Event Log showing connections to the compromised website, following by connections to the identified Keitaro TDS instances.
Figure 1: Device Event Log showing connections to the compromised website, following by connections to the identified Keitaro TDS instances.

Within milliseconds of the connection establishment, the user’s device initiated several HTTPS sessions over the destination port 443 to the external endpoint 176.53.147[.]97, linked to the following Keitaro TDS domains:

  • packedbrick[.]com
  • rednosehorse[.]com
  • blackshelter[.]org
  • blacksaltys[.]com

To evade detection, SocGholish uses highly obfuscated code and relies on traffic distribution systems (TDS) [3].  TDS is a tool used in digital and affiliate marketing to manage and distribute incoming web traffic based on predefined rules. More specifically, Keitaro is a premium self-hosted TDS frequently utilized by attackers as a payload repository for malicious scripts following redirects from compromised sites. In the previously noted example, it appears that the device connected to the compromised website, which then retrieved JavaScript code from the aforementioned Keitaro TDS domains. The script served by those instances led to connections to the endpoint virtual.urban-orthodontics[.]com (IP: 185.76.79[.]50), successfully completing SocGholish’s distribution.

Advanced Search showing connections to the compromised website, following by those to the identified Keitaro TDS instances.
Figure 2: Advanced Search showing connections to the compromised website, following by those to the identified Keitaro TDS instances.

Persistence

During some investigations, Darktrace researchers observed compromised devices initiating HTTPS connections to the endpoint files.pythonhosted[.]org (IP: 151.101.1[.]223), suggesting Python package downloads. External researchers have previously noted how attackers use Python-based backdoors to maintain access on compromised endpoints following initial access via SocGholish [5].

Credential access and lateral movement

Credential access – external

Darktrace researchers identified observed some variation in kill chain activities following initial access and foothold establishment. For example, Darktrace detected interesting variations in credential access techniques. In one such case, an affected device attempted to contact the rare external endpoint 161.35.56[.]33 using the Web Distributed Authoring and Versioning (WebDAV) protocol. WebDAV is an extension of the HTTP protocol that allows users to collaboratively edit and manage files on remote web servers. WebDAV enables remote shares to be mounted over HTTP or HTTPS, similar to how SMB operates, but using web-based protocols. Windows supports WebDAV natively, which means a UNC path pointing to an HTTP or HTTPS resource can trigger system-level behavior such as authentication.

In this specific case, the system initiated outbound connections using the ‘Microsoft-WebDAV-MiniRedir/10.0.19045’ user-agent, targeting the URI path of /s on the external endpoint 161.35.56[.]33. During these requests, the host attempted to initiate NTML authentication and even SMB sessions over the web, both of which failed. Despite the session failures, these attempts also indicate a form of forced authentication. Forced authentication exploits a default behavior in Windows where, upon encountering a UNC path, the system will automatically try to authenticate to the resource using NTML – often without any user interaction. Although no files were directly retrieved, the WebDAV server was still likely able to retrieve the user’s NTLM hash during the session establishment requests, which can later be used by the adversary to crack the password offline.

Credential access – internal

In another investigated incident, Darktrace observed a related technique utilized for credential access and lateral movement. This time, the infected host uploaded a file named ‘Thumbs.scf’ to multiple internal SMB network shares. Shell Command File ( SCF) is a legacy Windows file format used primarily for Windows Explorer shortcuts. These files contain instructions for rendering icons or triggering shell commands, and they can be executed implicitly when a user simply opens a folder containing the file – no clicks required.

The ‘Thumbs.scf’ file dropped by the attacker was crafted to exploit this behavior. Its contents included a [Shell] section with the Command=2 directive and an IconFile path pointing to a remote UNC resource on the same external endpoint, 161.35.56[.]33, seen in the previously described case – specifically, ‘\\161.35.56[.]33\share\icon.ico’. When a user on the internal network navigates to the folder containing the SCF file, their system will automatically attempt to load the icon. In doing so, the system issues a request to the specified UNC path, which again prompts Windows to initiate NTML authentication.

This pattern of activity implies that the attacker leveraged passive internal exposure; users who simply browsed a compromised share would unknowingly send their NTML hashes to an external attacker-controlled host. Unlike the WebDAV approach, which required initiating outbound communication from the infected host, this SCF method relies on internal users to interact with poisoned folders.

Figure 3: Contents of the file 'Thumbs.scf' showing the UNC resource hosted on the external endpoint.
Figure 3: Contents of the file 'Thumbs.scf' showing the UNC resource hosted on the external endpoint.

Command-and-control

Following initial compromise, affected devices would then attempt outbound connections using the TLS/SSL protocol over port 443 to different sets of command-and-control (C2) infrastructure associated with SocGholish. The malware frequently uses obfuscated JavaScript loaders to initiate its infection chain, and once dropped, the malware communicates back to its infrastructure over standard web protocols, typically using HTTPS over port 443. However, this set of connections would precede a second set of outbound connections, this time to infrastructure linked to RansomHub affiliates, possibly facilitating the deployed Python-based backdoor.

Connectivity to RansomHub infrastructure relied on defense evasion tactics, such as port-hopping. The idea behind port-hopping is to disguise C2 traffic by avoiding consistent patterns that might be caught by firewalls, and intrusion detection systems. By cycling through ephemeral ports, the malware increases its chances of slipping past basic egress filtering or network monitoring rules that only scrutinize common web traffic ports like 443 or 80. Darktrace analysts identified systems connecting to destination ports such as 2308, 2311, 2313 and more – all on the same destination IP address associated with the RansomHub C2 environment.

Figure 4: Advanced Search connection logs showing connections over destination ports that change rapidly.

Conclusion

Since the beginning of 2025, Darktrace analysts identified a campaign whereby ransomware affiliates leveraged SocGholish to establish network access in victim environments. This activity enabled multiple sets of different post exploitation activity. Credential access played a key role, with affiliates abusing WebDAV and NTML over SMB to trigger authentication attempts. The attackers were also able to plant SCF files internally to expose NTML hashes from users browsing shared folders. These techniques evidently point to deliberate efforts at early lateral movement and foothold expansion before deploying ransomware. As ransomware groups continue to refine their playbooks and work more closely with sophisticated loaders, it becomes critical to track not just who is involved, but how access is being established, expanded, and weaponized.

Credit to Chrisina Kreza (Cyber Analyst) and Adam Potter (Senior Cyber Analyst)

[related-resource]

Appendices

Darktrace / NETWORK model alerts

·       Anomalous Connection / SMB Enumeration

·       Anomalous Connection / Multiple Connections to New External TCP Port

·       Anomalous Connection / Multiple Failed Connections to Rare Endpoint

·       Anomalous Connection / New User Agent to IP Without Hostname

·       Compliance / External Windows Communication

·       Compliance / SMB Drive Write

·       Compromise / Large DNS Volume for Suspicious Domain

·       Compromise / Large Number of Suspicious Failed Connections

·       Device / Anonymous NTML Logins

·       Device / External Network Scan

·       Device / New or Uncommon SMB Named Pipe

·       Device / SMB Lateral Movement

·       Device / Suspicious SMB Activity

·       Unusual Activity / Unusual External Activity

·       User / Kerberos Username Brute Force

MITRE ATT&CK mapping

·       Credential Access – T1187 Forced Authentication

·       Credential Access – T1110 Brute Force

·       Command and Control – T1071.001 Web Protocols

·       Command and Control – T1571 Non-Standard Port

·       Discovery – T1083 File and Directory Discovery

·       Discovery – T1018 Remote System Discovery

·       Discovery – T1046 Network Service Discovery

·       Discovery – T1135 Network Share Discovery

·       Execution – T1059.007 JavaScript

·       Lateral Movement – T1021.002 SMB/Windows Admin Shares

·       Resource Deployment – T1608.004 Drive-By Target

List of indicators of compromise (IoCs)

·       garagebevents[.]com – 35.203.175[.]30 – Possibly compromised website

·       packedbrick[.]com – 176.53.147[.]97 – Keitaro TDS Domains used for SocGholish Delivery

·       rednosehorse[.]com – 176.53.147[.]97 – Keitaro TDS Domains used for SocGholish Delivery

·       blackshelter[.]org – 176.53.147[.]97 – Keitaro TDS Domains used for SocGholish Delivery

·       blacksaltys[.]com – 176.53.147[.]97 – Keitaro TDS Domains used for SocGholish Delivery

·       virtual.urban-orthodontics[.]com – 185.76.79[.]50

·       msbdz.crm.bestintownpro[.]com – 166.88.182[.]126 – SocGholish C2

·       185.174.101[.]240 – RansomHub Python C2

·       185.174.101[.]69 – RansomHub Python C2

·       108.181.182[.]143 – RansomHub Python C2

References

[1] https://www.checkpoint.com/cyber-hub/threat-prevention/what-is-malware/socgholish-malware/

[2] https://intel471.com/blog/threat-hunting-case-study-socgholish

[3] https://www.trendmicro.com/en_us/research/25/c/socgholishs-intrusion-techniques-facilitate-distribution-of-rans.html

[4] https://www.proofpoint.com/us/blog/threat-insight/update-fake-updates-two-new-actors-and-new-mac-malware

[5] https://www.guidepointsecurity.com/blog/ransomhub-affiliate-leverage-python-based-backdoor/

[6] https://www.cybereason.com/blog/how-do-initial-access-brokers-enable-ransomware-attacks

[7] https://attack.mitre.org/software/S1124/

[8] https://expel.com/blog/incident-report-spotting-socgholish-wordpress-injection/

[9] https://www.esentire.com/blog/socgholish-to-cobalt-strike-in-10-minutes

Get the latest insights on emerging cyber threats

This report explores the latest trends shaping the cybersecurity landscape and what defenders need to know in 2025

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
Christina Kreza
Cyber Analyst

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July 24, 2025

Untangling the web: Darktrace’s investigation of Scattered Spider’s evolving tactics

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What is Scattered Spider?

Scattered Spider is a native English-speaking group, also referred to, or closely associated with, aliases such as UNC3944, Octo Tempest and Storm-0875. They are primarily financially motivated with a clear emphasis on leveraging social engineering, SIM swapping attacks, exploiting legitimate tooling as well as using Living-Off-the-Land (LOTL) techniques [1][2].

In recent years, Scattered Spider has been observed employing a shift in tactics, leveraging Ransomware-as-a-Service (RaaS) platforms in their attacks. This adoption reflects a shift toward more scalable attacks with a lower barrier to entry, allowing the group to carry out sophisticated ransomware attacks without the need to develop it themselves.

While RaaS offerings have been available for purchase on the Dark Web for several years, they have continued to grow in popularity, providing threat actors a way to cause significant impact to critical infrastructure and organizations without requiring highly technical capabilities [12].

This blog focuses on the group’s recent changes in tactics, techniques, and procedures (TTPs) reported by open-source intelligence (OSINT) and how TTPs in a recent Scattered Spider attack observed by Darktrace compare.

How has Scattered Spider been reported to operate?

First observed in 2022, Scattered Spider is known to target various industries globally including telecommunications, technology, financial services, and commercial facilities.

Overview of key TTPs

Scattered Spider has been known to utilize the following methods which cover multiple stages of the Cyber Kill Chain including initial access, lateral movement, evasion, persistence, and action on objective:

Social engineering [1]:

Impersonating staff via phone calls, SMS and Telegram messages; obtaining employee credentials (MITRE techniques T1598,T1656), multi-factor authentication (MFA) codes such as one-time passwords, or convincing employees to run commercial remote access tools enabling initial access (MITRE techniques T1204,T1219,T1566)

  • Phishing using specially crafted domains containing the victim name e.g. victimname-sso[.]com
  • MFA fatigue: sending repeated requests for MFA approval with the intention that the victim will eventually accept (MITRE technique T1621)

SIM swapping [1][3]:

  • Includes hijacking phone numbers to intercept 2FA codes
  • This involves the actor migrating the victim's mobile number to a new SIM card without legitimate authorization

Reconnaissance, lateral movement & command-and-control (C2) communication via use of legitimate tools:

  • Examples include Mimikatz, Ngrok, TeamViewer, and Pulseway [1]. A more recently reported example is Teleport [3].

Financial theft through their access to victim networks: Extortion via ransomware, data theft (MITRE technique T1657) [1]

Bring Your Own Vulnerable Driver (BYOVD) techniques [4]:

  • Exploiting vulnerable drivers to evade detection from Endpoint Detection and Response (EDR) security products (MITRE technique T1068) frequently used against Windows devices.

LOTL techniques

LOTL techniques are also closely associated with Scattered Spider actors once they have gained initial access; historically this has allowed them to evade detection until impact starts to be felt. It also means that specific TTPs may vary from case-to-case, making it harder for security teams to prepare and harden defences against the group.

Prominent Scattered Spider attacks over the years

While attribution is sometimes unconfirmed, Scattered Spider have been linked with a number of highly publicized attacks since 2022.

Smishing attacks on Twilio: In August 2022 the group conducted multiple social engineering-based attacks. One example was an SMS phishing (smishing) attack against the cloud communication platform Twilio, which led to the compromise of employee accounts, allowing actors to access internal systems and ultimately target Twilio customers [5][6].

Phishing and social engineering against MailChimp: Another case involved a phishing and social engineering attack against MailChimp. After gaining access to internal systems through compromised employee accounts the group conducted further attacks specifically targeting MailChimp users within cryptocurrency and finance industries [5][7].

Social engineering against Riot Games: In January 2023, the group was linked with an attack on video game developer Riot Games where social engineering was once again used to access internal systems. This time, the attackers exfiltrated game source code before sending a ransom note [8][9].

Attack on Caesars & MGM: In September 2023, Scattered Spider was linked with attacked on Caesars Entertainment and MGM Resorts International, two of the largest casino and gambling companies in the United States. It was reported that the group gathered nearly six terabytes of stolen data from the hotels and casinos, including sensitive information of guests, and made use of the RaaS strain BlackCat [10].

Ransomware against Marks & Spencer: More recently, in April 2025, the group has also been linked to the alleged ransomware incident against the UK-based retailer Marks & Spencer (M&S) making use of the DragonForce RaaS [11].

How a recent attack observed by Darktrace compares

In May 2025, Darktrace observed a Scattered Spider attack affecting one of its customers. While initial access in this attack fell outside of Darktrace’s visibility, information from the affected customer suggests similar social engineering techniques involving abuse of the customer’s helpdesk and voice phishing (vishing) were used for reconnaissance.

Initial access

It is believed the threat actor took advantage of the customer’s third-party Software-as-a-Service (SaaS) applications, such as Salesforce during the attack.

Such applications are a prime target for data exfiltration due to the sensitive data they hold; customer, personnel, and business data can all prove useful in enabling further access into target networks.

Techniques used by Scattered Spider following initial access to a victim network tend to vary more widely and so details are sparser within OSINT. However, Darktrace is able to provide some additional insight into what techniques were used in this specific case, based on observed activity and subsequent investigation by its Threat Research team.

Lateral movement

Following initial access to the customer’s network, the threat actor was able to pivot into the customer’s Virtual Desktop Infrastructure (VDI) environment.

Darktrace observed the threat actor spinning up new virtual machines and activating cloud inventory management tools to enable discovery of targets for lateral movement.

In some cases, these virtual machines were not monitored or managed by the customer’s security tools, allowing the threat actor to make use of additional tooling such as AnyDesk which may otherwise have been blocked.

Tooling in further stages of the attack sometimes overlapped with previous OSINT reporting on Scattered Spider, with anomalous use of Ngrok and Teleport observed by Darktrace, likely representing C2 communication. Additional tooling was also seen being used on the virtual machines, such as Pastebin.

 Cyber AI Analyst’s detection of C2 beaconing to a teleport endpoint with hostname CUSTOMERNAME.teleport[.]sh, likely in an attempt to conceal the traffic.
Figure 1: Cyber AI Analyst’s detection of C2 beaconing to a teleport endpoint with hostname CUSTOMERNAME.teleport[.]sh, likely in an attempt to conceal the traffic.

Leveraging LOTL techniques

Alongside use of third-party tools that may have been unexpected on the network, various LOTL techniques were observed during the incident; this primarily involved the abuse of standard network protocols such as:

  • SAMR requests to alter Active Directory account details
  • Lateral movement over RDP and SSH
  • Data collection over LDAP and SSH

Coordinated exfiltration activity linked through AI-driven analysis

Multiple methods of exfiltration were observed following internal data collection. This included SSH transfers to IPs associated with Vultr, alongside significant uploads to an Amazon S3 bucket.

While connections to this endpoint were not deemed unusual for the network at this stage due to the volume of traffic seen, Darktrace’s Cyber AI Analyst was still able to identify the suspiciousness of this behavior and launched an investigation into the activity.

Cyber AI Analyst successfully correlated seemingly unrelated internal download and external upload activity across multiple devices into a single, broader incident for the customer’s security team to review.

Cyber AI Analyst Incident summary showing a clear outline of the observed activity, including affected devices and the anomalous behaviors detected.
Figure 2: Cyber AI Analyst Incident summary showing a clear outline of the observed activity, including affected devices and the anomalous behaviors detected.
Figure 3: Cyber AI Analyst’s detection of internal data downloads and subsequent external uploads to an Amazon S3 bucket.

Exfiltration and response

Unfortunately, as Darktrace was not configured in Autonomous Response mode at the time, the attack was able to proceed without interruption, ultimately escalating to the point of data exfiltration.

Despite this, Darktrace was still able to recommend several Autonomous Response actions, aimed at containing the attack by blocking the internal data-gathering activity and the subsequent data exfiltration connections.

These actions required manual approval by the customer’s security team and as shown in Figure 3, at least one of the recommended actions was subsequently approved.

Had Darktrace been enabled in Autonomous Response mode, these measures would have been applied immediately, effectively halting the data exfiltration attempts.

Further recommendations for Autonomous Response actions in Darktrace‘s Incident Interface, with surgical response targeting both the internal data collection and subsequent exfiltration.
Figure 4: Further recommendations for Autonomous Response actions in Darktrace‘s Incident Interface, with surgical response targeting both the internal data collection and subsequent exfiltration.

Scattered Spider’s use of RaaS

In this recent Scattered Spider incident observed by Darktrace, exfiltration appears to have been the primary impact. While no signs of ransomware deployment were observed here, it is possible that this was the threat actors’ original intent, consistent with other recent Scattered Spider attacks involving RaaS platforms like DragonForce.

DragonForce emerged towards the end of 2023, operating by offering their platform and capabilities on a wide scale. They also launched a program which offered their affiliates 80% of the eventual ransom, along with tools for further automation and attack management [13].

The rise of RaaS and attacker customization is fragmenting TTPs and indicators, making it harder for security teams to anticipate and defend against each unique intrusion.

While DragonForce appears to be the latest RaaS used by Scattered Spider, it is not the first, showcasing the ongoing evolution of tactics used the group.

In addition, the BlackCat RaaS strain was reportedly used by Scattered Spider for their attacks against Caesars Entertainment and MGM Resorts International [10].

In 2024 the group was also seen making use of additional RaaS strains; RansomHub and Qilin [15].

What security teams and CISOs can do to defend against Scattered Spider

The ongoing changes in tactics used by Scattered Spider, reliance on LOTL techniques, and continued adoption of evolving RaaS providers like DragonForce make it harder for organizations and their security teams to prepare their defenses against such attacks.

CISOs and security teams should implement best practices such as MFA, Single Sign-On (SSO), notifications for suspicious logins, forward logging, ethical phishing tests.

Also, given Scattered Spider’s heavy focus on social engineering, and at times using their native English fluency to their advantage, it is critical to IT and help desk teams are reminded they are possible targets.

Beyond social engineering, the threat actor is also adept at taking advantage of third-party SaaS applications in use by victims to harvest common SaaS data, such as PII and configuration data, that enable the threat actor to take on multiple identities across different domains.

With Darktrace’s Self-Learning AI, anomaly-based detection, and Autonomous Response inhibitors, businesses can halt malicious activities in real-time, whether attackers are using known TTPs or entirely new ones. Offerings such as Darktrace /Attack Surface Management enable security teams to proactively identify signs of malicious activity before it can cause an impact, while more generally Darktrace’s ActiveAI Security Platform can provide a comprehensive view of an organization’s digital estate across multiple domains.

Credit to Justin Torres (Senior Cyber Analyst), Emma Foulger (Global Threat Research Operations Lead), Zaki Al-Dhamari (Cyber Analyst), Nathaniel Jones (VP, Security & AI Strategy, FCISO), and Ryan Traill (Analyst Content Lead)

---------------------

The information provided in this blog post is for general informational purposes only and is provided "as is" without any representations or warranties, express or implied. While Darktrace makes reasonable efforts to ensure the accuracy and timeliness of the content related to cybersecurity threats such as Scattered Spider, we make no warranties or guarantees regarding the completeness, reliability, or suitability of the information for any purpose.

This blog post does not constitute professional cybersecurity advice, and should not be relied upon as such. Readers should seek guidance from qualified cybersecurity professionals or legal counsel before making any decisions or taking any actions based on the content herein.

No warranty of any kind, whether express or implied, including, but not limited to, warranties of performance, merchantability, fitness for a particular purpose, or non-infringement, is given with respect to the contents of this post.

Darktrace expressly disclaims any liability for any loss or damage arising from reliance on the information contained in this blog.

Appendices

References

[1] https://www.cisa.gov/news-events/cybersecurity-advisories/aa23-320a

[2] https://attack.mitre.org/groups/G1015/

[3] https://www.rapid7.com/blog/post/scattered-spider-rapid7-insights-observations-and-recommendations/

[4] https://www.crowdstrike.com/en-us/blog/scattered-spider-attempts-to-avoid-detection-with-bring-your-own-vulnerable-driver-tactic/

[5] https://krebsonsecurity.com/2024/06/alleged-boss-of-scattered-spider-hacking-group-arrested/?web_view=true

[6] https://www.cxtoday.com/crm/uk-teenager-accused-of-hacking-twilio-lastpass-mailchimp-arrested/

[7] https://mailchimp.com/newsroom/august-2022-security-incident/

[8] https://techcrunch.com/2023/02/02/0ktapus-hackers-are-back-and-targeting-tech-and-gaming-companies-says-leaked-report/

[9] https://www.pcmag.com/news/hackers-behind-riot-games-breach-stole-league-of-legends-source-code

[10] https://www.bbrown.com/us/insight/a-look-back-at-the-mgm-and-caesars-incident/

[11] https://cyberresilience.com/threatonomics/scattered-spider-uk-retail-attacks/

[12] https://www.crowdstrike.com/en-us/cybersecurity-101/ransomware/ransomware-as-a-service-raas/

[13] https://www.group-ib.com/blog/dragonforce-ransomware/
[14] https://blackpointcyber.com/wp-content/uploads/2024/11/DragonForce.pdf
[15] https://x.com/MsftSecIntel/status/1812932749314978191?lang=en

Select MITRE tactics associated with Scattered Spider

Tactic – Technique – Technique Name

Reconnaissance - T1598 -   Phishing for Information

Initial Access - T1566 – Phishing

Execution - T1204 - User Execution

Privilege Escalation - T1068 - Exploitation for Privilege Escalation

Defense Evasion - T1656 - Impersonation

Credential Access - T1621 - Multi-Factor Authentication Request Generation

Lateral Movement - T1021 - Remote Services

Command and Control - T1102 - Web Service

Command and Control - T1219 - Remote Access Tools

Command and Control - T1572 - Protocol Tunneling

Exfiltration - T1567 - Exfiltration Over Web Service

Impact - T1657 - Financial Theft

Select MITRE tactics associated with DragonForce

Tactic – Technique – Technique Name

Initial Access, Defense Evasion, Persistence, Privilege Escalation - T1078 - Valid Accounts

Initial Access, Persistence - T1133 - External Remote Services

Initial Access - T1190 - Exploit Public-Facing Application

Initial Access - T1566 – Phishing

Execution - T1047 - Windows Management Instrumentation

Privilege Escalation - T1068 - Exploitation for Privilege Escalation

Lateral Movement - T1021 - Remote Services

Impact - T1486 - Data Encrypted for Impact

Impact - T1657 - Financial Theft

Select Darktrace models

Compliance / Internet Facing RDP Server

Compliance / Incoming Remote Access Tool

Compliance / Remote Management Tool on Server

Anomalous File / Internet Facing System File Download

Anomalous Server Activity/ New User Agent from Internet Facing System

Anomalous Connection / Callback on Web Facing Device

Device / Internet Facing System with High Priority Alert

Anomalous Connection / Unusual Admin RDP

Anomalous Connection / High Priority DRSGetNCChanges

Anomalous Connection / Unusual Internal SSH

Anomalous Connection / Active Remote Desktop Tunnel

Compliance / Pastebin

Anomalous Connection / Possible Tunnelling to Rare Endpoint

Compromise / Beaconing Activity to External Rare

Device / Long Agent Connection to New Endpoint

Compromise / SSH to Rare External AWS

Compliance / SSH to Rare External Destination

Anomalous Server Activity / Outgoing from Server

Anomalous Connection / Large Volume of LDAP Download

Unusual Activity / Internal Data Transfer on New Device

Anomalous Connection / Download and Upload

Unusual Activity / Enhanced Unusual External Data Transfer

Compromise / Ransomware/Suspicious SMB Activity

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About the author
Emma Foulger
Global Threat Research Operations Lead

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July 24, 2025

Closing the Cloud Forensics and Incident Response Skills Gap

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Every alert that goes uninvestigated is a calculated risk — and teams are running out of room for error

Security operations today are stretched thin. SOCs face an overwhelming volume of alerts, and the shift to cloud has only made triage more complex.

Our research suggests that 23% of cloud alerts are never investigated, leaving risk on the table.

The rapid migration to cloud resources has security teams playing catch up. While they attempt to apply traditional on-prem tools to the cloud, it’s becoming increasingly clear that they are not fit for purpose. Especially in the context of forensics and incident response, the cloud presents unique complexities that demand cloud-specific solutions.

Organizations are increasingly adopting services from multiple cloud platforms (in fact, recent studies suggest 89% of organizations now operate multi-cloud environments), and container-based and serverless setups have become the norm. Security analysts already have enough on their plates; it’s unrealistic to expect them to be cloud experts too.

Why Digital Forensics and Incident Response (DFIR) roles are so hard to fill

Compounding these issues of alert fatigue and cloud complexity, there is a lack of DFIR talent. The cybersecurity skills gap is a well-known problem.

According to the 2024 ISC2 Cybersecurity Workforce Study, there is a global shortage of 4.8 million cybersecurity workers, up 19% from the previous year.

Why is this such an issue?

  • Highly specialized skill set: DFIR professionals need to have a deep understanding of various operating systems, network protocols, and security architectures, even more so when working in the cloud. They also need to be proficient in using a wide range of forensic tools and techniques. This level of expertise takes a lot of time and effort to develop.
  • Rapid technological changes: The cloud landscape is constantly changing and evolving with new services, monitoring tools, security mechanisms, and threats emerging regularly. Keeping up with these changes and staying current requires continuous learning and adaptation.
  • Lack of formal education and training: There are limited educational programs specifically dedicated for DFIR. Further, an industry for cloud DFIR has yet to be defined. While some universities and institutions offer courses or certifications in digital forensics, they may not cover the full spread of knowledge required in real-world incident response scenarios, especially for cloud-based environments.
  • High-stress nature of the job: DFIR professionals often work under tight deadlines in high-pressure situations, especially when handling security incidents. This can lead to burnout and high turnover rates in the profession.

Bridging the skills gap with usable cloud digital forensics and incident response tools  

To help organizations close the DFIR skills gap, it's critical that we modernize our approaches and implement a new way of doing things in DFIR that's fit for the cloud era. Modern cloud forensics and incident response platforms must prioritize usability in order to up-level security teams. A platform that is easy to use has the power to:

  • Enable more advanced analysts to be more efficient and have the ability to take on more cases
  • Uplevel more novel analysts to perform more advanced tasks than ever before
  • Eliminate cloud complexity– such as the complexities introduced by multi-cloud environments and container-based and serverless setups

What to look for in cloud forensics and incident response solutions

The following features greatly improve the impact of cloud forensics and incident response:

Data enrichment: Automated correlation of collected data with threat intelligence feeds, both external and proprietary, delivers immediate insight into suspicious or malicious activities. Data enrichment expedites investigations, enabling analysts to seamlessly pivot from key events and delve deeper into the raw data.

Single timeline view: A unified perspective across various cloud platforms and data sources is crucial. A single timeline view empowers security teams to seamlessly navigate evidence based on timestamps, events, users, and more, enhancing investigative efficiency. Pulling together a timeline has historically been a very time consuming task when using traditional approaches.

Saved search: Preserving queries during investigations allows analysts to re-execute complex searches or share them with colleagues, increasing efficiency and collaboration.

Faceted search: Facet search options provide analysts with quick insights into core data attributes, facilitating efficient dataset refinement.

Cross-cloud investigations: Analyzing evidence acquired from multiple cloud providers in a single platform is crucial for security teams. A unified view and timeline across cross cloud is critical in streamlining investigations.

How Darktrace can help

Darktrace’s cloud offerings have been bolstered with the acquisition of Cado Security Ltd., which enables security teams to gain immediate access to forensic-level data in multi-cloud, container, serverless, SaaS, and on-premises environments.

Not only does Darktrace offer centralized automation solutions for cloud forensics and investigation, but it also delivers a proactive approach Cloud Detection and Response (CDR). Darktrace / CLOUD is built with advanced AI to make cloud security accessible to all security teams and SOCs. By using multiple machine learning techniques, Darktrace brings unprecedented visibility, threat detection, investigation, and incident response to hybrid and multi-cloud environments.

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