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March 19, 2024

Pikabot Malware: Insights, Impact, & Attack Analysis

Learn about Pikabot malware and its rapid evolution in the wild, impacting organizations and how to defend against this growing threat.
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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.
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19
Mar 2024

How does Loader Malware work?

Throughout 2023, the Darktrace Threat Research team identified and investigated multiple strains of loader malware affecting customers across its fleet. These malicious programs typically serve as a gateway for threat actors to gain initial access to an organization’s network, paving the way for subsequent attacks, including additional malware infections or disruptive ransomware attacks.

How to defend against loader malware

The prevalence of such initial access threats highlights the need for organizations to defend against multi-phase compromises, where modular malware swiftly progresses from one stage of an attack to the next. One notable example observed in 2023 was Pikabot, a versatile loader malware used for initial access and often accompanied by secondary compromises like Cobalt Strike and Black Basta ransomware.

While Darktrace initially investigated multiple instances of campaign-like activity associated with Pikabot during the summer of 2023, a new campaign emerged in October which was observed targeting a Darktrace customer in Europe. Thanks to the timely detection by Darktrace DETECT™ and the support of Darktrace’s Security Operations Center (SOC), the Pikabot compromise was quickly shut down before it could escalate into a more disruptive attack.

What is Pikabot?

Pikabot is one of the latest modular loader malware strains that has been active since the first half of 2023, with several evolutions in its methodology observed in the months since. Initial researchers noted similarities to the Qakbot aka Qbot or Pinkslipbot and Mantanbuchus malware families, and while Pikabot appears to be a new malware in early development, it shares multiple commonalities with Qakbot [1].

First, both Pikabot and Qakbot have similar distribution methods, can be used for multi-stage attacks, and are often accompanied by downloads of Cobalt Strike and other malware strains. The threat actor known as TA577, which has also been referred to as Water Curupira, has been seen to use both types of malware in spam campaigns which can lead to Black Basta ransomware attacks [2] [3].Notably, a rise in Pikabot campaigns were observed in September and October 2023, shortly after the takedown of Qakbot in Operation Duck Hunt, suggesting that Pikabot may be serving as a replacement for initial access to target network [4].

How does Pikabot malware work?

Many Pikabot infections start with a malicious email, particularly using email thread hijacking; however, other cases have been distributed via malspam and malvertising [5]. Once downloaded, Pikabot runs anti-analysis techniques and checks the system’s language, self-terminating if the language matches that of a Commonwealth of Independent States (CIS) country, such as Russian or Ukrainian. It will then gather key information to send to a command-and-control (C2) server, at which point additional payload downloads may be observed [2]. Early response to a Pikabot infection is important for organizations to prevent escalation to a significant compromise such as ransomware.

Darktrace’s Coverage of Pikabot malware

Between April and July 2023, the Darktrace Threat Research team investigated Pikabot infections affected more than 15 customer environments; these attacks primarily targeted US and European organizations spanning multiple industries, and most followed the below lifecycle:

  1. Initial access via malspam or email, often outside of Darktrace’s scope
  2. Suspicious executable download from a URI in the format /\/[a-z0-9A-Z]{3,}\/[a-z0-9A-Z]{5,}/ and using a Windows PowerShell user agent
  3. C2 connections to IP addresses on uncommon ports including 1194 and 2078
  4. Some cases involved further C2 activity to Cobalt Strike endpoints

In October 2023, a second campaign emerged that largely followed the same attack pattern, with a notable difference that cURL was used for the initial payload download as opposed to PowerShell. All the Pikabot cases that Darktrace has observed since October 2023 have used cURL, which could indicate a shift in approach from targeting Windows devices to multi-operating system environments.

Figure 1: Timeline of the Pikabot infection over a 2-hour period.

On October 17, 2023, Darktrace observed a Pikabot infection on the network of a European customer after an internal user seemingly clicked a malicious link in a phishing email, thereby compromising their device. As the customer did not have Darktrace/Email™ deployed on their network, Darktrace did not have visibility over the email. Despite this, DETECT was still able to provide full visibility over the network-based activity that ensued.

Darktrace observed the device using a cURL user agent when initiating the download of an unusual executable (.exe) file from an IP address that had never previously been observed on the network. Darktrace further recognized that the executable file was attempting to masquerade as a different file type, likely to evade the detection of security teams and their security tools. Within one minute, the device began to communicate with additional unusual IP addresses on uncommon ports (185.106.94[.]174:5000 and 80.85.140[.]152:5938), both of which have been noted by open-source intelligence (OSINT) vendors as Pikabot C2 servers [6] [7].

Figure 2: Darktrace model breach Event Log showing the initial file download, immediately followed by a connection attempt to a Pikabot C2 server.

Around 40 minutes after the initial download, Darktrace detected the device performing suspicious DNS tunneling using a pattern that resembled the Cobalt Strike Beacon. This was accompanied by beaconing activity to a rare domain, ‘wordstt182[.]com’, which was registered only 4 days prior to this activity [8]. Darktrace observed additional DNS connections to the endpoint, ‘building4business[.]net’, which had been linked to Black Basta ransomware [2].

Figure 3: The affected device making successful TXT DNS requests to known Black Basta endpoints.

As this customer had integrated Darktrace with the Microsoft Defender, Defender was able to contextualize the DETECT model breaches with endpoint insights, such as known threats and malware, providing customers with unparalleled visibility of the host-level detections surrounding network-level anomalies.

In this case, the behavior of the affected device triggered multiple Microsoft Defender alerts, including one alert which linked the activity to the threat actor Storm-0464, another name for TA577 and Water Curupira. These insights were presented to the customer in the form of a Security Integration alert, allowing them to build a full picture of the ongoing incident.

Figure 4: Security Integration alert from Microsoft Defender in Darktrace, linking the observed activity to the threat group Storm-0464.

As the customer had subscribed to Darktrace’s Proactive Threat Notification (PTN) service, the customer received timely alerts from Darktrace’s SOC notifying them of the suspicious activity associated with Pikabot. This allowed the customer’s security team to quickly identify the affected device and remove it from their environment for remediation.

Although the customer did have Darktrace RESPOND™ enabled on their network, it was configured in human confirmation mode, requiring manual application for any RESPOND actions. RESPOND had suggested numerous actions to interrupt and contain the attack, including blocking connections to the observed Pikabot C2 addresses, which were manually actioned by the customer’s security team after the fact. Had RESPOND been enabled in autonomous response mode during the attack, it would have autonomously blocked these C2 connections and prevented the download of any suspicious files, effectively halting the escalation of the attack.

Nonetheless, Darktrace DETECT’s prompt identification and alerting of this incident played a crucial role in enabling the customer to mitigate the threat of Pikabot, preventing it from progressing into a disruptive ransomware attack.

Figure 5: Darktrace RESPOND actions recommended from the initial file download and throughout the C2 traffic, ranging from blocking specific connections to IP addresses and ports to enforcing a normal pattern of life for the source device.

Conclusion

Pikabot is just one recent example of a modular strain of loader known for its adaptability and speed, seamlessly changing tactics from one campaign to the next and utilizing new infrastructure to initiate multi-stage attacks. Leveraging commonly used tools and services like Windows PowerShell and cURL, alongside anti-analysis techniques, this malware can evade the detection and often bypass traditional security tools.

In this incident, Darktrace detected a Pikabot infection in its early stages, identifying an anomalous file download using a cURL user agent, a new tactic for this particular strain of malware. This timely detection, coupled with the support of Darktrace’s SOC, empowered the customer to quickly identify the compromised device and act against it, thwarting threat actors attempting to connect to malicious Cobalt Strike and Black Basta servers. By preventing the escalation of the attack, including potential ransomware deployment, the customer’s environment remained safeguarded.

Had Darktrace RESPOND been enabled in autonomous response mode at the time of this attack, it would have been able to further support the customer by applying targeted mitigative actions to contain the threat of Pikabot at its onset, bolstering their defenses even more effectively.

Credit to Brianna Leddy, Director of Analysis, Signe Zaharka, Senior Cyber Security Analyst

Appendix

Darktrace DETECT Models

Anomalous Connection / Anomalous SSL without SNI to New External

Anomalous Connection / Application Protocol on Uncommon Port

Anomalous Connection / Multiple Connections to New External TCP Port

Anomalous Connection / New User Agent to IP Without Hostname

Anomalous Connection / Powershell to Rare External

Anomalous Connection / Rare External SSL Self-Signed

Anomalous Connection / Repeated Rare External SSL Self-Signed

Anomalous File / EXE from Rare External Location

Anomalous File / Masqueraded File Transfer

Anomalous File / Multiple EXE from Rare External Locations

Compromise / Agent Beacon to New Endpoint

Compromise / Beacon to Young Endpoint

Compromise / Beaconing Activity To External Rare

Compromise / DNS / DNS Tunnel with TXT Records

Compromise / New or Repeated to Unusual SSL Port

Compromise / SSL Beaconing to Rare Destination

Compromise / Suspicious Beaconing Behaviour

Compromise / Suspicious File and C2

Device / Initial Breach Chain Compromise

Device / Large Number of Model Breaches

Device / New PowerShell User Agent

Device / New User Agent

Device / New User Agent and New IP

Device / Suspicious Domain

Security Integration / C2 Activity and Integration Detection

Security Integration / Egress and Integration Detection

Security Integration / High Severity Integration Detection

Security Integration / High Severity Integration Incident

Security Integration / Low Severity Integration Detection

Security Integration / Low Severity Integration Incident

Antigena / Network / External Threat / Antigena File then New Outbound Block

Antigena / Network / External Threat / Antigena Suspicious Activity Block

Antigena / Network / External Threat / Antigena Suspicious File Block

Antigena / Network / Significant Anomaly / Antigena Breaches Over Time Block

Antigena / Network / Significant Anomaly / Antigena Controlled and Model Breach

Antigena / Network / Significant Anomaly / Antigena Enhanced Monitoring from Client Block

Antigena / Network / Significant Anomaly / Antigena Significant Anomaly from Client Block

Antigena / Network / Significant Anomaly / Antigena Significant Security Integration and Network Activity Block

List of Indicators of Compromise (IoC)

IOC - TYPE - DESCRIPTION + CONFIDENCE

128.140.102[.]132 - IP Address - Pikabot Download

185.106.94[.]174:5000 - IP Address: Port - Pikabot C2 Endpoint

80.85.140[.]152:5938 - IP Address: Port - Pikabot C2 Endpoint

building4business[.]net - Hostname - Cobalt Strike DNS Beacon

wordstt182[.]com - Hostname - Cobalt Strike Server

167.88.166[.]109 - IP Address - Cobalt Strike Server

192.9.135[.]73 - IP - Pikabot C2 Endpoint

192.121.17[.]68 - IP - Pikabot C2 Endpoint

185.87.148[.]132 - IP - Pikabot C2 Endpoint

129.153.22[.]231 - IP - Pikabot C2 Endpoint

129.153.135[.]83 - IP - Pikabot C2 Endpoint

154.80.229[.]76 - IP - Pikabot C2 Endpoint

192.121.17[.]14 - IP - Pikabot C2 Endpoint

162.252.172[.]253 - IP - Pikabot C2 Endpoint

103.124.105[.]147 - IP - Likely Pikabot Download

178.18.246[.]136 - IP - Pikabot C2 Endpoint

86.38.225[.]106 - IP - Pikabot C2 Endpoint

198.44.187[.]12 - IP - Pikabot C2 Endpoint

154.12.233[.]66 - IP - Pikabot C2 Endpoint

MITRE ATT&CK Mapping

TACTIC - TECHNIQUE

Defense Evasion - Masquerading: Masquerade File Type (T1036.008)

Command and Control - Application Layer Protocol: Web Protocols (T1071.001)

Command and Control - Non-Standard Port (T1571)

Command and Control - Application Layer Protocol: DNS (T1071.004)

Command and Control - Protocol Tunneling (T1572)

References

[1] https://news.sophos.com/en-us/2023/06/12/deep-dive-into-the-pikabot-cyber-threat/?&web_view=true  

[2] https://www.trendmicro.com/en_be/research/24/a/a-look-into-pikabot-spam-wave-campaign.html

[3] https://thehackernews.com/2024/01/alert-water-curupira-hackers-actively.html

[4] https://www.darkreading.com/cyberattacks-data-breaches/pikabot-malware-qakbot-replacement-black-basta-attacks

[5] https://www.redpacketsecurity.com/pikabot-distributed-via-malicious-ads-6/

[6] https://www.virustotal.com/gui/ip-address/185.106.94.174/detection

[7] https://www.virustotal.com/gui/ip-address/80.85.140.152/detection

[8] https://www.domainiq.com/domain?wordstt182.com

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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.
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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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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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