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October 13, 2023

Protecting Brazilian Organizations from Malware

Discover how Darktrace DETECT thwarted a banking trojan targeting Brazilian organizations, preventing data theft and informing the customer.
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
Roberto Romeu
Senior SOC Analyst
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13
Oct 2023

Nationally Targeted Cyber Attacks

As the digital world becomes more and more interconnected, the threat of cyber-attacks transcends borders and presents a significant concern to security teams worldwide. Yet despite this, some malicious actors have shown a tendency to focus their attacks on specific countries. By employing highly tailored tactics, techniques, and procedures (TTPs) to target users and organizations from one nation, rather than launching more widespread campaigns, threat actors are able to maximize the efficiency and efficacy of their attacks.

What is Guildma and how does it work?

One example can be seen in the remote access trojan (RAT) and information stealer, Guildma. Guildma, also known by the demonic moniker, Astaroth, first appeared in the wild in 2017 and is a Latin America-based banking trojan known to primarily target organizations in Brazil, although has more recently been observed in North America and Europe too [1].

By concentrating their efforts on Brazil, Guildma is able to launch attacks with a high degree of specificity, focussing their language on Brazilian norms, referencing Brazilian institutions, and tailoring their social engineering accordingly. Moreover, considering that Brazilian customers likely represent a relatively small portion of security vendors’ clientele, there may be a limited pool of available indicators of compromise (IoCs). This limitation could significantly impact the efficacy of traditional security measures that rely on signature-based detection methods in identifying emerging threats.

Darktrace vs. Guildma

In June 2023, Darktrace observed a Guildma compromise on the network of a Brazilian customer in the manufacturing sector. The anomaly-based detection capabilities of Darktrace DETECT™ allowed it to identify suspicious activity surrounding the compromise, agnostic of any IoCs or specific signatures of a threat actor. Following the successful detection of the malware, the Darktrace Security Operations Center (SOC) carried out a thorough investigation into the compromise and brought it to the attention of the customer’s security team, allowing them to quickly react and prevent any further escalation.

This early detection by Darktrace effectively shut down Guildma operations on the network before any sensitive data could be gathered and stolen by malicious actors.

Attack Overview

In the case of the Guildma RAT detected by Darktrace, the affected system was a desktop device, ostensibly used by one employee. The desktop was first observed on the customer’s network in April 2023; however, it is possible that the initial compromise took place before Darktrace had visibility over the network. Guildma compromises typically start with phishing campaigns, indicating that the initial intrusion in this case likely occurred beyond the scope of Darktrace’s monitoring [2].

Early indicators

On June 23, 2023, Darktrace DETECT observed the first instance of unusual activity being performed by the affected desktop device, namely regular HTTP POST requests to a suspicious domain, indicative of command-and-control (C2) beaconing activity. The domain used an unusual Top-Level Domain (TLD), with a plausibly meaningful (in Portuguese) second-level domain and a seemingly random 11-character third-level domain, “dn00x1o0f0h.puxaofolesanfoneiro[.]quest”.

Throughout the course of this attack, Darktrace observed additional connections like this, representing something of a signature of the attack. The suspicious domains were typically registered within six months of observation, featured an uncommon TLD, and included a seemingly randomized third-level domain of 6-11 characters, followed by a plausibly legitimate second-level domain with a minimum of 15 characters. The connections to these unusual endpoints all followed a similar two-hour beaconing period, suggesting that Guildma may rotate its C2 infrastructure, using the Multi-Stage Channels TTP (MITRE ID T1104) to evade restrictions by firewalls or other signature-based security tools that rely on static lists of IoCs and “known bads”.

Figure 1: Model Breach Event Log for the “Compromise / Agent Beacon (Long Period)”. The connections at two-hour intervals, including at unreasonably late hours, is consistent with beaconing for C2.

Living-off-the-land with BITS abuse

A week later, on June 30, 2023, the affected device was observed making an unusual Microsoft BITS connection. BitsAdmin is a deprecated administrative tool available on most Windows devices and can be leveraged by attackers to transfer malicious obfuscated payloads into and around an organization’s network. The domain observed during this connection, "cwiufv.pratkabelhaemelentmarta[.]shop”, follows the previously outlined domain naming convention. Multiple open-source intelligence (OSINT) sources indicated that the endpoint had links to malware and, when visited, redirected users to the Brazilian versions of WhatsApp and Zoom. This is likely a tactic employed by threat actors to ensure users are unaware of suspicious domains, and subsequent malware downloads, by redirected them to a trusted source.

Figure 2: A screenshot of the Model Breach log summary of the “Unusual BITS Activity” model breach. The breach log contains key details such as the ASN, hostname, and user agent used in the breaching connection.

Obfuscated Tooling Downloads

Within one minute of the suspicious BITS activity, Darktrace detected the device downloading a suspicious file from the aforementioned endpoint, (cwiufv.pratkabelhaemelentmarta[.]shop). The file in question appeared to be a ZIP file with the 17-digit numeric name query, namely “?37627343830628786”, with the filename “zodzXLWwaV.zip”.

However, Darktrace DETECT recognized that the file extension did not match its true file type and identified that it was, in fact, an executable (.exe) file masquerading as a ZIP file. By masquerading files downloads, threat actors are able to make their malicious files seem legitimate and benign to security teams and traditional security tools, thereby evading detection. In this case, the suspicious file in question was indeed identified as malicious by multiple OSINT sources.

Following the initial download of this masqueraded file, Darktrace also detected subsequent downloads of additional executable files from the same endpoint.  It is possible that these downloads represented Guildma actors attempting to download additional tooling, including the information-stealer widely known as Astaroth, in order to begin its data collection and exfiltration operations.

Figure 3: A screenshot of a graph produced by the Threat Visualizer of the affected device's external connections. The visual aid marks breaches with red and orange dots, creating a more intuitive explanation of observed behavior.

Darktrace SOC

The successful detection of the masqueraded file transfer triggered an Enhanced Monitoring model breach, a high-fidelity model designed to detect activity that is more likely indicative of an ongoing compromise.  

This breach was immediately escalated to the Darktrace SOC for analysis by Darktrace’s team of expert analysts who were able to complete a thorough investigation and notify the customer’s security team of the compromise in just over half an hour. The investigation carried out by Darktrace’s analysts confirmed that the activity was, indeed, malicious, and provided the customer’s security team with details around the extent of the compromise, the specific IoCs, and risks this compromise posed to their digital environment. This information empowered the customer’s security team to promptly address the issue, having a significant portion of the investigative burden reduced and resolved by the round-the-clock Darktrace analyst team.

In addition to this, Cyber AI Analyst™ launched an investigation into the ongoing compromise and was able to connect the anomalous HTTP connections to the subsequent suspicious file downloads, viewing them as one incident rather than two isolated events. AI Analyst completed its investigation in just three minutes, upon which it provided a detailed summary of events of the activity, further aiding the customer’s remediation process.

Figure 4: CyberAI Analyst summary of the suspicious activity. A prose summary of the breach activity and the meaning of the technical details is included to maintain an easily digestible stream of information.

Conclusion

While the combination of TTPs observed in this Guildma RAT compromise is not uncommon globally, the specificity to targeting organizations in Brazil allows it to be incredibly effective. By focussing on just one country, malicious actors are able to launch highly specialized attacks, adapting the language used and tailoring the social engineering effectively to achieve maximum success. Moreover, as Brazil likely represents a smaller segment of security vendors’ customers, therefore leading to a limited pool of IoCs, attackers are often able to evade traditional signature-based detections.

Darktrace DETECT’s anomaly-based approach to threat detection allows for effective detection, mitigation, and response to emerging threats, regardless of the specifics of the attack and without relying on threat intelligence or previous IoCs. Ultimately in this case, Darktrace was able to identify the suspicious activity surrounding the Guildma compromise and swiftly bring it to the attention of the customer’s security team, before any data gathering, or exfiltration activity took place.

Darktrace’s threat detection capabilities coupled with its expert analyst team and round-the-clock SOC response is a highly effective addition to an organization’s defense-in-depth, whether in Brazil or anywhere else around the world.

Credit to Roberto Romeu, Senior SOC Analyst, Taylor Breland, Analyst Team Lead, San Francisco

References

https://malpedia.caad.fkie.fraunhofer.de/details/win.astaroth

https://www.welivesecurity.com/2020/03/05/guildma-devil-drives-electric/  

Appendices

Darktrace DETECT Model Breaches

  • Compromise / Agent Beacon (Long Period)
  • Device / Unusual BITS Activity
  • Anomalous File / Anomalous Octet Stream (No User Agent)
  • Anomalous File / Masqueraded File Transfer (Enhanced Monitoring Model)
  • Anomalous File / EXE from Rare External Location
  • Anomalous File / Multiple EXE from Rare External Locations

List of IoCs

IoC Type - Description + Confidence

5q710e1srxk.broilhasoruikaliventiladorrta[.]shop - Domain - Likely C2 server

m2pkdlse8md.roilhasohlcortinartai[.]hair - Domain - Likely C2 server

cwiufv.pratkabelhaemelentmarta[.]shop - Domain - C2 server

482w5pct234.jaroilcasacorkalilc[.]ru[.]com - Domain - C2 server

dn00x1o0f0h.puxaofolesanfoneiro[.]quest - Domain - Likely C2 server

10v7mybga55.futurefrontier[.]cyou - Domain - Likely C2 server

f788gbgdclp.growthgenerator[.]cyou - Domain - Likely C2 server

6nieek.satqabelhaeiloumelsmarta[.]shop - Domain - Likely C2 server

zodzXLWwaV.zip (SHA1 Hash: 2a4062e10a5de813f5688221dbeb3f3ff33eb417 ) - File hash - Malware

IZJQCAOXQb.zip (SHA1 Hash: eaec1754a69c50eac99e774b07ef156a1ca6de06 ) - File hash - Likely malware

MITRE ATT&CK Mapping

ATT&CK Technique - Technique ID

Multi-Stage Channels - T1104

BITS Jobs - T1197

Application Layer Protocol: Web Protocols - T1071.001

Acquire Infrastructure: Web Services - T1583.006

Obtain Capabilities: Malware - T1588.001

Masquerading - T1036

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
Roberto Romeu
Senior SOC 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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