Blog
/
Email
/
October 2, 2024

How Darktrace won an email security trial by learning the business, not the breach

Discover how Darktrace identified a sophisticated business email compromise (BEC) attack to successfully acquire a prospective customer in a trial alongside two other email security vendors. This case demonstrates the clear differentiator of true unsupervised machine learning applied to the right use cases, compared to miscellaneous vendor hype around AI.
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
Carlos Gray
Senior Product Marketing Manager, Email
Default blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog image
02
Oct 2024

Recently, Darktrace ran a customer trial of our email security product for a leading European infrastructure operator looking to upgrade its email protection.

During this prospective customer trial, Darktrace encountered several security incidents that penetrated existing security layers. Two of these incidents were Business Email Compromise (BEC) attacks, which we’re going to take a closer look at here.  

Darktrace was deployed for a trial at the same time as two other email security vendors, who were also being evaluated by the prospective customer. Darktrace’s superior detection of threats in this trial laid the groundwork for the respective company to choose our product.

Let’s dig into some of the elements of this Darktrace tech win and how they came to light during this trial.

Why truly intelligent AI starts learning from scratch

Darktrace’s detection capabilities are powered by true unsupervised machine learning, which detects anomalous activity from its ever-evolving understanding of normal for every unique environment. Consequently, it learns every business from the beginning, training on an organization’s data to understand normal for its users, devices, assets and the millions of connections between them.  

This learning period takes around a week, during which the AI hones its understanding of the business to a precise degree. At this stage, the system may produce some noise or lack precision, but this is a testament to our unsupervised machine learning. Unlike solutions that promise faster results by relying on preset assumptions, our AI takes the necessary time to learn from scratch, ensuring a deeper understanding and increasingly accurate detection over time.

Real threats detected by Darktrace

Attack 1: Supply chain attack

BEC and supply chain attacks are notoriously difficult to detect, as they take advantage of established, trusted senders.  

This attack came from a legitimate server via a known supplier with which the prospective customer had active and ongoing communication. Using the compromised account, the attacker didn’t just send out randomized spam, they crafted four sophisticated social engineering emails with the aim of soliciting users to click on a link – directly tapping into existing conversations. Darktrace / EMAIL was configured in passive mode during this trial; it would otherwise have held the emails before they arrived in the inbox. Luckily in this instance, one user reported the email to the CISO before any other users clicked the link. Upon investigation, the link contained timed ransomware detonation.  

Darktrace was the only vendor that caught any of these four emails. Our unique behavioral AI approach enables Darktrace / EMAIL to protect customers from even the most sophisticated attacks that abuse prior trust and relationships.

How did Darktrace catch this attack that other vendors missed?

With traditional email security, security teams have been obliged to allow entire organizations to eliminate false positives – on the premise that it’s easier to make a broad decision based on an entire known domain and assume that potential risk of a supply chain attack.

By contrast, Darktrace adopts a zero trust mentality, analyzing every email to understand whether communication that has previously been safe remains safe. That’s why Darktrace is uniquely positioned to detect BEC, based on its deep learning of internal and external users. Because it creates individual profiles for every account, group and business composed of multiple signals, it can detect deviations in their communication patterns based on the context and content of each message. We think of this as the ‘self-learning’ vs ‘learning the breach’ differentiator.

Fig 1: Darktrace analysis of one of four malicious emails sent by the trusted supplier. It gives it an anomaly score of 100, despite it being from a known correspondent with a known domain relationship and moderate mailing history.

If set in autonomous mode where it can apply actions, Darktrace / EMAIL would have quarantined all four emails. Using machine learning indicators such as ‘Inducement Shift’ and ‘General Behavioral Anomaly’, it deemed the four emails ‘Out of Character’. It also identified the link as highly likely to be phishing, based purely on its context. These indicators are critical because the link itself belonged to a widely used legitimate domain, leveraging their established internet reputation to appear safe.  

Around an hour later the supplier regained control of the account and sent a legitimate email alerting a wide distribution list to the phishing emails sent. Darktrace was able to discern the previously sent malicious emails from the current legitimate emails and allowed these emails through. Compared to other vendors that have a static understanding of malicious which needs to be updated (in cases like this, once a supplier is de-compromised), Darktrace’s deep understanding of external entities enables further nuance and precision in determining good from bad.

Fig 2: Darktrace let through four emails (subject line: Virus E-Mail) from the supplier once they had regained control of the compromised account, with a limited anomaly score despite having held the previous malicious emails. If any actions had been taken a red icon would show on the right-hand side – in this instance Darktrace did not take action and let the emails through.

Attack 2: Microsoft 365 account takeover

As part of building behavioral profiles of every email user, Darktrace analyzes their wider account activity. Account activity, such as unusual login patterns and administrative activity, is a key variable to detect account compromise before malicious activity occurs, but it also feeds into Darktrace’s understanding of which emails should belong in every user’s inbox.  

When the customer experienced an account compromise on day two of the trial, Darktrace began an investigation and was able to provide the full breakdown and scope of the incident.

The account was compromised via an email, which Darktrace would have blocked if it had been deployed autonomously at the time. Once the account had been compromised, detection details included:

  • Unusual Login and Account Update
  • Multiple Unusual External Sources for SaaS Credential
  • Unusual Activity Block
  • Login From Rare Endpoint While User is Active
Fig 3: Darktrace flagged the following indicators of compromise that deviated from normal behavior for the user in question, signaling an account takeover

With Darktrace / EMAIL, every user is analyzed for behavioral signals including authentication and configuration activity. Here the unusual login, credential input and rare endpoint were all clear signals a compromised account, contextualized against what is normal for that employee. Because Darktrace isn’t looking at email security merely from the perspective of the inbox. It constantly reevaluates the identity of each individual, group and organization (as defined by their behavioral signals), to determine precisely what belongs in the inbox and what doesn’t.  

In this instance, Darktrace / EMAIL would have blocked the incident were it not deployed in passive mode. In the initial intrusion it would have blocked the compromising email. And once the account was compromised, it would have taken direct blocking actions on the account based on the anomalous activity it detected, providing an extra layer of defense beyond the inbox.  

Account takeover protection is always part of Darktrace / EMAIL, which can be extended to fully cover Microsoft 365 SaaS with Darktrace / IDENTITY. By bringing SaaS activity into scope, security teams also benefit from an extended set of use cases including compliance and resource management.

Why this customer committed to Darktrace / EMAIL

“Darktrace was the only AI vendor that showed learning,” – CISO, Trial Customer

Throughout this trial, Darktrace evolved its understanding of the trial customer’s business and its email users. It identified attacks that other vendors did not, while allowing safe emails through. Furthermore, the CISO explicitly cited Darktrace as the only technology that demonstrated autonomous learning. As well as catching threats that other vendors did not, the CISO saw maturity areas such as how Darktrace dealt with non-productive mail and business-as-usual emails, without any user input.  Because of the nature of unsupervised ML, Darktrace’s learning of right and wrong will never be static or complete – it will continue to revise its understanding and adapt to the changing business and communications landscape.

This case study highlights a key tenet of Darktrace’s philosophy – that a rules and tuning-based approach will always be one step behind. Delivering benign emails while holding back malicious emails from the same domain demonstrates that safety is not defined in a straight line, or by historical precedent. Only by analyzing every email in-depth for its content and context can you guarantee that it belongs.  

While other solutions are making efforts to improve a static approach with AI, Darktrace’s AI remains truly unsupervised so it is dynamic enough to catch the most agile and evolving threats. This is what allows us to protect our customers by plugging a vital gap in their security stack that ensures they can meet the challenges of tomorrow's email attacks.

Interested in learning more about Darktrace / EMAIL? Check out our product hub.

Download: Darktrace / EMAIL Solution Brief

Discover the most advanced cloud-native AI email security solution to protect your domain and brand while preventing phishing, novel social engineering, business email compromise, account takeover, and data loss.

  • Gain up to 13 days of earlier threat detection and maximize ROI on your current email security
  • Experience 20-25% more threat blocking power with Darktrace / EMAIL
  • Stop the 58% of threats bypassing traditional email security

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
Carlos Gray
Senior Product Marketing Manager, Email

More in this series

No items found.

Blog

/

Network

/

July 24, 2025

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

Default blog imageDefault blog image

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

Continue reading
About the author
Emma Foulger
Global Threat Research Operations Lead

Blog

/

/

July 24, 2025

Closing the Cloud Forensics and Incident Response Skills Gap

Default blog imageDefault blog image

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.

[related-resource]

Continue reading
About the author
Your data. Our AI.
Elevate your network security with Darktrace AI