Explore effective strategies and learn how organizations can enhance Attack Surface Management using artificial intelligence (AI) automation. Read more.
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
Vincent Thiele
Deputy CISO
Share
09
Jun 2021
Effective attack surface management breaks down into four key parts:
Discovery
Assessment and prioritisation
Risk prevention
Integration
Discovery
The most important part of any attack surface management process is the discovery phase. As we’ve mentioned previously, most organizations miss as much as 30 to 50 percent of their true attack surface. This creates huge blind spots when it comes to understanding the real risks your organization is facing. In fact, we believe that something like 80% of all organizations’ cybersecurity problems exist due to blind spots in their attack surface. Eliminating those blind spots should be your core goal when setting out to discover your attack surface.
One of the biggest contributing factors to these blind spots is scoping. Organizations tend to work within a predefined scope when it comes to discovery – whether that’s within a defined IT infrastructure or a set of IP addresses that the organization uses and wants to protect.
However, the reality is that any would-be attackers out there do not care about your scope. Whether you have a vulnerability in-house, via an external supplier, or in a cloud environment; an attacker will find it and try to misuse it.
On top of this, with modern organizations having so many external dependencies, regulatory bodies are starting to insist that financial services companies look beyond the boundaries of their own networks when analysing risk.
For example, the Digital Operational Resilience of the financial sector (DORA), extends the focus of risk management to cover all external assets of the parties they have relationships with (such as fourth and fifth parties, or parties that you even don't know you have a relationship with), as well as any services and infrastructure that can impact on the organization’s day-to-day resilience.
Taking a zero-scope approach to your attack surface is therefore essential. This means that tracking down the full extent of your attack surface is not something that can be left to human endeavour. Relying on people to trace and discover your connections would be hugely expensive, time consuming, and error prone. So, a prerequisite of effective discovery is automation. AI and algorithmic-based discovery is the only way to uncover the bulk of your attack surface.
Assessment and Prioritization
Monitoring your attack surface is not a one-time, set-and-forget process because your attack surface is not static; it’s constantly evolving and changing. This means you need to be continuously monitoring it for changes, and you need to be alerted when those changes occur, so that you can decide whether or not something needs your attention. This data needs to be dynamic and as close to real-time as you can get.Only once you know what your full attack surface looks like can you really start to analyse the risk types presented to the business. These risks can be extensive and need prioritisation according to the threat presented to the brand. As the discovery process continues, you need an automated risk assessment tool to save time and effort. It will tell you what the most pressing risks are, so you can focus on the mitigating process. Then, even when the discovery process is ongoing, new risks are automatically reported on, and added to right lists. This ensures you stay up-to-date on the actual risks to the organization – removing a lot of the stress from the process for CISOs.
Risk Prevention
There is a flipside to seeing your whole attack surface. Having a comprehensive overview of every risk your organization faces can be terrifying – you are going to uncover a multitude of things you’d never considered. This can leave you facing one big question: “Do I really want to know all of this?” Most CISOs and cybersecurity professionals are already busy with all the things they do know about, so you need to have a way of striping out and solving some of the possibly lower priority but easier to solve risks in your report. This is again where automation can come into play. Automatically categorizing similar risk types throughout your attack surface will save time and effort when reducing risks.
Integration
Finally, it doesn’t matter how much data you have on something; if it’s not actionable it’s ultimately not going to be practical to use. So you need to be able to connect all that data coming from your attack surface monitoring into your existing internal processes and systems (your PSA, ITSM, or ESM tools etc). That way you can build it into your existing cybersecurity structure and minimise extra work.
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.
Untangling the web: Darktrace’s investigation of Scattered Spider’s evolving tactics
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.
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.
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.
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)
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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.
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
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.
![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.](https://cdn.prod.website-files.com/626ff4d25aca2edf4325ff97/68798ca3603c1ac18b3ed3d6_Screenshot%202025-07-17%20at%204.51.51%E2%80%AFPM.png)
