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April 1, 2020

How AI Caught APT41 Exploiting Vulnerabilities

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01
Apr 2020
Analyzing how the cyber-criminal group APT41 exploited a zero-day vulnerability, we show how Darktrace’s AI detected and investigated the threat immediately.

Executive summary

  • Darktrace detected several highly targeted attacks in early March, well before any associated signatures had become available. Two weeks later, the attacks were attributed to Chinese threat-actor APT41.
  • APT41 exploited the Zoho ManageEngine zero-day vulnerability CVE-2020-10189. Darktrace automatically detected and reported on the attack in its earliest stages, enabling customers to contain the threat before it could make an impact.
  • The intrusions described here were part of a wider campaign aiming to gain initial access to as many companies as possible during the window of opportunity presented by CVE-2020-10189.
  • The reports generated by Darktrace highlighted and delineated every aspect of the incident in the form of a meaningful security narrative. Even a junior responder could have reviewed this output and acted on this zero-day APT attack in under 5 minutes.

Fighting APT41’s global attack

In early March, Darktrace detected several advanced attacks targeting customers in the US and Europe. A majority of these customers are in the legal sector. The attacks shared the same Techniques, Tools & Procedures (TTPs), targeting public-facing servers and exploiting recent high-impact vulnerabilities. Last week, FireEye attributed this suspicious activity to the Chinese cyber espionage group APT41.

This campaign used the Zoho ManageEngine zero-day vulnerability CVE-2020-10189 to get access to various companies, but little to no follow-up was detected after initial intrusion. This activity indicates a broad-brush campaign to get initial access to as many target companies as possible during the zero-day window of opportunity.

The malicious activity observed by Darktrace took place late on Sunday March 8, 2020 and in the morning of March 9, 2020 (UTC), broadly in line with office hours previously attributed to the Chinese cyber espionage group APT41.

The graphic below shows an exemplary timeline from one of the customers targeted by APT41. The attacks observed in other customer environments are identical.

Timeline of the APT41 attack
Figure 1: A timeline of the attack

Technical analysis

The attack described here centered around the Zoho ManageEngine zero-day vulnerability CVE-2020-10189. Most of the attack appears to have been automated.

We observed the initial intrusion, several follow-up payload downloads, and command and control (C2) traffic. In all cases, the activity was contained before any later steps in the attack lifecycle, such as lateral movement or data exfiltration, were identified.

The below screenshot shows an overview of the key AI Analyst detections reported. Not only did it report on the SSL and HTTP C2 traffic, but it also reported on the payload downloads:

Cyber AI Analyst breaks down the APT41 attack
Figure 2: SSL C2 detection by Cyber AI Analyst
Figure 3: Payload detection by Cyber AI Analyst

Initial compromise

The initial compromise began with the successful exploitation of the Zoho ManageEngine zero-day vulnerability CVE-2020-10189. Following the initial intrusion, the Microsoft BITSAdmin command line tool was used to fetch and install a malicious Batch file, described below:

install.bat (MD5: 7966c2c546b71e800397a67f942858d0) from infrastructure 66.42.98[.]220 on port 12345.

Source: 10.60.50.XX
Destination: 66.42.98[.]220
Destination Port: 12345
Content Type: application/x-msdownload
Protocol: HTTP
Host: 66.42.98[.]220
URI: /test/install.bat
Method: GET
Status Code: 200

Figure 4: Outbound connection fetching batch file

Shortly after the initial compromise, the first stage Cobalt Strike Beacon LOADER was downloaded.

Cobalt Strike Beacon loader screenshot
Figure 5: Detection of the Cobalt Strike Beacon LOADER

Command and Control traffic

Interestingly, TeamViewer activity and the download of Notepad++ was taking place at the same time as the C2 traffic was starting in some of the customer attacks. This indicates APT41 trying to use familiar tools instead of completely ‘Living off the Land’.

Storesyncsvc.dll was a Cobalt Strike Beacon implant (trial-version) which connected to exchange.dumb1[.]com. A successful DNS resolution to 74.82.201[.]8 was identified, which Darktrace discerned as a successful SSL connection to a hostname with Dynamic DNS properties.

Multiple connections to exchange.dumb1[.]com were identified as beaconing to a C2 center. This C2 traffic to the initial Cobalt Strike Beacon was leveraged to download a second stage payload.

Interestingly, TeamViewer activity and the download of Notepad++ was taking place at the same time as the C2 traffic was starting in some of the customer attacks. This indicates APT41 trying to use familiar tools instead of completely ‘Living off the Land’. There is at least high certainty that the use of these two tools can be attributed to this intrusion instead of regular business activity. Notepad++ was not normally used in the target customers’ environments, nor was TeamViewer – in fact, the use of both applications was 100% unusual for the targeted organizations.

Attack tools download

CertUtil.exe, a command line program installed as part of Certificate Services, was then leveraged to connect externally and download the second stage payload.

Detection associated with Meterpreter activity

Figure 6: Darktrace detecting the usage of CertUtil

A few hours after this executable download, the infected device made an outbound HTTP connection requesting the URI /TzGG, which was identified as Meterpreter downloading further shellcode for the Cobalt Strike Beacon.

Figure 7: Detection associated with Meterpreter activity. No lateral movement or significant data exfiltration was observed.

How Cyber AI Analyst reported on the zero-day exploit

Darktrace not only detected this zero-day attack campaign, but Cyber AI Analyst also saved security teams valuable time by investigating disparate security events and generating a report that immediately put them in a position to take action.

The below screenshot shows the AI Analyst incidents reported in one infected environment, over the eight days covering the intrusion period. The first incident on the left represents the APT activity described here. The other five incidents are independent of the APT activity and not as severe.

AI Analyst Security Incidents
Figure 8: The security incidents surfaced by AI Analyst

AI Analyst reported on six incidents in total over the eight-day period. Each AI Analyst incident includes a detailed timeline and summary of the incident, in a concise format that takes an average of two minutes to review. This means that with Cyber AI Analyst, even a non-technical person could have actioned a response to this sophisticated, zero-day incident in less than five minutes.

Conclusion

Without public Indicators of Compromise (IoCs) or any open-source intelligence available, targeted attacks are incredibly difficult to detect. Moreover, even the best detections are useless if they cannot be actioned by a security analyst at an early stage. Too often this occurs because of an overwhelming volume of alerts, or simply because the skills barrier to triage and investigation is too high.

This appears to be a broad campaign to gain initial access to many different companies and sectors. While very sophisticated in nature, the threat sacrificed stealth for speed by targeting many companies at the same time. APT41 wanted to utilize the limited window of opportunity that the Zoho zero-day provided before IT staff starts patching.

Darktrace’s Cyber AI is specifically designed to detect the subtle signs of targeted, unknown attacks at an early stage, without relying on prior knowledge or IoCs. It achieves this by continuously learning the normal patterns of behavior for every user, device, and associated peer group from scratch, and ‘on the job’.

In the face of this zero-day attack campaign, the AI’s ability to (a) detect unknown threats with self-learning AI and (b) augment strained responders with AI-driven investigations and reporting proved crucial. Indeed, it ensured that the attacks were swiftly contained before escalating to the later stages of the attack lifecycle.

Indicators of Compromise

Selection of Darktrace model breaches:

  • Anomalous File / Script from Rare External
  • Anomalous File / EXE from Rare External Location
  • Compromise / SSL to DynDNS
  • Compliance / CertUtil External Connection
  • Anomalous Connection / CertUtil Requesting Non Certificate
  • Anomalous Connection / CertUtil to Rare Destination
  • Anomalous Connection / New User-Agent to IP Without Hostname
  • Device / Initial Breach Chain Compromise
  • Compromise / Slow Beaconing Activity To External Rare
  • Compromise / Beaconing Activity To External Rare
  • Anomalous File / Numeric Exe Download
  • Device / Large Number of Model Breaches
  • Anomalous Server Activity / Rare External from Server
  • Compromise / Sustained TCP Beaconing Activity To Rare Endpoint
  • Compliance / Remote Management Tool On Server

The below screenshot shows Darktrace model breaches occurring together during the compromise of one customer:

Figure 9: Darktrace model breaches occurring together

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.
Author
Max Heinemeyer
Global Field CISO

Max is a cyber security expert with over a decade of experience in the field, specializing in a wide range of areas such as Penetration Testing, Red-Teaming, SIEM and SOC consulting and hunting Advanced Persistent Threat (APT) groups. At Darktrace, Max is closely involved with Darktrace’s strategic customers & prospects. He works with the R&D team at Darktrace, shaping research into new AI innovations and their various defensive and offensive applications. Max’s insights are regularly featured in international media outlets such as the BBC, Forbes and WIRED. Max holds an MSc from the University of Duisburg-Essen and a BSc from the Cooperative State University Stuttgart in International Business Information Systems.

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January 14, 2025

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Ransomware

RansomHub Ransomware: Darktrace’s Investigation of the Newest Tool in ShadowSyndicate's Arsenal

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What is ShadowSyndicate?

ShadowSyndicate, also known as Infra Storm, is a threat actor reportedly active since July 2022, working with various ransomware groups and affiliates of ransomware programs, such as Quantum, Nokoyawa, and ALPHV. This threat actor employs tools like Cobalt Strike, Sliver, IcedID, and Matanbuchus malware in its attacks. ShadowSyndicate utilizes the same SSH fingerprint (1ca4cbac895fc3bd12417b77fc6ed31d) on many of their servers—85 as of September 2023. At least 52 of these servers have been linked to the Cobalt Strike command and control (C2) framework [1].

What is RansomHub?

First observed following the FBI's takedown of ALPHV/BlackCat in December 2023, RansomHub quickly gained notoriety as a Ransomware-as-a-Service (RaaS) operator. RansomHub capitalized on the law enforcement’s disruption of the LockBit group’s operations in February 2024 to market themselves to potential affiliates who had previously relied on LockBit’s encryptors. RansomHub's success can be largely attributed to their aggressive recruitment on underground forums, leading to the absorption of ex-ALPHV and ex-LockBit affiliates. They were one of the most active ransomware operators in 2024, with approximately 500 victims reported since February, according to their Dedicated Leak Site (DLS) [2].

ShadowSyndicate and RansomHub

External researchers have reported that ShadowSyndicate had as many as seven different ransomware families in their arsenal between July 2022, and September 2023. Now, ShadowSyndicate appears to have added RansomHub’s their formidable stockpile, becoming an affiliate of the RaaS provider [1].

Darktrace’s analysis of ShadowSyndicate across its customer base indicates that the group has been leveraging RansomHub ransomware in multiple attacks in September and October 2024. ShadowSyndicate likely shifted to using RansomHub due to the lucrative rates offered by this RaaS provider, with affiliates receiving up to 90% of the ransom—significantly higher than the general market rate of 70-80% [3].

In many instances where encryption was observed, ransom notes with the naming pattern “README_[a-zA-Z0-9]{6}.txt” were written to affected devices. The content of these ransom notes threatened to release stolen confidential data via RansomHub’s DLS unless a ransom was paid. During these attacks, data exfiltration activity to external endpoints using the SSH protocol was observed. The external endpoints to which the data was transferred were found to coincide with servers previously associated with ShadowSyndicate activity.

Darktrace’s coverage of ShadowSyndicate and RansomHub

Darktrace’s Threat Research team identified high-confidence indicators of compromise (IoCs) linked to the ShadowSyndicate group deploying RansomHub. The investigation revealed four separate incidents impacting Darktrace customers across various sectors, including education, manufacturing, and social services. In the investigated cases, multiple stages of the kill chain were observed, starting with initial internal reconnaissance and leading to eventual file encryption and data exfiltration.

Attack Overview

Timeline attack overview of ransomhub ransomware

Internal Reconnaissance

The first observed stage of ShadowSyndicate attacks involved devices making multiple internal connection attempts to other internal devices over key ports, suggesting network scanning and enumeration activity. In this initial phase of the attack, the threat actor gathers critical details and information by scanning the network for open ports that might be potentially exploitable. In cases observed by Darktrace affected devices were typically seen attempting to connect to other internal locations over TCP ports including 22, 445 and 3389.

C2 Communication and Data Exfiltration

In most of the RansomHub cases investigated by Darktrace, unusual connections to endpoints associated with Splashtop, a remote desktop access software, were observed briefly before outbound SSH connections were identified.

Following this, Darktrace detected outbound SSH connections to the external IP address 46.161.27[.]151 using WinSCP, an open-source SSH client for Windows used for secure file transfer. The Cybersecurity and Infrastructure Security Agency (CISA) identified this IP address as malicious and associated it with ShadowSyndicate’s C2 infrastructure [4]. During connections to this IP, multiple gigabytes of data were exfiltrated from customer networks via SSH.

Data exfiltration attempts were consistent across investigated cases; however, the method of egress varied from one attack to another, as one would expect with a RaaS strain being employed by different affiliates. In addition to transfers to ShadowSyndicate’s infrastructure, threat actors were also observed transferring data to the cloud storage and file transfer service, MEGA, via HTTP connections using the ‘rclone’ user agent – a command-line program used to manage files on cloud storage. In another case, data exfiltration activity occurred over port 443, utilizing SSL connections.

Lateral Movement

In investigated incidents, lateral movement activity began shortly after C2 communications were established. In one case, Darktrace identified the unusual use of a new administrative credential which was quickly followed up with multiple suspicious executable file writes to other internal devices on the network.

The filenames for this executable followed the regex naming convention “[a-zA-Z]{6}.exe”, with two observed examples being “bWqQUx.exe” and “sdtMfs.exe”.

Cyber AI Analyst Investigation Process for the SMB Writes of Suspicious Files to Multiple Devices' incident.
Figure 1: Cyber AI Analyst Investigation Process for the SMB Writes of Suspicious Files to Multiple Devices' incident.

Additionally, script files such as “Defeat-Defender2.bat”, “Share.bat”, and “def.bat” were also seen written over SMB, suggesting that threat actors were trying to evade network defenses and detection by antivirus software like Microsoft Defender.

File Encryption

Among the three cases where file encryption activity was observed, file names were changed by adding an extension following the regex format “.[a-zA-Z0-9]{6}”. Ransom notes with a similar naming convention, “README_[a-zA-Z0-9]{6}.txt”, were written to each share. While the content of the ransom notes differed slightly in each case, most contained similar text. Clear indicators in the body of the ransom notes pointed to the use of RansomHub ransomware in these attacks. As is increasingly the case, threat actors employed double extortion tactics, threatening to leak confidential data if the ransom was not paid. Like most ransomware, RansomHub included TOR site links for communication between its "customer service team" and the target.

Figure 2: The graph shows the behavior of a device with encryption activity, using the “SMB Sustained Mimetype Conversion” and “Unusual Activity Events” metrics over three weeks.

Since Darktrace’s Autonomous Response capability was not enabled during the compromise, the ransomware attack succeeded in its objective. However, Darktrace’s Cyber AI Analyst provided comprehensive coverage of the kill chain, enabling the customer to quickly identify affected devices and initiate remediation.

Figure 3: Cyber AI Analyst panel showing the critical incidents of the affected device from one of the cases investigated.

In lieu of Autonomous Response being active on the networks, Darktrace was able to suggest a variety of manual response actions intended to contain the compromise and prevent further malicious activity. Had Autonomous Response been enabled at the time of the attack, these actions would have been quickly applied without any human interaction, potentially halting the ransomware attack earlier in the kill chain.

Figure 4: A list of suggested Autonomous Response actions on the affected devices."

Conclusion

The Darktrace Threat Research team has noted a surge in attacks by the ShadowSyndicate group using RansomHub’s RaaS of late. RaaS has become increasingly popular across the threat landscape due to its ease of access to malware and script execution. As more individual threat actors adopt RaaS, security teams are struggling to defend against the increasing number of opportunistic attacks.

For customers subscribed to Darktrace’s Security Operations Center (SOC) services, the Analyst team promptly investigated detections of the aforementioned unusual and anomalous activities in the initial infection phases. Multiple alerts were raised via Darktrace’s Managed Threat Detection to warn customers of active ransomware incidents. By emphasizing anomaly-based detection and response, Darktrace can effectively identify devices affected by ransomware and take action against emerging activity, minimizing disruption and impact on customer networks.

Credit to Kwa Qing Hong (Senior Cyber Analyst and Deputy Analyst Team Lead, Singapore) and Signe Zahark (Principal Cyber Analyst, Japan)

Appendices

Darktrace Model Detections

Antigena Models / Autonomous Response:

Antigena / Network / Insider Threat / Antigena Network Scan Block

Antigena / Network / Insider Threat / Antigena SMB Enumeration Block

Antigena / Network / Insider Threat / Antigena Internal Anomalous File Activity

Antigena / Network / Insider Threat / Antigena Large Data Volume Outbound Block

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

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

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

Antigena / Network / Significant Anomaly / Antigena Significant Server Anomaly Block

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

Antigena / Network / External Threat / Antigena Suspicious Activity Block

Antigena / Network / External Threat / Antigena Suspicious File Pattern of Life Block

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


Network Reconnaissance:

Device / Network Scan

Device / ICMP Address Scan

Device / RDP Scan
Device / Anomalous LDAP Root Searches
Anomalous Connection / SMB Enumeration
Device / Spike in LDAP Activity

C2:

Enhanced Monitoring - Device / Lateral Movement and C2 Activity

Enhanced Monitoring - Device / Initial Breach Chain Compromise

Enhanced Monitoring - Compromise / Suspicious File and C2

Compliance / Remote Management Tool On Server

Anomalous Connection / Outbound SSH to Unusual Port


External Data Transfer:

Enhanced Monitoring - Unusual Activity / Enhanced Unusual External Data Transfer

Unusual Activity / Unusual External Data Transfer

Anomalous Connection / Data Sent to Rare Domain

Unusual Activity / Unusual External Data to New Endpoint

Compliance / SSH to Rare External Destination

Anomalous Connection / Application Protocol on Uncommon Port

Enhanced Monitoring - Anomalous File / Numeric File Download

Anomalous File / New User Agent Followed By Numeric File Download

Anomalous Server Activity / Outgoing from Server

Device / Large Number of Connections to New Endpoints

Anomalous Connection / Multiple HTTP POSTs to Rare Hostname

Anomalous Connection / Uncommon 1 GiB Outbound

Lateral Movement:

User / New Admin Credentials on Server

Anomalous Connection / New or Uncommon Service Control

Anomalous Connection / High Volume of New or Uncommon Service Control

Anomalous File / Internal / Executable Uploaded to DC

Anomalous Connection / Suspicious Activity On High Risk Device

File Encryption:

Compliance / SMB Drive Write

Anomalous File / Internal / Additional Extension Appended to SMB File

Compromise / Ransomware / Possible Ransom Note Write

Anomalous Connection / Suspicious Read Write Ratio

List of Indicators of Compromise (IoCs)

IoC - Type - Description + Confidence

83.97.73[.]198 - IP - Data exfiltration endpoint

108.181.182[.]143 - IP - Data exfiltration endpoint

46.161.27[.]151 - IP - Data exfiltration endpoint

185.65.212[.]164 - IP - Data exfiltration endpoint

66[.]203.125.21 - IP - MEGA endpoint used for data exfiltration

89[.]44.168.207 - IP - MEGA endpoint used for data exfiltration

185[.]206.24.31 - IP - MEGA endpoint used for data exfiltration

31[.]216.148.33 - IP - MEGA endpoint used for data exfiltration

104.226.39[.]18 - IP - C2 endpoint

103.253.40[.]87 - IP - C2 endpoint

*.relay.splashtop[.]com - Hostname - C2 & data exfiltration endpoint

gfs***n***.userstorage.mega[.]co.nz - Hostname - MEGA endpoint used for data exfiltration

w.api.mega[.]co.nz - Hostname - MEGA endpoint used for data exfiltration

ams-rb9a-ss.ams.efscloud[.]net - Hostname - Data exfiltration endpoint

MITRE ATT&CK Mapping

Tactic - Technqiue

RECONNAISSANCE – T1592.004 Client Configurations

RECONNAISSANCE – T1590.005 IP Addresses

RECONNAISSANCE – T1595.001 Scanning IP Blocks

RECONNAISSANCE – T1595.002 Vulnerability Scanning

DISCOVERY – T1046 Network Service Scanning

DISCOVERY – T1018 Remote System Discovery

DISCOVERY – T1083 File and Directory Discovery
INITIAL ACCESS - T1189 Drive-by Compromise

INITIAL ACCESS - T1190 Exploit Public-Facing Application

COMMAND AND CONTROL - T1001 Data Obfuscation

COMMAND AND CONTROL - T1071 Application Layer Protocol

COMMAND AND CONTROL - T1071.001 Web Protocols

COMMAND AND CONTROL - T1573.001 Symmetric Cryptography

COMMAND AND CONTROL - T1571 Non-Standard Port

DEFENSE EVASION – T1078 Valid Accounts

DEFENSE EVASION – T1550.002 Pass the Hash

LATERAL MOVEMENT - T1021.004 SSH

LATERAL MOVEMENT – T1080 Taint Shared Content

LATERAL MOVEMENT – T1570 Lateral Tool Transfer

LATERAL MOVEMENT – T1021.002 SMB/Windows Admin Shares

COLLECTION - T1185 Man in the Browser

EXFILTRATION - T1041 Exfiltration Over C2 Channel

EXFILTRATION - T1567.002 Exfiltration to Cloud Storage

EXFILTRATION - T1029 Scheduled Transfer

IMPACT – T1486 Data Encrypted for Impact

References

1.     https://www.group-ib.com/blog/shadowsyndicate-raas/

2.     https://www.techtarget.com/searchsecurity/news/366617096/ESET-RansomHub-most-active-ransomware-group-in-H2-2024

3.     https://cyberint.com/blog/research/ransomhub-the-new-kid-on-the-block-to-know/

4.     https://www.cisa.gov/sites/default/files/2024-05/AA24-131A.stix_.xml

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About the author
Qing Hong Kwa
Senior Cyber Analyst and Deputy Analyst Team Lead, Singapore

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January 14, 2025

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Email

Why AI-powered Email Protection Became Essential for this Global Financial Services Leader

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When agile cyber-attackers don’t stop, but pivot  

When he first joined this leading financial services provider, it was clear to the CISO that email security needed to be a top priority. The organization provides transfer services to millions of consumers via a network of thousands of agent locations across the US. Those agents are connected to hundreds of thousands of global payers to complete consumer transfers, ranging from leading financial institutions to small local businesses.

With this vast network of agents and payers, the provider relies on email as its primary communications channel. Transmitting billions of dollars every year, the organization is a prime target for cyber criminals looking to steal credentials, financial assets, and sensitive data.

Vulnerable to attacks with gaps in email security and visibility

The CISO discovered that employees were under constant attack by phishing emails impersonating his company’s own executives. The business email compromise (BEC) attacks were designed to deceive employees into sharing credentials or clicking on malicious links.

Upon discovering that their Microsoft 365 tenant lacked secure configuration, the CISO implemented necessary changes to strengthen the service, including enabling authentication controls. While his efforts significantly reduced BEC attacks, cyber criminals changed their tactics, sending employees malicious phishing emails from seemingly valid email accounts from trusted domains like Google and Yahoo. The emails passed through the organization’s native email filters without detection.

The CISO also sought to strengthen defenses against third-party supply chain attacks that could originate with any of the hundreds of thousands of third-party agents and payers the company works with around the world. While the larger institutions typically have sophisticated email security strategies in place, the smaller businesses may lack the cybersecurity expertise needed to effectively secure and manage their data, putting the organization at risk.

While the CISO knew the company was vulnerable to phishing and third-party threats, he didn’t have visibility across the flow of email. Without access to key metrics and valuable data, he couldn’t get the crucial insights needed to quickly identify possible threats and adjust security protocols.  

Skilled analysts bogged down with low-level tasks

Like many enterprise organizations, this leading financial services provider relied on a crew of highly skilled analysts to respond to alerts and analyze and triage emails most of their workday. “That shouldn’t be how we operate,” said the CISO. “My role and the role of my staff should be to focus on more strategic projects, support the business, and work on important new product development.”

Balancing user experience with mitigating threats

Enabling greater email security measures without negatively impacting the business, user experience, and customer satisfaction was a daunting challenge the CISO and his security team faced. Imposing restrictions that are too stringent could restrict communication, delay the delivery of important messages, or block legitimate emails – potentially slowing down money transfers, frustrating customers, affecting employee productivity, and impacting revenue. However, maintaining controls that are too permissive could result in serious outcomes like data theft, financial fraud, operational disruption, compliance penalties, and customer attrition.  

Self-Learning AI is a game changer

After conducting a thorough POC with several modern security solution providers, this global financial services provider chose the Darktrace / EMAIL an AI-driven email security platform. The CISO said they chose the solution for two key reasons:

First, Darktrace / EMAIL offers modern capabilities

  • Self-Learning AI uses business data to recognize anomalies in communication patterns and user behavior to stop known and unknown threats
  • Secures the organization’s entire mailflow across all inbound, outbound, and lateral email
  • Protects against account takeover attacks by identifying subtle anomalies in cloud SaaS
  • Catches sophisticated threats like impersonations, session token misuse, adversary-in-the-middle attacks, credential theft, and data exfiltration

Second, they pointed to Darktrace’s experience, innovation, and expertise

  • Deep cybersecurity and industry knowledge
  • Demonstrated customers successes worldwide
  • At the forefront of innovation and research, establishing new thresholds in cybersecurity, with technology advances backed by over 200 patents and pending applications

Moreover, and most importantly, this organization trusted Darktrace to deliver on its promises.  And according to the CISO, that’s just what happened.

Significantly reduced phishing threats and business risk

Since implementing Darktrace / EMAIL, the threat posed by BEC attacks has dropped sharply. “Phishing is not an issue that concerns me anymore. I estimate we are now identifying and blocking more than 85% of threats our previous solution was missing,” said the CISO. The biggest factor contributing to this success? The power of AI.

With Darktrace / EMAIL, this leadingglobal financial services provider is identifying and blocking more than 85% ofthe phishing email threats its previous solution missed.

AI wasn’t originally on the financial service provider’s list of criteria. But after seeing AI in action and understanding its potential to vastly scale their detection and response capabilities–without adding headcount, the CISO determined AI wasn’t an option but an imperative. “AI is essential when it comes to email security, it’s an absolute necessity,” he said.  

Darktrace / EMAIL’s Self-Learning AI is uniquely powerful because it learns the content and context of every internal and external user and can spot the subtle differences in behavioral patterns that point to possible social engineering attacks. Through patented behavioral anomaly detection, Darktrace / EMAIL continuously learns about the organization’s business and users, based on its own operations and data, adjusting security protocols accordingly.  

For example, when clients are transferring large amounts of money, they are required to send photos of their driver’s licenses and passports via email to the organization for verification – accounting for a large percentage of its’ inbound email. Darktrace / EMAIL recognizes that it’s normal for customers to send this sensitive information, and it also knows that it’s not normal for that same sensitive information to leave the organization via outbound mail. In addition, Darktrace identifies patterns in user behavior, including who employees communicate with and what kind of information they share. When user behavior falls outside of established norms, such as an email sent from the CFO to employees the CEO would not typically communicate with, Darktrace can take the appropriate action to remove the threat.  

“After the implementation, we gave the solution two weeks to ingest our data and learn the specifics of our business. After that, it was perfect, just amazing,” said the CISO.  

Boosted team productivity and elevated value to the business

With Darktrace / EMAIL, the organization has successfully scaled its detection and response efforts without scaling personnel. The security team has reduced the number of emails requiring manual investigation by 90%. And because analysts now have the benefit of Darktrace / EMAIL’s analytics and reporting, the investigation process is much easier and faster. “The impact of this solution on my team has been very positive,” said the CISO. “Darktrace / EMAIL essentially manages itself, freeing up time for our skilled analysts–and for myself–to focus on more important projects.”  

The security team has scaled its detection and response efforts without scaling personnel,reducing the number of emails it manually investigates by 90%

Increased visibility delivers business-critical insights

You can’t control what you can’t see, and with zero visibility into critical data and metrics, this financial services provider was at a serious disadvantage. That has all changed. “Something that I love about Darktrace / EMAIL is the visibility that it provides into key metrics from a single dashboard. We can now understand the behavior of our email flow and data traffic and can make insight-driven decisions to continuously optimize our email security. It’s awesome,” said the CISO.  

An efficient user interface also improves productivity and reduces mean time to action by enabling teams to easily visualize key data points and quickly evaluate what actions need to be taken. Darktrace / EMAIL was developed with that experience in mind, allowing users to access data and take quick action without having to constantly log into the solution.

Keeping the business focused on cybersecurity

The leadership of this global organization takes information security very seriously, understanding that cyber-attacks aren’t just an IT problem but a business problem. When it came to evaluating Darktrace, the CISO said numerous stakeholders were involved including C-level executives, infrastructure, and IT, which operates separately from information security. The CISO initially identified the need, conducted the market research, engaged the target vendors, and then brought the other decision makers into the process for the solution evaluation and final decision. “Our IT group, infrastructure team, CTO and CEO are all involved when it comes to making major cybersecurity investments. We always try to make these decisions jointly to ensure we are taking everything into consideration.”

The organization has reached a higher level of maturity when it comes to email cybersecurity. The ability to automate routine email detection and investigation tasks has both strengthened the organization’s cyber resilience and enabled the CISO and his team to contribute more to the business. His advice for other IT leaders facing the same email security and visibility challenges he once experienced: “For those companies that need greater insight and control over their email but have limited resources and people, AI is the answer.”  

Darktrace / Email solution brief screenshot

Secure Your Inbox with Cutting-Edge AI Email Protection

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

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