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September 6, 2023

Preparing Security Defenses For the AI Cyber Attack Era

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06
Sep 2023
The threat of AI being used in cyberattacks is growing. Learn how Darktrace is harnessing the power of AI to protect security systems against these attacks.

The last 12 months have been a watershed moment in the public perception and adoption of AI. With the rise of generative AI systems like ChatGPT and Google Bard, AI is becoming more embedded in our everyday lives and there is a lot of hype around what these tools can – or will - do.  

In cyber security, AI is a double-edged sword. Its use by cyber-attackers is still in its infancy, but Darktrace expects that the mass availability of generative AI tools like ChatGPT will significantly enhance attackers’ capabilities by providing better tools to generate and automate human-like attacks. There are three areas where Darktrace sees potential for AI to significantly enhance the capabilities of attackers: increasing the sophistication of low-level threat actors, increasing the speed of attacks through automation and eroding trust among users.

We’ve already started to see some potential indicators of these shifts.

In April, Darktrace revealed a 135% increase in ‘novel social engineering attacks’ – email attacks that show a strong linguistic deviation from other phishing emails – from January to February 2023 [1]. The timing corresponds with the widespread adoption of ChatGPT and suggests the use of generative AI tools is providing an avenue for threat actors to craft more sophisticated and targeted attacks, at speed and scale.

Between May and July this year, our Cyber AI Research Centre observed that multistage payload attacks, in which a malicious email encourages the recipient to follow a series of steps before delivering a payload or attempting to harvest sensitive information, have increased by an average of 59% across Darktrace customers. Nearly 50,000 more of these attacks were detected by Darktrace in July than May, indicating potential use of automation, and the speed of these types of attacks will likely rise as greater automation and AI are adopted and applied by attackers.

In the same period, Darktrace has seen changes in attacks that abuse trust. While VIP impersonation – phishing emails that mimic senior executives – decreased 11%, email account takeover attempts increased by 52% and impersonation of the internal IT team increased by 19% [2]. The changes suggest that as employees have become better attuned to the impersonation of senior executives, attackers are pivoting to impersonating IT teams to launch their attacks. While it’s common for attackers to pivot and adjust their techniques as efficacy declines, generative AI –  particularly deepfakes - has the potential to disrupt this pattern in favor of attackers. Factors like increasing linguistic sophistication and highly realistic voice deep fakes could more easily be deployed to deceive employees.

These early indicators give us a glimpse of a new era of disruption and challenges for cyber security. An era where novel is the new normal.

Darktrace was built for this moment.

Darktrace began ten years ago as an AI Research Centre. We saw that AI could address an existential threat – defending people, businesses and nations from a world of constantly evolving threats. This threat is only poised to grow as AI is increasingly used by attackers. That’s why we became one of the first to apply AI to cyber security and built a completely AI native technology platform aimed at freeing the world of cyber disruption.

We built everything at Darktrace with the same philosophy of using the right AI and the right data for the job.

Most AI today is trained periodically in offline training environments on huge amounts of combined historic training data. You give all that data to the AI, and then after a few days or weeks, you get a static AI model which you push live to serve its role until the next version is ready. This is ideal for tasks like generating imagery or, in cyber security, checking against known attack patterns, but the AI is static – it doesn’t learn or adapt until the next version is pushed live.

Darktrace takes a different and unique approach to nearly everyone else in cyber security. Our distinction lies in the algorithms we use, the data we use AND, most importantly, in how the two interact.  

Instead of taking your data to the AI, we take our AI to your data. Inside every single customer lies a Darktrace AI that is completely unique to them – their OWN data AI pipeline – plugged into their enterprise and self-learning in real time from everything that happens in their digital world –including email, cloud environments, manufacturing and operational systems, and physical locations.

The pace of new threats and the sophistication of the technology, including the use of AI, now outpaces any notion that a week old view of historic cyber threats can fully protect a business – either from the new threats that we’re seeing today from the sudden availability of generative AI tools, or the threats of tomorrow. For example, automated deepfakes where you can’t trust what you’re hearing or seeing, your employees being tricked into being inadvertent insiders, or self-evolving code designed to evade the best of those legacy defenses.

And because the increased use of AI in attacks will mean novel attacks will become the new normal, only Darktrace stands between those attacks succeeding or failing. We’ve seen this before with our technology detecting, and protecting customers against, Log4J, supply chain attacks like SolarWinds, the novel phishing scams we saw during the Covid-19 lockdowns, zero days like the Citrix Netscaler attack, novel ransomware worms such as WannaCry, or sophisticated nation-state attacks like APT35. We didn’t protect businesses because we were looking specifically for these threats, but we found them because every threat, whether known or novel, accidental or malicious, human or AI driven, impacts the customer, its people and its data.

The right AI for the right job

Today we’re on our 6th generation of Darktrace AI and, as we’ve innovated and developed, we’ve built a platform of applied AI techniques and algorithms that utilise Darktrace’s live, tailored knowledge of a business, to defend it alongside human security teams. Our focus has always been on using the right AI and the right data for the job, which is why our software uses:

  • A wide range of our own self-learning methods to understand new information and decide if something never seen before looks suspicious.
  • Real time Bayesian Probabilistic Methods allow models to be efficiently updated and controlled in real time.
  • Generative and applied AI run simulated phishing campaigns, tabletop exercises and realistic drills.
  • Deep-neural networks replicate the thought process of humans.
  • Graph theory understands the incredibly complex relationships between people, systems, organizations and supply chains.
  • Offensive AI techniques such as Generative Adversarial Networks (GANs) help to test and improve our ability to counter AI driven attacks.  
  • Natural language processing and large language models interpret and produce human consumable output.

This complex platform of AI tools and techniques, all sat within a business, focused on the customers’ data, brings a range of advantages in data privacy, explainability and data transfer costs. But its main achievement is the one we set out for ten years ago. It can provide protection that is always on - always learning, able to detect and stop the unusual, the suspicious and the novel – and, ultimately, to protect our customers from it. That’s what we’ve always done and that’s what we will continue to do, regardless of how the landscape shifts.


[1] Based on the average change in email attacks between January and February 2023 detected across Darktrace/Email deployments with control of outliers.

[2] Based on the change in the average number of emails assigned this classification per 10,000 emails on each Darktrace/Email deployment in May versus July 2023 (significantly more than 1,000 deployments in total).

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Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
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January 29, 2025

Bytesize Security: Insider Threats in Google Workspace

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What is an insider threat?

An insider threat is a cyber risk originating from within an organization. These threats can involve actions such as an employee inadvertently clicking on a malicious link (e.g., a phishing email) or an employee with malicious intent conducting data exfiltration for corporate sabotage.

Insiders often exploit their knowledge and access to legitimate corporate tools, presenting a continuous risk to organizations. Defenders must protect their digital estate against threats from both within and outside the organization.

For example, in the summer of 2024, Darktrace / IDENTITY successfully detected a user in a customer environment attempting to steal sensitive data from a trusted Google Workspace service. Despite the use of a legitimate and compliant corporate tool, Darktrace identified anomalies in the user’s behavior that indicated malicious intent.

Attack overview: Insider threat

In June 2024, Darktrace detected unusual activity involving the Software-as-a-Service (SaaS) account of a former employee from a customer organization. This individual, who had recently left the company, was observed downloading a significant amount of data in the form of a “.INDD” file (an Adobe InDesign document typically used to create page layouts [1]) from Google Drive.

While the use of Google Drive and other Google Workspace platforms was not unexpected for this employee, Darktrace identified that the user had logged in from an unfamiliar and suspicious IPv6 address before initiating the download. This anomaly triggered a model alert in Darktrace / IDENTITY, flagging the activity as potentially malicious.

A Model Alert in Darktrace / IDENTITY showing the unusual “.INDD” file being downloaded from Google Workspace.
Figure 1: A Model Alert in Darktrace / IDENTITY showing the unusual “.INDD” file being downloaded from Google Workspace.

Following this detection, the customer reached out to Darktrace’s Security Operations Center (SOC) team via the Security Operations Support service for assistance in triaging and investigating the incident further. Darktrace’s SOC team conducted an in-depth investigation, enabling the customer to identify the exact moment of the file download, as well as the contents of the stolen documents. The customer later confirmed that the downloaded files contained sensitive corporate data, including customer details and payment information, likely intended for reuse or sharing with a new employer.

In this particular instance, Darktrace’s Autonomous Response capability was not active, allowing the malicious insider to successfully exfiltrate the files. If Autonomous Response had been enabled, Darktrace would have immediately acted upon detecting the login from an unusual (in this case 100% rare) location by logging out and disabling the SaaS user. This would have provided the customer with the necessary time to review the activity and verify whether the user was authorized to access their SaaS environments.

Conclusion

Insider threats pose a significant challenge for traditional security tools as they involve internal users who are expected to access SaaS platforms. These insiders have preexisting knowledge of the environment, sensitive data, and how to make their activities appear normal, as seen in this case with the use of Google Workspace. This familiarity allows them to avoid having to use more easily detectable intrusion methods like phishing campaigns.

Darktrace’s anomaly detection capabilities, which focus on identifying unusual activity rather than relying on specific rules and signatures, enable it to effectively detect deviations from a user’s expected behavior. For instance, an unusual login from a new location, as in this example, can be flagged even if the subsequent malicious activity appears innocuous due to the use of a trusted application like Google Drive.

Credit to Vivek Rajan (Cyber Analyst) and Ryan Traill (Analyst Content Lead)

Appendices

Darktrace Model Detections

SaaS / Resource::Unusual Download Of Externally Shared Google Workspace File

References

[1]https://www.adobe.com/creativecloud/file-types/image/vector/indd-file.html

MITRE ATT&CK Mapping

Technqiue – Tactic – ID

Data from Cloud Storage Object – COLLECTION -T1530

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About the author
Vivek Rajan
Cyber Analyst

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January 28, 2025

RansomHub Ransomware: investigación de Darktrace sobre la herramienta más nueva en 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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