Phishing Attacks Surge Over 600% in the Buildup to Black Friday
Black Friday and Cyber Monday are prime targets for cyber-attacks, as consumer spending rises and threat actors flock to take advantage. Darktrace analysis reveals a surge in retail cyber scams at the opening of the peak 2024 shopping period, and the top brands that scammers love to impersonate. Plus, don’t forget to check out our top tips for holiday-proofing your SOC before you clock off for the festive season.
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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.
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04
Dec 2024
Defenders are accustomed now to an uptick in cyber-attacks around the holiday period. The festive shopping season creates ideal conditions for cybercriminals. Consumers are inundated with time-sensitive deals, while retailers handle record-breaking transaction volumes at speed. This environment makes it harder than ever to identify suspicious activity.
An investigation conducted by Darktrace’s global analyst team revealed that Christmas-themed phishing attacks leapt 327%1 around the world and Black Friday and Cyber Monday themed phishing attacks soared to 692% last week compared to the beginning of November2 (4th - 9th November), as threat actors seek to take advantage of the busy holiday shopping period.
The United States retail sector saw the most marked increase in threat actors crafting convincing emails purporting to be from well-known brands, mimicking promotional emails. Attacks designed to look like they came from major brands including Walmart – which was easily the most mimicked US brand – Macy’s, Target, Old Navy, and Best Buy3 increased by more than 2000% during peak shopping periods.
Darktrace analysis also highlighted a redistribution of scammers’ resources to take advantage of the festive shopping season, moving from targeting businesses to consumers. The impersonation of major consumer brands, dominated by Amazon and PayPal4, increased by 92% globally between analyzed periods, while the spoofing of workplace-focused brands, like Adobe, Zoom and LinkedIn, decreased by 9%.
Major retail brands invest heavily in safeguarding themselves and their customers from scams and cyberattacks, particularly during the holiday season. However, phishing and website spoofing occur outside the retailers' legitimate infrastructure and security controls, making it difficult to catch and prevent every instance due to their sheer volume. While advancements like AI are helping security teams narrow the gap, brand impersonation remains a persistent challenge.
Multiple attack methods exploit trust during holiday rush
Darktrace’s findings demonstrate some of the most common brand spoofing strategies used by attackers during the holiday season:
Domain spoofing, which sees attackers create near perfect replicas of retail websites, complete with lookalike domain names and branding, to trick consumers into handing over personal and payment details.
Brand spoofing, where attackers send a phishing email designed to look like a favorite retailer, enticing their target to click a link for a discount, when in fact the link downloads malware to their device.
Multi-stage attacks which combine these tactics into a single attack: brand spoofing emails lead unsuspecting shoppers directly to domain spoofed websites that harvest login or payment details, creating a seamless deception that hands personal and financial data directly to attackers. This coordinated approach exploits the chaos of holiday sales, when shoppers are primed to expect high volumes of retail emails and website traffic promoting significant savings.
A spike in cyber-criminal activity which extends beyond email
While email often serves as the front door to an organization and the initial avenue of attack, Darktrace frequently observes a surge in cyber-attacks during public holidays5. These “off-peak” attacks exploit common organizational practices and human vulnerabilities with greater ease.
When staff numbers are reduced, and employees mentally and physically disconnect from work, the speed of detection and response has the potential to slow. This creates opportunities for threat actors to infiltrate undetected. Without real-time autonomous systems in place, such attacks can have a far more severe impact on an organization’s ability to respond and recover effectively.
Festive cheer: giving your SOC team the break they deserve
Staff burnout is increasingly top of mind, with 74% of cybersecurity leaders reporting that they’ve had employees resign due to stress7. And the numbers stack up – almost 60% of security analysts report feeling burnt out, and many are choosing to leave their jobs and even security altogether.8
At a human level, the holiday season should be a time of relaxation and merriment rather than anxiety. For SOC leaders, giving teams time to prioritize recharging during the holidays is crucial for sustaining long-term resilience and productivity, balanced with the importance of maintaining rigorous defenses with a reduced workforce.
So… how can cybersecurity leaders ensure peace of mind during the holidays?
Step 1: Cover yourself from every angle. It’s no longer enough for your email solution to only catch known threats. Security leaders need to invest in multi-layered email defenses that can combat novel and advanced attacks – such as the multi-stage brand personation attacks that lead shoppers to domain-spoofed websites.
Darktrace / EMAIL – the fastest growing email security solution – has been proven to detect up to 56% more threats than other email solutions.9 It is uniquely capable of catching novel attacks on the first encounter, rather than waiting the 13 days it takes for other solutions to take action10 – by which time your decorations might be coming down, along with your business.
Step 2: Avoid an overwhelming deluge of alerts raining (or snowing) down on your L1 SOC analysts. Lining up people to manage the grunt work over the holidays is an easy pattern to fall into, but consider technology that can automate that initial triage. For example, Darktrace’s Cyber AI Analyst automatically investigates every alert detected by Darktrace’s core real-time detection engine. It does an additional layer of AI analysis – establishing whether an alert is unusual but benign, or part of a more serious security incident. Rather than looking at hundreds of alerts, your team is presented with just a handful of overall incidents. They can use that new free time to do more strategic work, or take some much-needed time off.
Step 3: Make sure someone – or something – is keeping guard in those super off-peak hours. Enter Autonomous Response. Because it knows what normal looks like for your business it can take action to stop and contain only the unusual and threatening activity. Even if it doesn’t eliminate the threat entirely, it can buy your security team time and space, allowing them to enjoy their holiday in peace.
With Black Friday over and the festive shopping period looming, businesses should act now to protect their brand and ensure they have the cybersecurity measures are in place to enjoy the gift of a stress-free holiday season.
[1] Based on analysis of 626 customer deployments and attempted phishing emails mentioning Christmas that were detected by Darktrace / EMAIL.
[2] Emails in the analysis mentioning ‘Black Friday’ or ‘Cyber Monday’.
[3] Walmart, Target, Best Buy, Macy's, Old Navy, 1800-Flowers
[4] Amazon, eBay, Netflix, Alibaba, Paypal, Apple
[5] In 2021, Darktrace observed a 70% average increase in attempted ransomware attacks in November and December compared to January and February. (Darktrace Press Release, 2021)
[9] 56% of malicious phishing emails detected and analyzed across Darktrace / EMAIL customer deployments from December 2023 – July 2024 passed through all existing security layers. (Darktrace Half Year Report 2024)
[10] 13 days mean average of phishing payloads active in the wild between the response of Darktrace / EMAIL compared to the earliest of 16 independent feeds submitted by other email security technologies. (Darktrace Press Release, 2023)
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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.
Darktrace Collaborates with Microsoft: Unifying Email Security with a Shared Vision
Darktrace and Microsoft have joined forces to enhance email security through a new integration, unifying threat response and quarantine capabilities. This collaboration strengthens defenses and streamlines visibility for security teams, reflecting a shared vision for proactive cyber protection.
Why attack-centric approaches to email security can’t cope with modern threats
Despite evolving email threats, many organizations still rely on SEGs or outdated, attack-focused methods. These approaches can’t counter advanced, AI-driven attacks. The solution? Business-centric email security that understands users and inbox behavior, not just threats.
Evaluating Email Security: How to Select the Best Solution for Your Organization
In today’s saturated market for email security, it can be difficult to cut through the noise of AI hype and vendor claims. CISOs should be using a structured evaluation framework to support informed, objective comparisons of different vendors – to allow them to make the best decision for their organization.
Defending the Cloud: Stopping Cyber Threats in Azure and AWS with Darktrace
Real-world intrusions across Azure and AWS
As organizations pursue greater scalability and flexibility, cloud platforms like Microsoft Azure and Amazon Web Services (AWS) have become essential for enabling remote operations and digitalizing corporate environments. However, this shift introduces a new set of security risks, including expanding attack surfaces, misconfigurations, and compromised credentials frequently exploited by threat actors.
This blog dives into three instances of compromise within a Darktrace customer’s Azure and AWS environment which Darktrace.
The first incident took place in early 2024 and involved an attacker compromising a legitimate user account to gain unauthorized access to a customer’s Azure environment.
The other two incidents, taking place in February and March 2025, targeted AWS environments. In these cases, threat actors exfiltrated corporate data, and in one instance, was able to detonate ransomware in a customer’s environment.
Case 1 - Microsoft Azure
Figure 1: Simplified timeline of the attack on a customer’s Azure environment.
In early 2024, Darktrace identified a cloud compromise on the Azure cloud environment of a customer in the Europe, the Middle East and Africa (EMEA) region.
Initial access
In this case, a threat actor gained access to the customer’s cloud environment after stealing access tokens and creating a rogue virtual machine (VM). The malicious actor was found to have stolen access tokens belonging to a third-party external consultant’s account after downloading cracked software.
With these stolen tokens, the attacker was able to authenticate to the customer’s Azure environment and successfully modified a security rule to allow inbound SSH traffic from a specific IP range (i.e., securityRules/AllowCidrBlockSSHInbound). This was likely performed to ensure persistent access to internal cloud resources.
Detection and investigation of the threat
Darktrace / IDENTITY recognized that this activity was highly unusual, triggering the “Repeated Unusual SaaS Resource Creation” alert.
Cyber AI Analyst launched an autonomous investigation into additional suspicious cloud activities occurring around the same time from the same unusual location, correlating the individual events into a broader account hijack incident.
Figure 2: Cyber AI Analyst’s investigation into unusual cloud activity performed by the compromised account.
Figure 3: Surrounding resource creation events highlighted by Cyber AI Analyst.
Figure 4: Surrounding resource creation events highlighted by Cyber AI Analyst.
“Create resource service limit” events typically indicate the creation or modification of service limits (i.e., quotas) for a specific Azure resource type within a region. Meanwhile, “Registers the Capacity Resource Provider” events refer to the registration of the Microsoft Capacity resource provider within an Azure subscription, responsible for managing capacity-related resources, particularly those related to reservations and service limits. These events suggest that the threat actor was looking to create new cloud resources within the environment.
Around ten minutes later, Darktrace detected the threat actor creating or modifying an Azure disk associated with a virtual machine (VM), suggesting an attempt to create a rogue VM within the environment.
Threat actors can leverage such rogue VMs to hijack computing resources (e.g., by running cryptomining malware), maintain persistent access, move laterally within the cloud environment, communicate with command-and-control (C2) infrastructure, and stealthily deliver and deploy malware.
Persistence
Several weeks later, the compromised account was observed sending an invitation to collaborate to an external free mail (Google Mail) address.
Darktrace deemed this activity as highly anomalous, triggering a compliance alert for the customer to review and investigate further.
The next day, the threat actor further registered new multi-factor authentication (MFA) information. These actions were likely intended to maintain access to the compromised user account. The customer later confirmed this activity by reviewing the corresponding event logs within Darktrace.
Case 2 – Amazon Web Services
Figure 5: Simplified timeline of the attack on a customer’s AWS environment
In February 2025, another cloud-based compromised was observed on a UK-based customer subscribed to Darktrace’s Managed Detection and Response (MDR) service.
How the attacker gained access
The threat actor was observed leveraging likely previously compromised credential to access several AWS instances within customer’s Private Cloud environment and collecting and exfiltrating data, likely with the intention of deploying ransomware and holding the data for ransom.
Darktrace alerting to malicious activity
This observed activity triggered a number of alerts in Darktrace, including several high-priority Enhanced Monitoring alerts, which were promptly investigated by Darktrace’s Security Operations Centre (SOC) and raised to the customer’s security team.
The earliest signs of attack observed by Darktrace involved the use of two likely compromised credentials to connect to the customer’s Virtual Private Network (VPN) environment.
Internal reconnaissance
Once inside, the threat actor performed internal reconnaissance activities and staged the Rclone tool “ProgramData\rclone-v1.69.0-windows-amd64.zip”, a command-line program to sync files and directories to and from different cloud storage providers, to an AWS instance whose hostname is associated with a public key infrastructure (PKI) service.
The threat actor was further observed accessing and downloading multiple files hosted on an AWS file server instance, notably finance and investment-related files. This likely represented data gathering prior to exfiltration.
Shortly after, the PKI-related EC2 instance started making SSH connections with the Rclone SSH client “SSH-2.0-rclone/v1.69.0” to a RockHoster Virtual Private Server (VPS) endpoint (193.242.184[.]178), suggesting the threat actor was exfiltrating the gathered data using the Rclone utility they had previously installed. The PKI instance continued to make repeated SSH connections attempts to transfer data to this external destination.
Darktrace’s Autonomous Response
In response to this activity, Darktrace’s Autonomous Response capability intervened, blocking unusual external connectivity to the C2 server via SSH, effectively stopping the exfiltration of data.
This activity was further investigated by Darktrace’s SOC analysts as part of the MDR service. The team elected to extend the autonomously applied actions to ensure the compromise remained contained until the customer could fully remediate the incident.
Continued reconissance
Around the same time, the threat actor continued to conduct network scans using the Nmap tool, operating from both a separate AWS domain controller instance and a newly joined device on the network. These actions were accompanied by further internal data gathering activities, with around 5 GB of data downloaded from an AWS file server.
The two devices involved in reconnaissance activities were investigated and actioned by Darktrace SOC analysts after additional Enhanced Monitoring alerts had triggered.
Lateral movement attempts via RDP connections
Unusual internal RDP connections to a likely AWS printer instance indicated that the threat actor was looking to strengthen their foothold within the environment and/or attempting to pivot to other devices, likely in response to being hindered by Autonomous Response actions.
This triggered multiple scanning, internal data transfer and unusual RDP alerts in Darktrace, as well as additional Autonomous Response actions to block the suspicious activity.
Suspicious outbound SSH communication to known threat infrastructure
Darktrace subsequently observed the AWS printer instance initiating SSH communication with a rare external endpoint associated with the web hosting and VPS provider Host Department (67.217.57[.]252), suggesting that the threat actor was attempting to exfiltrate data to an alternative endpoint after connections to the original destination had been blocked.
Further investigation using open-source intelligence (OSINT) revealed that this IP address had previously been observed in connection with SSH-based data exfiltration activity during an Akira ransomware intrusion [1].
Once again, connections to this IP were blocked by Darktrace’s Autonomous Response and subsequently these blocks were extended by Darktrace’s SOC team.
The above behavior generated multiple Enhanced Monitoring alerts that were investigated by Darktrace SOC analysts as part of the Managed Threat Detection service.
Figure 5: Enhanced Monitoring alerts investigated by SOC analysts as part of the Managed Detection and Response service.
Final containment and collaborative response
Upon investigating the unusual scanning activity, outbound SSH connections, and internal data transfers, Darktrace analysts extended the Autonomous Response actions previously triggered on the compromised devices.
As the threat actor was leveraging these systems for data exfiltration, all outgoing traffic from the affected devices was blocked for an additional 24 hours to provide the customer’s security team with time to investigate and remediate the compromise.
Additional investigative support was provided by Darktrace analysts through the Security Operations Service, after the customer's opened of a ticket related to the unfolding incident.
Figure 8: Simplified timeline of the attack
Around the same time of the compromise in Case 2, Darktrace observed a similar incident on the cloud environment of a different customer.
Initial access
On this occasion, the threat actor appeared to have gained entry into the AWS-based Virtual Private Cloud (VPC) networkvia a SonicWall SMA 500v EC2 instance allowing inbound traffic on any port.
The instance received HTTPS connections from three rare Vultr VPS endpoints (i.e., 45.32.205[.]52, 207.246.74[.]166, 45.32.90[.]176).
Lateral movement and exfiltration
Around the same time, the EC2 instance started scanning the environment and attempted to pivot to other internal systems via RDP, notably a DC EC2 instance, which also started scanning the network, and another EC2 instance.
The latter then proceeded to transfer more than 230 GB of data to the rare external GTHost VPS endpoint 23.150.248[.]189, while downloading hundreds of GBs of data over SMB from another EC2 instance.
Figure 7: Cyber AI Analyst incident generated following the unusual scanning and RDP connections from the initial compromised device.
The same behavior was replicated across multiple EC2 instances, whereby compromised instances uploaded data over internal RDP connections to other instances, which then started transferring data to the same GTHost VPS endpoint over port 5000, which is typically used for Universal Plug and Play (UPnP).
What Darktrace detected
Darktrace observed the threat actor uploading a total of 718 GB to the external endpoint, after which they detonated ransomware within the compromised VPC networks.
This activity generated nine Enhanced Monitoring alerts in Darktrace, focusing on the scanning and external data activity, with the earliest of those alerts triggering around one hour after the initial intrusion.
Darktrace’s Autonomous Response capability was not configured to act on these devices. Therefore, the malicious activity was not autonomously blocked and escalated to the point of ransomware detonation.
Conclusion
This blog examined three real-world compromises in customer cloud environments each illustrating different stages in the attack lifecycle.
The first case showcased a notable progression from a SaaS compromise to a full cloud intrusion, emphasizing the critical role of anomaly detection when legitimate credentials are abused.
The latter two incidents demonstrated that while early detection is vital, the ability to autonomously block malicious activity at machine speed is often the most effective way to contain threats before they escalate.
Together, these incidents underscore the need for continuous visibility, behavioral analysis, and machine-speed intervention across hybrid environments. Darktrace's AI-driven detection and Autonomous Response capabilities, combined with expert oversight from its Security Operations Center, give defenders the speed and clarity they need to contain threats and reduce operational disruption, before the situation spirals.
Credit to Alexandra Sentenac (Senior Cyber Analyst) and Dylan Evans (Security Research Lead)
Top Eight Threats to SaaS Security and How to Combat Them
The latest on the identity security landscape
Following the mass adoption of remote and hybrid working patterns, more critical data than ever resides in cloud applications – from Salesforce and Google Workspace, to Box, Dropbox, and Microsoft 365.
As SaaS applications look set to remain an integral part of the digital estate, organizations are being forced to rethink how they protect their users and data in this area.
What is SaaS security?
SaaS security is the protection of cloud applications. It includes securing the apps themselves as well as the user identities that engage with them.
Below are the top eight threats that target SaaS security and user identities.
1. Account Takeover (ATO)
Attackers gain unauthorized access to a user’s SaaS or cloud account by stealing credentials through phishing, brute-force attacks, or credential stuffing. Once inside, they can exfiltrate data, send malicious emails, or escalate privileges to maintain persistent access.
2. Privilege escalation
Cybercriminals exploit misconfigurations, weak access controls, or vulnerabilities to increase their access privileges within a SaaS or cloud environment. Gaining admin or superuser rights allows attackers to disable security settings, create new accounts, or move laterally across the organization.
3. Lateral movement
Once inside a network or SaaS platform, attackers move between accounts, applications, and cloud workloads to expand their foot- hold. Compromised OAuth tokens, session hijacking, or exploited API connections can enable adversaries to escalate access and exfiltrate sensitive data.
4. Multi-Factor Authentication (MFA) bypass and session hijacking
Threat actors bypass MFA through SIM swapping, push bombing, or exploiting session cookies. By stealing an active authentication session, they can access SaaS environments without needing the original credentials or MFA approval.
5. OAuth token abuse
Attackers exploit OAuth authentication mechanisms by stealing or abusing tokens that grant persistent access to SaaS applications. This allows them to maintain access even if the original user resets their password, making detection and mitigation difficult.
6. Insider threats
Malicious or negligent insiders misuse their legitimate access to SaaS applications or cloud platforms to leak data, alter configurations, or assist external attackers. Over-provisioned accounts and poor access control policies make it easier for insiders to exploit SaaS environments.
SaaS applications rely on APIs for integration and automation, but attackers exploit insecure endpoints, excessive permissions, and unmonitored API calls to gain unauthorized access. API abuse can lead to data exfiltration, privilege escalation, and service disruption.
8. Business Email Compromise (BEC) via SaaS
Adversaries compromise SaaS-based email platforms (e.g., Microsoft 365 and Google Workspace) to send phishing emails, conduct invoice fraud, or steal sensitive communications. BEC attacks often involve financial fraud or data theft by impersonating executives or suppliers.
BEC heavily uses social engineering techniques, tailoring messages for a specific audience and context. And with the growing use of generative AI by threat actors, BEC is becoming even harder to detect. By adding ingenuity and machine speed, generative AI tools give threat actors the ability to create more personalized, targeted, and convincing attacks at scale.
Protecting against these SaaS threats
Traditionally, security leaders relied on tools that were focused on the attack, reliant on threat intelligence, and confined to a single area of the digital estate.
However, these tools have limitations, and often prove inadequate for contemporary situations, environments, and threats. For example, they may lack advanced threat detection, have limited visibility and scope, and struggle to integrate with other tools and infrastructure, especially cloud platforms.
AI-powered SaaS security stays ahead of the threat landscape
New, more effective approaches involve AI-powered defense solutions that understand the digital business, reveal subtle deviations that indicate cyber-threats, and action autonomous, targeted responses.
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