December 4, 2024

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.

Written by

Nathaniel Jones

VP, Security & AI Strategy, Field CISO

Inside the SOC

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

Written by

Nathaniel Jones

VP, Security & AI Strategy, Field CISO

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.

Safelink smuggling, which involves an attacker intentionally getting their malicious payload rewritten by a security solution’s Safelink capability to then propagate the rewritten URL to others. This not only evades detection but also undermines trust in email security tools. Darktrace observed over 300,000 cases of Safelinks being included in unexpected and suspicious contexts over a period of 3 months.

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.

Ransomware is among the most common threats targeting organizations after hours. In 76% of cases, the encryption process begins during off-hours or on weekends6. For instance, Darktrace identified a ransomware attack launched in the early hours of Christmas Day on a client’s network, taking advantage of the period when most employees were offline.

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.

Interested in how AI-driven email security can protect your organization? Check out the product hub to learn more. Or watch the demo video to see Darktrace / EMAIL in action.

References

[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)

[6] https://www.zdnet.com/article/most-ransomware-attacks-take-place-during-the-night-or-the-weekend

[7] https://www.scworld.com/perspective/ciso-stress-levels-are-out-of-control

[8] https://www.informationweek.com/cyber-resilience/the-psychology-of-cybersecurity-burnout

[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)

Written by

Nathaniel Jones

VP, Security & AI Strategy, Field CISO

Inside the SOC

Written by

Nathaniel Jones

VP, Security & AI Strategy, Field CISO

Malware Research Engineer

•

April 28, 2026

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April 29, 2026

Darktrace Malware Analysis: Jenkins Honeypot Reveals Emerging Botnet Targeting Online Games

DDoS Botnet discovery

To observe adversary behavior in real time, Darktrace operates a global honeypot network known as “CloudyPots”, designed to capture malicious activity across a wide range of services, protocols, and cloud platforms. These honeypots provide valuable insights into the techniques, tools, and malware actively targeting internet‑facing infrastructure.

How attackers used a Jenkins honeypot to deploy the botnet

One such software honeypotted by Darktrace is Jenkins, a CI build system that allows developers to build code and run tests automatically. The instance of Jenkins in Darktrace’s honeypot is intentionally configured with a weak password, allowing attackers to obtain remote code execution on the service.

In one instance observed by Darktrace on March 18, 2026, a threat actor seemingly attempted to target Darktrace’s Jenkins honeypot to deploy a distributed denial-of-service (DDoS) botnet. Further analysis by Darktrace’s Threat Research team revealed the botnet was intended to specifically target video game servers.

How the Jenkins scriptText endpoint was used for remote code execution

The Jenkins build system features an endpoint named scriptText, which enables users to programmatically send new jobs, in the form of a Groovy script. Groovy is a programming language with similar syntax to Java and runs using the Java Virtual Machine (JVM). An attacker can abuse the scriptText endpoint to run a malicious script, achieving code execution on the victim host.

*Figure 1: Request sent to the scriptText endpoint containing the malicious script.*

The malicious script is sent using the form-data content type, which results in the contents of the script being URL encoded. This encoding can be decoded to recover the original script, as shown in Figure 2, where Darktrace Analysts decoded the script using CyberChef,

*Figure 2: The malicious script decoded using CyberChef.*

What happens after Jenkins is compromised

As Jenkins can be deployed on both Microsoft Windows and Linux systems, the script includes separate branches to target each platform.

In the case of Windows, the script performs the following actions:

Downloads a payload from 103[.]177.110.202/w.exe and saves it to C:\Windows\Temp\update.dat.
Renames the “update.dat” file to “win_sys.exe” (within the same folder)
Runs the Unblock-File command is used to remove security restrictions typically applied to files downloaded from the internet.
Adds a firewall allow rule is added for TCP port 5444, which the payload uses for command-and-control (C2) communications.

On Linux systems, the script will instead use a Bash one-liner to download the payload from 103[.]177.110.202/bot_x64.exe to /tmp/bot and execute it.

Why this botnet uses a single IP for delivery and command and control

The IP 103[.]177.110.202 belongs to Webico Company Limited, specifically its Tino brand, a Vietnamese company that offers domain registrar services and server hosting. Geolocation data indicates that the IP is located in Ho Chi Minh City. Open-source intelligence (OSINT) analysis revealed multiple malicious associations tied to the IP [1].

Darktrace’s analysis found that the IP 103[.]177.110.202 is used for multiple stages of an attack, including spreading and initial access, delivering payloads, and C2 communication. This is an unusual combination, as many malware families separate their spreading servers from their C2 infrastructure. Typically, malware distribution activity results in a high volume of abuse complaints, which may result in server takedowns or service suspension by internet providers. Separate C2 infrastructure ensures that existing infections remain controllable even if the spreading server is disrupted.

How the malware evades detection and maintains persistence

Analysis of the Linux payload (bot _x64)

The sample begins by setting the environmental variables BUILD_ID and JENKINS_NODE_COOKIE to “dontKillMe”. By default, Jenkins terminates long-running scripts after a defined timeout period; however, setting these variables to “dontKillMe” bypasses this check, allowing the script to continue running uninterrupted.

The script then performs several stealth behaviors to evade detection. First, it deletes the original executable from disk and then renames itself to resemble the legitimate kernel processes “ksoftirqd/0” or “kworker”, which are found on Linux installations by default. It then uses a double fork to daemonize itself, enabling it to run in the background, before redirecting standard input, standard output, and standard error to /dev/null, hiding any logging from the malware. Finally, the script creates a signal handler for signals such as SIGTERM, causing them to be ignored and making it harder to stop the process.

*Figure 3: Stealth component of the main function*

How the botnet communicates with command and control (C2)

The sample then connects to the C2 server and sends the detected architecture of the system on which the agent was installed. The malware then enters a loop to handle incoming commands.

The sample features two types of commands, utility commands used to manage the malware, and commands to trigger attacks. Three special commands are defined: “PING” (which replies with PONG as a keep-alive mechanism), “!stop” which causes the malware to exit, and “!update”, which triggers the malware to download a new version from the C2 server and restart itself.

*Figure 4: Initial connection to the C2 sever.*

What DDoS attack techniques this botnet uses

The attack commands consist of the following:

Many of these commands invoke the same function despite appearing to be different attack techniques. For example, specialized attacks such as Cloudflare bypass (cfbypass, uam) use the exact same function as a standard HTTP attack. This may indicate the threat actor is attempting to make the botnet look like it has more capabilities than it actually has, or it could suggest that these commands are placeholders for future attack functionality that has yet to be implemented

All the commands take three arguments: IP, port to attack, and the duration of the attack.

attack_udp and attack_udp_pps

The attack_udp and attack_udp_pps functions both use a basic loop and sendto system call to send UDP packets to the victim’s IP, either targeting a predetermined port or a random port. The attack_udp function sends packets with 1,450 bytes of data, aimed at bandwidth saturation, while the attack_udp_pps function sends smaller 64-byte packets. In both cases, the data body of the packet consists of entirely random data.

*Figure 5: Code for the UDP attack method*

attack_dayz

The attack_dayz function follows a similar structure to the attack_udp function; however, instead of sending random data, it will instead send a TSource Engine Query. This command is specific to Valve Source Engine servers and is designed to return a large volume of data about the targeted server. By repeatedly flooding this request, an attacker can exhaust the resources of a server using a comparatively small amount of data.

The Valve Source Engine server, also called Source Engine Dedicated server, is a server developed by video game company Valve that enables multiplayer gameplay for titles built using the Source game engine, which is also developed by Valve. The Source engine is used in games such as Counterstrike and Team Fortress 2. Curiously, the function attack_dayz, appears to be named after another popular online multiplayer game, DayZ; however, DayZ does not use the Valve Source Engine, making it unclear why this name was chosen.

The code for the “attack_dayz” attack function. — *Figure 6: The code for the* “*attack_dayz” attack function.*

attack_tcp_push

The attack_tcp_push function establishes a TCP socket with the non-blocking flag set, allowing it to rapidly call functions such as connect() and send() without waiting for their completion. For the duration of the attack, it enters a while loop in which it repeatedly connects to the victim, sends 1,024 bytes of random data, and then closes the connection. This process repeats until the attack duration ends. If the mode flag is set to 1, the function also configures the socket with TCP no-delay enabled, allowing for packets to be sent immediately without buffering, resulting in a higher packet rate and a more effective attack.

*Figure 7: The code for the TCP attack function.*

attack_http

Similar to attach_tcp_push, attack_http configures a socket with no-delay enabled and non-blocking set. After establishing the connection, it sends 64 HTTP GET requests before closing the socket.

*Figure 8: The code for the HTTP attack function.*

attack_special

The attack_special function creates a UDP socket and sets the port and payload based on the value of the mode flag:

Mode 0: Port 53 (DNS), sending a 10-byte malformed data packet.
Mode 1: Port 27015 (Valve Source Engine), sending the previously observed TSource Engine Query packet.
Mode 2: Port 123 (NTP), sending the start of an NTP control request.

*Figure 9: The code for the attack_special function.*

What this botnet reveals about opportunistic attacks on internet-facing systems

Jenkins is one of the less frequently exploited services honeypotted by Darktrace, with only a handful campaigns observed. Nonetheless, the emergence of this new DDoS botnet demonstrates that attackers continue to opportunistically exploit any internet-facing misconfiguration at scale to grow the botnet strength.

While the hosts most commonly affected by these opportunistic attacks are usually “lower-value” systems, this distinction is largely irrelevant for botnets, where numbers alone are more important to overall effectiveness

The presence of game-specific DoS techniques further highlights that the gaming industry continues to be extensively targeted by cyber attackers, with Cloudflare reporting it as the fourth most targeted industry [2]. This botnet has likely already been used against game servers, serving as a reminder for server operators to ensure appropriate mitigations are in place.

Credit to Nathaniel Bill (Malware Research Engineer)
Edited by Ryan Traill (Content Manager)

Indicators of Compromise (IoCs)

103[.]177.110.202 - Attacker and command-and-control IP

F79d05065a2ba7937b8781e69b5859d78d5f65f01fb291ae27d28277a5e37f9b – bot_x64

References

[1] https://www.virustotal.com/gui/url/86db2530298e6335d3ecc66c2818cfbd0a6b11fcdfcb75f575b9fcce1faa00f1/detection

[2] - https://blog.cloudflare.com/ddos-threat-report-2025-q4/

About the author

Nathaniel Bill

Malware Research Engineer

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AI

April 28, 2026

State of AI Cybersecurity 2026: 87% of security professionals are seeing more AI-driven threats, but few feel ready to stop them

The findings in this blog are taken from Darktrace’s annual State of AI Cybersecurity Report 2026.

In part 1 of this blog series, we explored how AI is remaking the attack surface, with new tools, models, agents — and vulnerabilities — popping up just about everywhere. Now embedded in workflows across the enterprise, and often with far-reaching access to sensitive data, AI systems are quickly becoming a favorite target of cyber threat actors.

Among bad actors, though, AI is more often used as a tool than a target. Nearly 62% of organizations experienced a social engineering attack involving a deepfake, or an incident in which bad actors used AI-generated video or audio to try to trick a biometric authentication system, compared to 32% that reported an AI prompt injection attack.

In the hands of attackers, AI can do many things. It’s being used across the entire kill chain: to supercharge reconnaissance, personalize phishing, accelerate lateral movement, and automate data exfiltration. Evidence from Anthropic demonstrates that threat actors have harnessed AI to orchestrate an entire cyber espionage campaign from end to end, allegedly running it with minimal human involvement.

CISOs inhabit a world where these increasingly sophisticated attacks are ubiquitous. Naturally, combatting AI-powered threats is top of mind among security professionals, but many worry about whether their capabilities are up to the challenge.

AI-powered threats at scale: no longer hypothetical

AI-driven threats share signature characteristics. They operate at speed and scale. Automated tools can probe multiple attack paths, search for multiple vulnerabilities and send out a barrage of phishing emails, all within seconds. The ability to attack everywhere at once, at a pace that no human operator could sustain, is the hallmark of an AI-powered threat. AI-powered threats are also dynamic. They can adapt their behavior to spread across a network more efficiently or rewrite their own code to evade detection.

Security teams are seeing the signs that they’re fighting AI-powered threats at every stage of the kill chain, and the sophistication of these threats is testing their resolve and their resources.

73% say that AI-powered cyber threats are having a significant impact on their organization
92% agree that these threats are forcing them to upgrade their defenses
87% agree that AI is significantly increasing the sophistication and success rate of malware
87% say AI is significantly increasing the workload of their security operations team

These teams now confront a challenge unlike anything they’ve seen before in their careers, and the risks are compounding across workflows, tools, data, and identities. It’s no surprise that 66% of security professionals say their role is more stressful today than it was five years ago, or that 47% report feeling overwhelmed at work.

Up all night: Security professionals’ worry list is long

Traditional security methods were never built to handle the complexity and subtlety of AI-driven behavior. Working in the trenches, defenders have deep firsthand experience of how difficult it can be to detect and stop AI-assisted threats.

Increasingly effective social engineering attacks are among their top concerns. 50% of security leaders mentioned hyper-personalized phishing campaigns as one of their biggest worries, while 40% voiced apprehension about deepfake voice fraud. These concerns are legitimate: AI-generated phishing emails are increasingly tailored to individual organizations, business activities, or individuals. Gone are the telltale signs – like grammar or spelling mistakes – that once distinguished malicious communications. Notably, 33% of the malicious emails Darktrace observed in 2025 contained over 1,000 characters, indicating probable LLM usage.

Security leaders also worry about how bad actors can leverage AI to make attacks even faster and more dynamic. 45% listed automated vulnerability scanning and exploit chaining among their biggest concerns, while 40% mentioned adaptive malware.

Confidence is lacking

Protecting against AI demands capabilities that many organizations have not yet built. It requires interpreting new indicators, uncovering the subtle intent within interactions, and recognizing when AI behavior – human or machine – could be suspicious. Leaders know that their current tools aren’t prepared for this. Nearly half don’t feel confident in their ability to defend against AI-powered attacks.

We’ve asked participants in our survey about their confidence for the last three years now. In 2024, 60% said their organizations were not adequately prepared to defend against AI-driven threats. Last year, that percentage shrunk to 45%, a possible indicator that security programs were making progress. Since then, however, the progress has apparently stalled. 46% of security leaders now feel inadequately prepared to protect their organizations amidst the current threat landscape.

Some of these differences are accentuated across different cultures. Respondents in Japan are far less confident (77% say they are not adequately prepared) than respondents in Brazil (where only 21% don’t feel prepared).

Where security programs are falling short

It’s no longer the case that cybersecurity is overlooked or underfunded by executive leadership. Across industries, management recognizes that AI-powered threats are a growing problem, and insufficient budget is near the bottom of most CISO’s list of reasons that they struggle to defend against AI-powered threats.

It’s the things that money can’t buy – experience, knowledge, and confidence – that are holding programs back. Near the top of the list of inhibitors that survey participants mention is “insufficient knowledge or use of AI-driven countermeasures.” As bad actors embrace AI technologies en masse, this challenge is coming into clearer focus: attack-centric security tools, which rely on static rules, signatures, and historical attack patterns, were never designed to handle the complexity and subtlety of AI-driven attacks. These challenges feel new to security teams, but they are the core problems Darktrace was built to solve.

Our Self-Learning AI develops a deep understanding of what “normal” looks like for your organization –including unique traffic patterns, end user habits, application and device profiles – so that it can detect and stop novel, dynamic threats at the first encounter. By focusing on learning the business, rather than the attack, our AI can keep pace with AI-powered threats as they evolve.

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Explore the full State of AI Cybersecurity 2026 report for deeper insights into how security leaders are responding to AI-driven risks.

Learn more about securing AI in your enterprise.

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Check out this article by Darktrace: Phishing Attacks Surge Over 600% in the Buildup to Black Friday

Phishing Attacks Surge Over 600% in the Buildup to Black Friday

Multiple attack methods exploit trust during holiday rush

A spike in cyber-criminal activity which extends beyond email

Festive cheer: giving your SOC team the break they deserve

Darktrace Malware Analysis: Jenkins Honeypot Reveals Emerging Botnet Targeting Online Games

State of AI Cybersecurity 2026: 87% of security professionals are seeing more AI-driven threats, but few feel ready to stop them

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Blog

Network

April 29, 2026

Darktrace Malware Analysis: Jenkins Honeypot Reveals Emerging Botnet Targeting Online Games

DDoS Botnet discovery

How attackers used a Jenkins honeypot to deploy the botnet

How the Jenkins scriptText endpoint was used for remote code execution

What happens after Jenkins is compromised

Why this botnet uses a single IP for delivery and command and control

How the malware evades detection and maintains persistence

How the botnet communicates with command and control (C2)

What DDoS attack techniques this botnet uses

attack_udp and attack_udp_pps

attack_dayz

attack_tcp_push

What this botnet reveals about opportunistic attacks on internet-facing systems

Indicators of Compromise (IoCs)

Blog

AI

April 28, 2026

State of AI Cybersecurity 2026: 87% of security professionals are seeing more AI-driven threats, but few feel ready to stop them

AI-powered threats at scale: no longer hypothetical

Up all night: Security professionals’ worry list is long

Confidence is lacking

Where security programs are falling short