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December 16, 2024

Breaking Down Nation State Attacks on Supply Chains

Explore how nation-state supply chain attacks like 3CX, NotPetya, and SolarWinds exploited trusted providers to cause global disruption, highlighting the urgent need for robust security measures.
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
Benjamin Druttman
Cyber Security AI Technical Instructor
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16
Dec 2024

Introduction: Nation state attacks on supply chains

In recent years, supply chain attacks have surged in both frequency and sophistication, evolving into one of the most severe threats to organizations across almost every industry. By exploiting third-party vendors and service providers, these attacks can inflict widespread disruption with a single breach. They have become a go-to choice for nation state actors and show no signs of slowing down. According to Gartner, the costs from these attacks will skyrocket “from $46 billion in 2023 to $138 billion by 2031” [1].  

But why are supply chains specifically such an irresistible target for threat actors? Dwight D. Eisenhower, the General of the US Army in World War II and former US President, once said, “you won’t find it difficult to prove that battles, campaigns, and even wars have been won or lost primarily because of logistics.”

The same is true in cyberspace and cyberwarfare. We live in an increasingly interconnected world. The provision of almost every service integral to our daily lives relies on a complex web of interdependent third parties.  

Naturally, threat actors gravitate towards these service providers. By compromising just one of them, they can spread through supply chains downstream to other organizations and raise the odds of winning their battle, campaign, or war.  

software supply chain sequence
Figure 1: Software supply chain attack cycle

A house built on open-source sand

Software developers face immense pressure to produce functional code quickly, often under tight deadlines. Adding to this challenge is the need to comply with stringent security requirements set by their DevSecOps counterparts, who aim to ensure that code is safe from vulnerabilities.  

Open-source repositories alleviate some of this pressure by providing pre-built packages of code and fully functioning tools that developers can freely access and integrate. These highly accessible resources enhance productivity and boost innovation. As a result, they have a huge, diverse user base spanning industries and geographies. However, given their extensive adoption, any security lapse can result in widespread compromise across businesses.

Cautionary tales for open-source dependencies

This is exactly what happened in December 2021 when a remote code execution vulnerability was discovered in Log4J’s software. In simple terms, it exposed an alarmingly straightforward way for attackers to take control of any system using Log4J.  

The scope for potential attack was unprecedented. Some estimates say up to 3 billion devices were affected worldwide, in what was quickly labelled the “single biggest, most critical vulnerability of the last decade” [2].

What ensued was a race between opportunistic nefarious actors and panicked security professionals. The astronomical number of vulnerable devices laid expansive groundwork for attackers, who quickly began probing potentially exploitable systems. 48% of corporate networks globally were scanned for the vulnerability, while security teams scrambled to apply the remediating patch [3].

The vulnerability attracted nation states like a moth to a flame, who, unsurprisingly, beat many security teams to it. According to the FBI and the US Cybersecurity and Infrastructure Agency (CISA), Iranian government-sponsored threat groups were found using the Log4J vulnerability to install cryptomining software, credential stealers and Ngrok reverse proxies onto no less than US Federal networks [4].  

Research from Microsoft and Mandiant revealed nation state groups from China, North Korea and Turkey also taking advantage of the Log4J vulnerability to deploy malware on target systems [5].  

If Log4j taught us anything, it’s that vulnerabilities in open-source technologies can be highly attractive target for nation states. When these technologies are universally adopted, geopolitical adversaries have a much wider net of opportunity to successfully weaponize them.  

It therefore comes as no surprise that nation states have ramped up their operations targeting the open-source link of the supply chain in recent years.  

Since 2020, there has been a 1300% increase in malicious threats circulating on open-source repositories. PyPI is the official open-source code repository for programming done in the Python language and used by over 800,000 developers worldwide. In the first 9 months of 2023 alone, 7,000 malicious packages were found on PyPI, some of which were linked to the North Korea state-sponsored threat group, Lazarus [6].  

Most of them were found using a technique called typosquatting, in which the malicious payloads are disguised with names that very closely resemble those of legitimate packages, ready for download by an unwitting software developer. This trickery of the eye is an example of social engineering in the supply chain.  

A hop, skip, and a jump into the most sensitive networks on earth

One of the most high-profile supply chain attacks in recent history occurred in 2023, targeting 3CX’s Desktop App – a widely used video communications by over 600,000 customers in various sectors such as aerospace, healthcare and hospitality.

The incident gained notoriety as a double supply chain attack. The initial breach originated from financial trading software called X_Trader, which had been infected with a backdoor.  A 3CX employee unknowingly downloaded the compromised X_Trader software onto a corporate device. This allowed attackers to steal the employee’s credentials and use them to gain access to 3CX’s network, spread laterally and compromising Windows and Mac systems.  

The attack moved along another link of the supply chain to several of 3CX’s customers, impacting critical national infrastructure like energy sector in US and Europe.  

For the average software provider, this attack shed more light on how a compromise of their technology could cause chaos for their customers.  

But nation states already knew this. The 3CX attack was attributed, yet again, to Lazarus, the same North Korean nation state blamed for implanting malicious packages in the Python repository.  

It’s also worth mentioning the astounding piece of evidence in a separate social engineering campaign which linked the 3CX hack to North Korea. It was an attack worthy of a Hollywood cyber block buster. The threat group, Lazarus, lured hopeful job candidates on LinkedIn into clicking on malicious ZIP file disguised as an attractive PDF offer for a position as a Developer at HSBC. The malware’s command and control infrastructure, journalide[.]org, was the same one discovered in the 3CX campaign.  

Though not strictly a supply chain attack, the LinkedIn campaign illustrates how nation states employ a diverse array of methods that span beyond the supply chain to achieve their goals. These sophisticated and well-resourced adversaries are adaptable and capable of repurposing their command-and-control infrastructure to orchestrate a range of attacks. This attack, along with the typosquatting attacks found in PyPI, serve as a critical reminder for security teams: supply chain attacks are often coupled with another powerful tactic – social engineering of human teams.

When the cure is worse than the disease

Updates to the software are a core pillar of cybersecurity, designed to patch vulnerabilities like Log4J and ensure it is safe. However, they have also proven to serve as alarmingly efficient delivery vessels for nation states to propagate their cyberattacks.  

Two of the most prolific supply chain breaches in recent history have been deployed through malicious updates, illustrating how they can be a double-edged sword when it comes to cyber defense.  

NotPetya (2017) and Solarwinds (2020)

The 2017 NotPetya ransomware attack exemplified the mass spread of ransomware via a single software update. A Russian military group injected malware on accounting software used by Ukrainian businesses for tax reporting. Via an automatic update, the ransomware was pushed out to thousands of customers within hours, crippled Ukrainian infrastructure including airports, financial institutions and government agencies.  

Some of the hardest hit victims were suppliers themselves. Maersk, the global shipping giant responsible for shipping one fifth of the world’s goods, had their entire global operations brought to a halt and their 76 ports temporarily shut down. The interruptions to global trade were then compounded when a FedEx subsidiary was hit by the same ransomware. Meanwhile, Merck, a pharmaceutical company, was unable to supply vaccines to the Center for Disease Control and Prevention due to the attack.  

In 2020, another devastating supply chain attack unfolded in a similar way. Threat actors tied to Russian intelligence embedded malicious code into Solarwinds’ Orion IT software, which was then distributed as an update to 18,000 organizations. Victims included at least eight U.S. government agencies, as well as several major tech companies.  

These two attacks highlighted two key lessons. First, in a hyperconnected digital world, nation states will exploit the trust organizations place in software updates to cause a ripple effect of devastation downstream. Secondly, the economies of scale for the threat actor themselves are staggering: a single malicious update provided the heavy lifting work of dissemination to the attacker. A colossal number of originations were infected, and they obtained the keys to the world’s most sensitive networks.

The conclusion is obvious, albeit challenging to implement; organizations must rigorously scrutinize the authenticity and security of updates to prevent far-reaching consequences.  

Some of the biggest supply chain attacks in recent history and the nation state actor they are attributed to
Figure 2: Some of the biggest supply chain attacks in recent history and the nation state actor they are attributed to

Geopolitics and nation States in 2024: Beyond the software supply chain

The threat to our increasingly complex web of global supply is real. But organizations must look beyond their software to successfully mitigate supply chain disruption. Securing hardware and logistics is crucial, as these supply chain links are also in the crosshairs of nation states.  

In July 2024, suspicious packages caused a warehouse fire at a depot belonging to courier giant DHL in Birmingham, UK. British counter-terrorism authorities investigated Russian involvement in this fire, which was linked to a very similar incident that same month at a DHL facility in Germany.  

In September 2024, camouflaged explosives were hidden in walkie talkies and pagers in Lebanon and Syria – a supply chain attack widely believed to be carried out by Israel.

While these attacks targeted hardware and logistics rather than software, the underlying rule of thumb remained the same: the compromise of a single distributor can provide the attackers with considerable economies of scale.

These attacks sparked growing concerns of coordinated efforts to sabotage the supply chain. This sentiment was reflected in a global survey carried out by HP in August 2024, in which many organisations reported “nation-state threat actors targeting physical supply chains and tampering with device hardware and firmware integrity” [7].

More recently, in November 2024, the Russian military unit 29155 vowed to “turn the lights out for millions” by threatening to launch cyberattacks on the blood supply of NATO countries, critical national infrastructure (CNI). Today, CNI encompasses more than the electric grid and water supply; it includes ICT services and IT infrastructure – the digital systems that underpin the foundations of modern society.    

This is nothing new. The supply and logistics-focused tactic has been central to warfare throughout history. What’s changed is that cyberspace has merely expanded the scale and efficiency of these tactics, turning single software compromises into attack multipliers. The supply chain threat is now more multi-faceted than ever before.  

Learnings from the supply chain threat landscape

Consider some of the most disastrous nation-state supply chain attacks in recent history – 3CX, NotPetya and Solarwinds. They share a remarkable commonality: the attackers only needed to compromise a single piece of software to cause rampant disruption. By targeting a technology provider whose products were deeply embedded across industries, threat actors leveraged the trust inherent in the supply chain to infiltrate networks at scale.

From a nation-state’s perspective, targeting a specific technology, device or service used by vast swathes of society amplifies operational efficiency. For software, hardware and critical service suppliers, these examples serve as an urgent wake-up call. Without rigorous security measures, they risk becoming conduits for global disruption. Sanity-checking code, implementing robust validation processes, and fostering a culture of security throughout the supply chain are no longer optional—they are essential.  

The stakes are clear: in the interconnected digital age, the safety of countless systems, industries and society at large depends on their vigilance.  

Screenshot of supply chain security whitepaper

Gain a deeper understanding of the evolving risks in supply chain security and explore actionable strategies to protect your organization against emerging threats. Download the white paper to empower your decision-making with expert insights tailored for CISOs

Download: Securing the Supply Chain White Paper

References

  1. https://www.gartner.com/en/documents/5524495
  1. CISA Insights “Remediate Vulnerabilities for Internet-Accessible Systems.”
  1. https://blog.checkpoint.com/security/the-numbers-behind-a-cyber-pandemic-detailed-dive/
  1. https://www.cisa.gov/news-events/cybersecurity-advisories/aa22-320a  
  1. https://www.microsoft.com/en-us/security/blog/2021/12/11/guidance-for-preventing-detecting-and-hunting-for-cve-2021-44228-log4j-2-exploitation/  
  1. https://content.reversinglabs.com/state-of-sscs-report/the-state-of-sscs-report-24  
  1. https://www.hp.com/us-en/newsroom/press-releases/2024/hp-wolf-security-study-supply-chains.html
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
Benjamin Druttman
Cyber Security AI Technical Instructor

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May 21, 2026

Darktrace named a Leader in the 2026 Gartner® Magic Quadrant™ for Network Detection and Response (NDR) For the Second Consecutive Year

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Continued recognition in NDR  

Darktrace has been recognized as a Leader in the 2026 Gartner® Magic Quadrant™ for Network Detection and Response (NDR), marking the second consecutive year in the Leaders quadrant.

We believe this consistency reflects sustained ability to execute, adapt, and deliver outcomes as the market evolves.

While we are immensely proud to be recognized by industry analysts as a Leader in NDR, that's just part of the story. Darktrace was also Named the Only 2025 Gartner® Peer Insights™ Customers’ Choice for Network Detection and Response based on direct customer feedback and real-world experience.

We believe the combination of these two signals is important. One reflects how the market is evaluated. The other reflects how technology performs in practice.

Why Darktrace continues to be recognized as a leader

We believe our position as a Leader for the second consecutive year reflects a combination of our sustained ability to execute in NDR, continued AI innovation, and proven delivery of security outcomes for customers and partners worldwide.

We also feel that our leadership in the NDR market is a testament to our unique and multi-layered AI approach, for which we were recognized as No.7 on Fast Company’s Most Innovative AI Companies of 2026 list, plus one of the hottest AI cybersecurity companies in CRN's AI 100.

Adapting to complex, real-world environments

Organizations are no longer protecting a single network perimeter. They are securing a mix of users, devices, applications, and data that move across hybrid environments.

Darktrace has focused on maintaining visibility and detection across these conditions, allowing security teams to understand activity as it scales.

Supporting organizations globally, not just technically

Security outcomes are shaped as much by deployment and support as they are by detection capability.

Darktrace continues to invest in regional presence across 29 countries around the world, helping organizations operationalize NDR in ways that align with local requirements, internal processes, and team structures.

Continuing to push AI beyond detection

AI in cybersecurity is often positioned as a way to improve detection accuracy. But the more important shift is how AI can influence decision-making and response.

Darktrace continues to develop models that learn from both live environments and historical incident data, combining real-time behavioral analysis with insights derived from prior attack patterns.

Using technologies such as the Incident Graph and DIGEST (Darktrace Incident Graph Evaluation for Security Threats), activity is not analyzed in isolation. Instead, relationships between users, devices, connections, and events are mapped over time, allowing the system to reconstruct how an incident is unfolding and how similar incidents have progressed in the past.

By evaluating these patterns, Darktrace can assess the likelihood that an incident will escalate, prioritizing the activity that poses the greatest risk and surfacing the most relevant context for investigation.

This shifts security operations from simply identifying anomalies to understanding their trajectory, helping teams anticipate potential impact and respond earlier with greater precision.

Why NDR is shifting from reactive detection to proactive, AI-driven security

Traditional approaches to NDR have been built around reactively identifying threats once they become clearly visible. That model is increasingly difficult to rely on.

Attackers are no longer operating in ways that stand out. They use valid credentials, trusted tools, and low-and-slow techniques that blend into everyday activity. By the time something looks obviously malicious, the impact is often already underway.

This is the core limitation of reactive detection. It depends on recognizing something that already looks like a threat.

As a result, many of the most consequential incidents today fall into a gap.

Insider activity, compromised credentials, and novel attacks rarely trigger traditional alerts because they do not follow known patterns. On the surface, they often appear legitimate, making them difficult to distinguish from normal behavior without deeper context.

This is why we believe this Gartner recognition reflects a broader shift in NDR toward autonomous, proactive and pre‑emptive security operations.

By understanding normal behavior within an environment, it is possible to identify subtle deviations rather than waiting for confirmation of threats as they are taking place.

Darktrace’s Self-Learning AI is designed for behavioral understanding. By continuously learning each organization’s normal patterns, it can detect deviations in real time, enabling a proactive and pre-emptive model of NDR where security teams can respond to early signs of risk as they emerge, reducing the window in which attacks can develop.

In multiple cases, this behavioral approach has led to early threat detection where Darktrace identified completely unknown threats, including pre-CVE zero-day activity. By detecting subtle behavioral changes before vulnerabilities were publicly disclosed or widely understood, organizations can mitigate threats before they do damage.

This shift is subtle but important. Modern NDR solutions must shift from a system that explains what happened to one that helps prevent threats from developing in the first place, and Darktrace is proud to be at the forefront of this shift - helping organizations build and maintain a state of proactive network resilience.

Continuing to innovate at the forefront of NDR

In our view, recognition as a Leader reflects where the market is today. Continuing to innovate defines what comes next.

As businesses evolve, new technologies like AI tools and agents introduce new security risks and challenges; security teams need more than simple detection. They need a complete understanding of risk as it develops, the ability to investigate it in context, and to contain threats at machine speed.  

Darktrace / NETWORK is built to deliver across that full spectrum. Its Self-Learning AI continuously adapts to each organization’s environment, identifying subtle behavioral changes that signal emerging threats. Integrated investigation and autonomous response reduce the time between detection and action, allowing teams to move with greater speed and confidence.

This combination enables organizations to detect and contain known, unknown, and insider threats as they develop, while also strengthening resilience over time.

As a two-time Leader in the Gartner® Magic Quadrant™ for NDR and the only 2025 Gartner® Peer Insights™ Customers’ Choice, we feel Darktrace continues to evolve its platform to meet the demands of modern environments, delivering a more complete and adaptive approach to network security.

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Disclaimer: The 2026 Gartner® Magic Quadrant™ for Network Detection and Response (NDR) ,The 2026 Gartner® Magic Quadrant™ for Network Detection and Response (NDR), Thomas Lintemuth, Charanpal Bhogal, Nahim Fazal, 18 May 2026.

Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved. Magic Quadrant is a registered trademark of Gartner, Inc. and/or its affiliates and is used herein with permission. All rights reserved.

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Mikey Anderson
Product Marketing Manager, Network Detection & Response

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May 21, 2026

Prompt Security in Enterprise AI: Strengths, Weaknesses, and Common Approaches

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How enterprise AI Agents are changing the risk landscape  

Generative AI Agents are changing the way work gets done inside enterprises, and subsequently how security risks may emerge. Organizations have quickly realized that providing these agents with wider access to tooling, internal information, and granting permissions for the agent to perform autonomous actions can greatly increase the efficiency of employee workflows.

Early deployments of Generative AI systems led many organizations to scope individual components as self-contained applications: a chat interface, a model, and a prompt, with guardrails placed at the boundary. Research from Gartner has shown that while the volume and scope of Agentic AI deployments in enterprise environments is rapidly accelerating, many of the mechanisms required to manage risk, trust, and cost are still maturing.

The issue now resides on whether an agent can be influenced, misdirected, or manipulated in ways that leads to unsafe behavior across a broader system.

Why prompt security matters in enterprise AI

Prompt security matters in enterprise AI because prompts are the primary way users and systems interact with Agentic AI models, making them one of the earliest and most visible indicators of how these systems are being used and where risk may emerge.

For security teams, prompt monitoring is a logical starting point for understanding enterprise AI usage, providing insight into what types of questions are being asked and tasks are being given to AI Agents, how these systems are being guided, and whether interactions align with expected behavior. Complete prompt security takes this one step further, filtering out or blocking sensitive or dangerous content to prevent risks like prompt injection and data leakage.

However, visibility only at the prompt layer can create a false sense of security. Prompts show what was asked, but not always why it was asked, or what downstream actions were triggered by the agent across connected systems, data sources, or applications.

What prompt security reveals  

The primary function of prompt security is to minimize risks associated with generative and agentic AI use, but monitoring and analysis of prompts can also grant insight into use cases for particular agents and model. With comprehensive prompt security, security teams should be able to answer the following questions for each prompt:

  • What task was the user attempting to complete?
  • What data was included in the request, and was any of the data high-risk or confidential?
  • Was the interaction high-risk, potentially malicious, or in violation of company policy?
  • Was the prompt anomalous (in comparison to previous prompts sent to the agent / model)?

Improving visibility at this layer is a necessary first step, allowing organizations to establish a baseline for how AI systems are being used and where potential risks may exist.  

Prompt security alone does not provide a complete view of risk. Further data is needed to understand how the prompt is interpreted, how context is applied, what autonomous actions the agent takes (if any), or what downstream systems are affected. Understanding the outcome of a query is just as important for complete prompt security as understanding the input prompt itself – for example, a perfectly normal, low-risk prompt may inadvertently result in an agent taking a high-risk action.

Comprehensive AI security systems like Darktrace / SECURE AI can monitor and analyze both the prompt submitted to a Generative AI system, as well as the responses and chain-of-thought of the system, providing greater insight into the behavior of the system. Darktrace / SECURE AI builds on the core Darktrace methodology, learning the expected behaviors of your organization and identifying deviations from the expected pattern of life.

How organizations address prompt security today

As prompt-level visibility has become a focus, a range of approaches have emerged to make this activity more observable and controllable. Various monitoring and logging tools aim to capture prompt inputs to be analyzed after the fact.  

Input validation and filtering systems attempt to intervene earlier, inspecting prompts before they reach the model. These controls look for known jailbreak patterns, language indicative of adversarial attacks, or ambiguous instructions which could push the system off course.

Importantly, for a prompt security solution to be accurate and effective, prompts must be continually observed and governed, rather than treated as a point-in-time snapshot.  

Where prompt security breaks down in real environments

In more complex environments, especially those involving multiple agents or extensive tool use, AI security becomes harder to define and control.

Agent-to-Agent communications can be harder to monitor and trace as these happen without direct user interaction. Communication between agents can create routes for potential context leakage between agents, unintentional privilege escalation, or even data leakage from a higher privileged agent to a lower privileged one.

Risk is shaped not just by what is asked, but by the conditions in which that prompt operates and the actions an agent takes. Controls at the orchestration layer are starting to reflect this reality. Techniques such as context isolation, scoped memory, and role-based boundaries aim to limit how far a prompt’s influence can extend.  

Furthermore, Shadow AI usage can be difficult to monitor. AI systems that are deployed outside of formal governance structures and Generative AI systems hosted on unknown endpoints can fly under the radar and can go unseen by monitoring tools, leaving a critical opening where adversarial prompts may go undetected. Darktrace / SECURE AI features comprehensive detection of Shadow AI usage, helping organizations identify potential risk areas.

How prompt security fits in a broader AI risk model

Prompt security is an important starting point, but it is not a complete security strategy. As AI systems become more integrated into enterprise environments, the risks extend to what resources the system can access, how it interprets context, and what actions it is allowed to take across connected tools and workflows.

This creates a gap between visibility and control. Prompt security alone allows security teams to observe prompt activity but falls short of creating a clear understanding of how that activity translates into real-world impact across the organization.

Closing that gap requires a broader approach, one that connects signals across human and AI agent identities, SaaS, cloud, and endpoint environments. It means understanding not just how an AI system is being used, but how that usage interacts with the rest of the digital estate.

Prompt security, in that sense, is less of a standalone solution and more of an entry point into a larger problem: securing AI across the enterprise as a whole.

Explore how Darktrace / SECURE AI brings prompt security to enterprises

Darktrace brings more than a decade of AI expertise, built on an enterprise‑wide platform designed to operate in and understand the behaviors of the complex, ambiguous environments where today’s AI now lives. With Darktrace / SECURE AI, enterprises can safely adopt, manage, monitor, and build AI within their business.  

Learn about Darktrace / SECURE AI here.

Sign up today to stay informed about innovations across securing AI.

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Jamie Bali
Technical Author (AI) Developer
Your data. Our AI.
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