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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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December 22, 2025

The Year Ahead: AI Cybersecurity Trends to Watch in 2026

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Introduction: 2026 cyber trends

Each year, we ask some of our experts to step back from the day-to-day pace of incidents, vulnerabilities, and headlines to reflect on the forces reshaping the threat landscape. The goal is simple:  to identify and share the trends we believe will matter most in the year ahead, based on the real-world challenges our customers are facing, the technology and issues our R&D teams are exploring, and our observations of how both attackers and defenders are adapting.  

In 2025, we saw generative AI and early agentic systems moving from limited pilots into more widespread adoption across enterprises. Generative AI tools became embedded in SaaS products and enterprise workflows we rely on every day, AI agents gained more access to data and systems, and we saw glimpses of how threat actors can manipulate commercial AI models for attacks. At the same time, expanding cloud and SaaS ecosystems and the increasing use of automation continued to stretch traditional security assumptions.

Looking ahead to 2026, we’re already seeing the security of AI models, agents, and the identities that power them becoming a key point of tension – and opportunity -- for both attackers and defenders. Long-standing challenges and risks such as identity, trust, data integrity, and human decision-making will not disappear, but AI and automation will increase the speed and scale of the cyber risk.  

Here's what a few of our experts believe are the trends that will shape this next phase of cybersecurity, and the realities organizations should prepare for.  

Agentic AI is the next big insider risk

In 2026, organizations may experience their first large-scale security incidents driven by agentic AI behaving in unintended ways—not necessarily due to malicious intent, but because of how easily agents can be influenced. AI agents are designed to be helpful, lack judgment, and operate without understanding context or consequence. This makes them highly efficient—and highly pliable. Unlike human insiders, agentic systems do not need to be socially engineered, coerced, or bribed. They only need to be prompted creatively, misinterpret legitimate prompts, or be vulnerable to indirect prompt injection. Without strong controls around access, scope, and behavior, agents may over-share data, misroute communications, or take actions that introduce real business risk. Securing AI adoption will increasingly depend on treating agents as first-class identities—monitored, constrained, and evaluated based on behavior, not intent.

-- Nicole Carignan, SVP of Security & AI Strategy

Prompt Injection moves from theory to front-page breach

We’ll see the first major story of an indirect prompt injection attack against companies adopting AI either through an accessible chatbot or an agentic system ingesting a hidden prompt. In practice, this may result in unauthorized data exposure or unintended malicious behavior by AI systems, such as over-sharing information, misrouting communications, or acting outside their intended scope. Recent attention on this risk—particularly in the context of AI-powered browsers and additional safety layers being introduced to guide agent behavior—highlights a growing industry awareness of the challenge.  

-- Collin Chapleau, Senior Director of Security & AI Strategy

Humans are even more outpaced, but not broken

When it comes to cyber, people aren’t failing; the system is moving faster than they can. Attackers exploit the gap between human judgment and machine-speed operations. The rise of deepfakes and emotion-driven scams that we’ve seen in the last few years reduce our ability to spot the familiar human cues we’ve been taught to look out for. Fraud now spans social platforms, encrypted chat, and instant payments in minutes. Expecting humans to be the last line of defense is unrealistic.

Defense must assume human fallibility and design accordingly. Automated provenance checks, cryptographic signatures, and dual-channel verification should precede human judgment. Training still matters, but it cannot close the gap alone. In the year ahead, we need to see more of a focus on partnership: systems that absorb risk so humans make decisions in context, not under pressure.

-- Margaret Cunningham, VP of Security & AI Strategy

AI removes the attacker bottleneck—smaller organizations feel the impact

One factor that is currently preventing more companies from breaches is a bottleneck on the attacker side: there’s not enough human hacker capital. The number of human hands on a keyboard is a rate-determining factor in the threat landscape. Further advancements of AI and automation will continue to open that bottleneck. We are already seeing that. The ostrich approach of hoping that one’s own company is too obscure to be noticed by attackers will no longer work as attacker capacity increases.  

-- Max Heinemeyer, Global Field CISO

SaaS platforms become the preferred supply chain target

Attackers have learned a simple lesson: compromising SaaS platforms can have big payouts. As a result, we’ll see more targeting of commercial off-the-shelf SaaS providers, which are often highly trusted and deeply integrated into business environments. Some of these attacks may involve software with unfamiliar brand names, but their downstream impact will be significant. In 2026, expect more breaches where attackers leverage valid credentials, APIs, or misconfigurations to bypass traditional defenses entirely.

-- Nathaniel Jones, VP of Security & AI Strategy

Increased commercialization of generative AI and AI assistants in cyber attacks

One trend we’re watching closely for 2026 is the commercialization of AI-assisted cybercrime. For example, cybercrime prompt playbooks sold on the dark web—essentially copy-and-paste frameworks that show attackers how to misuse or jailbreak AI models. It’s an evolution of what we saw in 2025, where AI lowered the barrier to entry. In 2026, those techniques become productized, scalable, and much easier to reuse.  

-- Toby Lewis, Global Head of Threat Analysis

Conclusion

Taken together, these trends underscore that the core challenges of cybersecurity are not changing dramatically -- identity, trust, data, and human decision-making still sit at the core of most incidents. What is changing quickly is the environment in which these challenges play out. AI and automation are accelerating everything: how quickly attackers can scale, how widely risk is distributed, and how easily unintended behavior can create real impact. And as technology like cloud services and SaaS platforms become even more deeply integrated into businesses, the potential attack surface continues to expand.  

Predictions are not guarantees. But the patterns emerging today suggest that 2026 will be a year where securing AI becomes inseparable from securing the business itself. The organizations that prepare now—by understanding how AI is used, how it behaves, and how it can be misused—will be best positioned to adopt these technologies with confidence in the year ahead.

Learn more about how to secure AI adoption in the enterprise without compromise by registering to join our live launch webinar on February 3, 2026.  

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December 22, 2025

Why Organizations are Moving to Label-free, Behavioral DLP for Outbound Email

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Why outbound email DLP needs reinventing

In 2025, the global average cost of a data breach fell slightly — but remains substantial at USD 4.44 million (IBM Cost of a Data Breach Report 2025). The headline figure hides a painful reality: many of these breaches stem not from sophisticated hacks, but from simple human error: mis-sent emails, accidental forwarding, or replying with the wrong attachment. Because outbound email is a common channel for sensitive data leaving an organization, the risk posed by everyday mistakes is enormous.

In 2025, 53% of data breaches involved customer PII, making it the most commonly compromised asset (IBM Cost of a Data Breach Report 2025). This makes “protection at the moment of send” essential. A single unintended disclosure can trigger compliance violations, regulatory scrutiny, and erosion of customer trust –consequences that are disproportionate to the marginal human errors that cause them.

Traditional DLP has long attempted to mitigate these impacts, but it relies heavily on perfect labelling and rigid pattern-matching. In reality, data loss rarely presents itself as a neat, well-structured pattern waiting to be caught – it looks like everyday communication, just slightly out of context.

How data loss actually happens

Most data loss comes from frustratingly familiar scenarios. A mistyped name in auto-complete sends sensitive data to the wrong “Alex.” A user forwards a document to a personal Gmail account “just this once.” Someone shares an attachment with a new or unknown correspondent without realizing how sensitive it is.

Traditional, content-centric DLP rarely catches these moments. Labels are missing or wrong. Regexes break the moment the data shifts formats. And static rules can’t interpret the context that actually matters – the sender-recipient relationship, the communication history, or whether this behavior is typical for the user.

It’s the everyday mistakes that hurt the most. The classic example: the Friday 5:58 p.m. mis-send, when auto-complete selects Martin, a former contractor, instead of Marta in Finance.

What traditional DLP approaches offer (and where gaps remain)

Most email DLP today follows two patterns, each useful but incomplete.

  • Policy- and label-centric DLP works when labels are correct — but content is often unlabeled or mislabeled, and maintaining classification adds friction. Gaps appear exactly where users move fastest
  • Rule and signature-based approaches catch known patterns but miss nuance: human error, new workflows, and “unknown unknowns” that don’t match a rule

The takeaway: Protection must combine content + behavior + explainability at send time, without depending on perfect labels.

Your technology primer: The three pillars that make outbound DLP effective

1) Label-free (vs. data classification)

Protects all content, not just what’s labeled. Label-free analysis removes classification overhead and closes gaps from missing or incorrect tags. By evaluating content and context at send time, it also catches misdelivery and other payload-free errors.

  • No labeling burden; no regex/rule maintenance
  • Works when tags are missing, wrong, or stale
  • Detects misdirected sends even when labels look right

2) Behavioral (vs. rules, signatures, threat intelligence)

Understands user behavior, not just static patterns. Behavioral analysis learns what’s normal for each person, surfacing human error and subtle exfiltration that rules can’t. It also incorporates account signals and inbound intel, extending across email and Teams.

  • Flags risk without predefined rules or IOCs
  • Catches misdelivery, unusual contacts, personal forwards, odd timing/volume
  • Blends identity and inbound context across channels

3) Proprietary DSLM (vs. generic LLM)

Optimized for precise, fast, explainable on-send decisions. A DSLM understands email/DLP semantics, avoids generative risks, and stays auditable and privacy-controlled, delivering intelligence reliably without slowing mail flow.

  • Low-latency, on-send enforcement
  • Non-generative for predictable, explainable outcomes
  • Governed model with strong privacy and auditability

The Darktrace approach to DLP

Darktrace / EMAIL – DLP stops misdelivery and sensitive data loss at send time using hold/notify/justify/release actions. It blends behavioral insight with content understanding across 35+ PII categories, protecting both labeled and unlabeled data. Every action is paired with clear explainability: AI narratives show exactly why an email was flagged, supporting analysts and helping end-users learn. Deployment aligns cleanly with existing SOC workflows through mail-flow connectors and optional Microsoft Purview label ingestion, without forcing duplicate policy-building.

Deployment is simple: Microsoft 365 routes outbound mail to Darktrace for real-time, inline decisions without regex or rule-heavy setup.

A buyer’s checklist for DLP solutions

When choosing your DLP solution, you want to be sure that it can deliver precise, explainable protection at the moment it matters – on send – without operational drag.  

To finish, we’ve compiled a handy list of questions you can ask before choosing an outbound DLP solution:

  • Can it operate label free when tags are missing or wrong? 
  • Does it truly learn per user behavior (no shortcuts)? 
  • Is there a domain specific model behind the content understanding (not a generic LLM)? 
  • Does it explain decisions to both analysts and end users? 
  • Will it integrate with your label program and SOC workflows rather than duplicate them? 

For a deep dive into Darktrace’s DLP solution, check out the full solution brief.

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Carlos Gray
Senior Product Marketing Manager, Email
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