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
Justin Fier
SVP, Red Team Operations
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23
Sep 2021
Back in December, we predicted that supply chain attacks would overtake CEO fraud as a top cyber security concern. This year, the importance of supply chains has been brought to the forefront by a series of disruptions hitting the headlines.
From blockages in the Suez Canal to microchip shortages affecting automotive production, from fighting for toilet paper rolls to Australian gas prices spiking because Colonial Pipeline stopped operations, 2021 showed us that our major supply chains are not only vulnerable but critical to our daily lives.
Countries and organizations have been shocked by their dependency on global systems and third-party vendors. And whether it’s meat, oil, or software, threat actors have increasingly targeted security vulnerabilities to bring production lines to a standstill. The world has been taken aback by the recent string of supply chain cyber-attacks – including the SolarWinds hack revealed in December 2020 and the Kaseya attack that occurred over the Fourth of July weekend.
Nothing about this should come as a surprise. The supply system has been a target for as long as warfare has existed. Logistics – the practice of having your bullets and bread in the right place at the right time – is one of the core pillars of war. The term was coined by Antoine-Henri Jomini, a general under Napoleon, who in ‘The Art of War’ argues that although strategy and tactics comprise the conduct of warfare, logistics is the means. Without logistics in place, defeat is inevitable.
At the time Jomini was writing, the size of Napoleon’s campaigns required a new approach. Napoleon had amassed the largest army Europe had ever seen and secured swift victories across the continent through effective logistics management, including ‘Living off the Land’ techniques, agreements with allies, military train regiments, and even turning a whole city into a supply center during the Ulm Campaign.
And yet logistics ultimately led to Napoleon’s downfall. In 1812, as the Russian troops retreated, burning everything in their wake, Napoleon’s Grande Armée ran out of supplies and were forced to eat their horses – and eventually each other. Only 2% of the army survived.
“The masterpiece of a successful general is to starve his enemy.” – Frederick the Great
Fast-forward to the twentieth century and attacking the supply system had become a central part of offensive campaigns. Cutting off supplies during the Blockade of Germany played a decisive role in the Allied victory. Since then – from the tonnage wars to strafing to flying in provisions during the Berlin Airlift – logistics have proven influential in determining a conflict’s outcome.
Brave old world
The disruption of supply chains this year is nothing new – it is simply a continuation of age-old military strategy. In World War I, ships were a subversive force and were used in naval blockades to cut off supply lines. In World War II, aircraft allowed the attacker to strike behind enemy lines and destroy supply vehicles and railway infrastructure. Now, cyber is being leveraged in the same way: to undermine physical borders and bring a supply system to its knees.
There are cyber-attacks which disrupt the supply chain, and there are those which leverage the supply chain to spread. The latter are particularly dangerous because they exploit our human tendency for trust. If an email comes from a trusted source or an application is managed by a trusted supplier, we tend to let our guards down. So rather than trying to breach large companies directly, threat actors can get in through a side door, using one undefended individual to compromise an organization and then an entire system.
These two types are not mutually exclusive. NotPetya infected its victims through a Ukrainian tax software program, which eventually led to Maersk, the largest container shipping company in the world, halting operations for nearly two weeks.
Hitting the consumer where it hurts
This tactic has been waged by nation states for espionage, as we saw with SolarWinds and the Hafnium campaigns, and by organized crime to hold large numbers of businesses to ransom. We’ve heard of double extortion ransomware, but the emergence of triple extortion – where ransomware actors threaten not only the victim but any related third parties or customers, demanding a ransom to keep the data private – signals a new avenue of profitability for cyber-criminals.
We shouldn’t be surprised that the supply chain has fallen simultaneously into the firing line of cyber-crime and cyber-war. In the words of Henry E. Eccles, a rear admiral in the US Navy, logistics is the economic element of the military, but equally it is the military element of the economy. Logistics bridges the gap between economics and warfare: the supply chain is pivotal for both.
Underestimating your supply chain risk therefore can have serious consequences for your business, just as for a battle. How your suppliers work, the defenses they have in place, and what happens if they get compromised, are all important questions to ensure the success of your company. And a cyber security posture which can detect third-party breaches, a tonal language shift in an email or a binary from a trusted source acting anomalously, is an essential layer of any defensive solution.
This blog post has previously appeared on Tecnogazzetta, packagingrevolution.net and LineaEDP.
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.
Security After Signatures: Operating in a World of Pre‑CVE Disclosure Exploitation, Collapsed Trust Boundaries, and Autonomous Systems
Three shifts have reshaped what it means to defend an enterprise securely.
First, exploitation often begins before defenders have a Common Vulnerabilities and Exposures (CVE) identifier, a security advisory, or an entry in the Cybersecurity and Infrastructure Security Agency's (CISA) Known Exploited Vulnerabilities (KEV) catalog.
Secondly, the trust boundary has moved beyond the network edge into identities, tokens, APIs, and Software-as-a-Service (SaaS) workflows.
Third, an increasing share of business activity is executed through automation, integrations, and AI agent-like systems that can act faster than teams can verify intent.
If your security model still relies on detecting known bad artefacts, triaging isolated alerts, and waiting for confirmation before acting, you are already behind the threat.
This is not a failure of security teams; it’s a failure of the operating model to keep pace with how the environment has changed.
A SOC built around alerts and signatures assumes that malicious activity will eventually surface as an event. In real incidents, however, the decisive evidence is rarely a single event. Instead, it is a chain of individually explainable actions that only appears malicious once you connect the dots across identity, non-human identity, cloud, email, SaaS, operational technology (OT), and network telemetry.
The defenders succeeding today observe behaviors, link them into sequences, understand what those sequences mean, and contain impact before the full story unfolds. That is the operating model the current threat environment demands.
In one example, Darktrace observed a sequence of subtle but strategically significant anomalies within a customer environment that later aligned with exploitation of CVE‑2025‑0994 in Trimble Cityworks by likely Chinese-nexus threat actors. Behavioral indicators were visible at least 18 days before public disclosure, with related anomalies emerging 40 to 50 days earlier during the intrusion window.
This case illustrates a familiar pattern: clusters of weak‑signal anomalies combing to form an actionable picture of intrusion long before a CVE is published. Such activity reflects long‑horizon, option‑preserving operator models often associated with mature state‑linked activity.
Figure 1: Darktrace’s detection of malicious exploitation of CVE 2025-0994, later tied to Chinese-nexus threat actors targeting critical national infrastructure (CNI) in the US, weeks before public disclosure.
Throughout 2025 and 2026, Darktrace has continued to observe the value of anomaly-based detections across a range of incidents.
CVE
CVE public disclosure date
Darktrace detection date
Days between detection of exploitation and CVE public disclosure
CVE-2025-0994Trimble Cityworks
2025-02-06
2025-01-19
18 days
CVE-2025-24183Apache
2025-03-10
2025-02-18
20 days
CVE-2025-10035Fortra GoAnywhere
2025-09-18
2025-09-11
7 days
CVE-2026-0257PAN-OS
2026-05-13
—
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Identity is the real control plane
The second shift is that identity has replaced perimeter as the primary control plane. As Darktrace’s Annual Threat Report 2026 illustrated, identity remains the main challenge in defending against modern intrusions. A clear example is the Adversary-in-the-Middle (AiTM) case published by Darktrace in December 2025. A phishing email led to the compromise of an Office 365 account. Session hijacking bypassed multi-factor authentication (MFA), and the compromised account was used for follow-on phishing and persistence activities including the creation of malicious email rules.
Every step in that sequence mattered. A successful login alone does not prove legitimacy. An inbox rule, on its own, may not appear catastrophic. Mail activity, viewed in isolation, may seem operationally normal. But the behavioral chain tells a different story: credential theft, token abuse, persistence, and onward compromise through a trusted identity.
This is why the question is no longer “Did the user authenticate successfully”. The more important question is, “Does this identity action make sense right now, in this context, given what came before it?” The AiTM case shows how identity can be compromised. In practice, however, attacks rarely remained confined to identity alone.
In another Darktrace case, a compromised SaaS account triggered activity across the email, SaaS, and network layers, including inbox rule changes, phishing propagation, and connections to suspicious infrastructure. Viewed in isolation, none of these events were decisive. Together, however, they formed a behavioral sequence that revealed the intrusion, with the full attack story automatically correlated and surfaced to defenders by Darktrace’s Cyber AI Analyst.
Figure 2: Cyber AI Analyst correlated and appended additional events to the incident, including other users who connected to the suspicious redirect link after outbound phishing emails were sent.
AI accelerates the threat
The third shift is the one many teams still underestimate: trusted tooling, integrations, and AI agent-like systems can create actions that appear legitimate but are strategically dangerous.
The shift becomes clearer when examining how governments are now framing AI risk. In 2026, guidance published by CISA, UK’s National Cyber Security Centre (NCSC) and Five Eyes partners warned that agentic systems expand attack surfaces, accumulate privilege, and can behave in ways that are difficult to predict or explain [1]. The advice is simple: assume unexpected behavior and design controls around it.
The real risk is not AI usage. It is unknown autonomy: systems with credentials, data access, and action paths that can execute workflow steps without sufficient behavioral validation, traceability, or human oversight. Darktrace’s Model Context Protocol (MCP) risk analysis provides a useful framework for understanding this challenge. Over-privileged agents, content injection, and tool abuse become high-consequence risks when connected systems can dynamically retrieve data, execute actions, and communicate externally.
Whether security teams like it or not, AI is already in the enterprise. It will help drive innovation, but it will also be abused, whether accidentally or maliciously. In each of the cases below, AI either scaled the attacker, built the tooling, or existed within the environment as something to exploit or misuse.
1. AI as an Attack Multiplier
In one campaign targeting Mexican government entities, a single operator used commercial AI platforms to generate exploits, automate reconnaissance, and process large volumes of data, compressing work that would traditionally have required an entire team into a single workflow [2].
Attempted AI exploitation is now appearing within customer environments. In one case involving an automation technology manufacturer, a compromised LLM proxy was seemingly used as a stepping stone to access additional AI services. When that attempt failed, the attacker pivoted to cryptomining.
What is clear is that the AI layer has already become an asset worth probing, exploiting, and pivoting through. It is also clear that defenders benefit from rapidly understanding how these activities connect. In this case, Cyber AI Analyst automatically pieced together the intrusion, while Darktrace’s Managed Threat Detection service alerted to the customer, enabling the activity to be contained before it could progress further.
Figure 3: Cyber AI Analyst's investigation into a compromised LLM proxy that was abused for cryptomining activity.
AI as a trusted but dangerous actor
This does not require a cinematic vision of “rogue AI.” The Salesloft incident provides a more grounded example, where AI and automation operate with legitimate access but served malicious intent. In that case, attackers abused compromised OAuth tokens associated with the Drift AI chat agent to export significant volumes of data from Salesforce environments.
The activity resembled legitimate API usage and relied on trusted SaaS integrations rather than malware or other obvious signs of intrusion. That is precisely the challenge. Traditional security controls are good at detecting forced entry, but far less effective when a trusted application integration behaves in a way that is technically permitted yet operationally harmful.
In these scenarios, the security challenge shifts from validating access to validating behavior.
This is what that looks like in practice: AI-linked identities executing legitimate actions that require behavioral validation rather than access validation.
Figure 4: Darktrace / SECURE AI highlights anomalous activity across AI identities, surfacing critical behavior that requires validation and containment.
Early observations from Darktrace / SECURE AI deployments reinforce this reality. Across Darktrace's observed fleet, AI service connections per deployment increased 13% during the first half of 2026, reaching over 16 million connections overall. The typical organisation now interacts with seven different AI providers, evidence that AI is no longer operating at the edges of the enterprise. It is increasingly woven into day-to-day business activity.
The most common risks are not compromised models or advanced AI attacks. Instead, they stem from employees and business functions exposing sensitive information through entirely legitimate-looking interactions. Darktrace has observed repeated submission of personally identifiable information (PII), tax information, identification documents, and medical data into LLM prompts, alongside widespread use of unsanctioned (shadow) AI services and growing AI activity from mobile devices.
For defenders, the challenge is increasingly one of context: understanding when legitimate business use crosses into material risk, while preserving privacy and user trust.
Conclusion
Across all three shifts, the pattern is the same: behavior precedes understanding. Security teams are not losing because adversaries have become invisible. An increasingly outdated security model assumes that malicious activity will reveal itself cleanly and early. It no longer does.
In 2026 and beyond, defenders win by understanding behavioral sequences, continuously validating trust, and acting before certainty becomes hindsight. That is security after signatures. That is security in the AI era.
Credit to: Daniel Levy, Threat Hunting Data Scientist
2026年6月12日、DarktraceはLiteLLM-Proxyという名前のAmazon Web Service (AWS) EC2インスタンスから暗号通貨マイニング発生中とみられるアクティビティを観測しました。このインスタンスはLiteLLMアクティビティをサポートしており、Amazon Bedrockリソースへのアクセス権を有するインスタンスプロファイルと関連付けられていました。
