Defending Against Cyber Attacks on San Diego & Barcelona Ports
Discover how Darktrace AI safeguards ports globally against cyber-attacks, including those in San Diego and Barcelona, enhancing maritime cyber security!
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
Andrew Tsonchev
VP, Security & AI Strategy, Field CISO
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03
Oct 2018
Last summer’s wave of ransomware attacks compromised port terminals and disrupted global shipping. Since then, cyber security has quickly risen to the top of the agenda for the maritime sector. Earlier this year, another port was hit with ransomware, and then, last week, the ports of Barcelona and San Diego revealed that they had been the victims of further ransomware attacks.
Whilst the 2017 attacks were globally devastating, there was no evidence that they deliberately targeted particular sectors; port terminals were merely caught in the indiscriminate wave of attacks. However, the widespread disruption these attacks caused across industry – from shipping to manufacturing – drew attention to the risk of IT cyber-attacks propagating into the industrial sector’s critical control systems. Operational Technology within industrial environments had previously been kept relatively separate from IT systems, and, consequently, relatively immune from cyber-attack. These attacks showed that the recent trend in integrating and unifying IT and OT systems had now exposed these systems to such indiscriminate attacks.
The increasing convergence of IT and OT systems shows no signs of slowing, however. Hyper-connected ‘smart’ ports are bringing efficiency and precision while cutting costs. Yet, the intertwining of the physical and digital across ports remains a significant challenge for the cyber security teams tasked with their defense. Without rushing to conclusions, it is perhaps no surprise that the Port of Barcelona is in the process of a “Digital Port project,” launched last year to promote the digitization of the port environment.
Although specifics have not yet been revealed, the recent attacks in Barcelona and San Diego appear to be targeted. Perhaps the inadvertent success of last year’s ransomware campaign inspired attackers to pursue the maritime sector specifically. Disruptions to Operational Technology can be highly detrimental to the maritime sector – these systems oversee critical port and ship systems. Any compromise could inflict reputational harm, significant financial losses, and physical damage. That we would see ransomware attacks specifically targeting ports was foreseeable. Many in the industry have been expecting and preparing for such an eventuality over the last 12 months. Now that attackers are actively targeting them, the protection of OT systems has become critical.
Darktrace has deployed AI to a number of companies in the maritime sector to specifically mitigate and defend Operational Technology. These systems are highly customized and bespoke, and therefore unsuitable for the use of off-the-shelf IT solutions. Darktrace’s cyber AI is able to automatically tailor to OT environments and learn a unique sense of ‘self’, regardless of vendor or technology platform.
Our AI is actively defending ports across the world – such as Harwich Haven Authority and Belfast Harbour – and protecting them against both targeted and indiscriminate attacks on their OT and IT systems. Defending these environments requires the ability to protect all technology systems, from the oldest PLCs and SCADA systems, to the newest IoT devices. Whether in the cloud, on a vessel, or on the mainland, Darktrace is able to passively defend your systems and identify cyber-threats in real time, without any impact or disruption.
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.
React2Shell Reflections: Cloud Insights, Finance Sector Impacts, and How Threat Actors Moved So Quickly
Introduction
Last month’s disclosure of CVE 2025-55812, known as React2Shell, provided a reminder of how quickly modern threat actors can operationalize newly disclosed vulnerabilities, particularly in cloud-hosted environments.
The vulnerability was discovered on December 3, 2025, with a patch made available on the same day. Within 30 hours of the patch, a publicly available proof-of-concept emerged that could be used to exploit any vulnerable server. This short timeline meant many systems remained unpatched when attackers began actively exploiting the vulnerability.
Darktrace researchers rapidly deployed a new honeypot to monitor exploitation of CVE 2025-55812 in the wild.
Within two minutes of deployment, Darktrace observed opportunistic attackers exploiting this unauthenticated remote code execution flaw in React Server Components, leveraging a single crafted request to gain control of exposed Next.js servers. Exploitation quickly progressed from reconnaissance to scripted payload delivery, HTTP beaconing, and cryptomining, underscoring how automation and pre‑positioned infrastructure by threat actors now compress the window between disclosure and active exploitation to mere hours.
For cloud‑native organizations, particularly those in the financial sector, where Darktrace observed the greatest impact, React2Shell highlights the growing disconnect between patch availability and attacker timelines, increasing the likelihood that even short delays in remediation can result in real‑world compromise.
Cloud insights
In contrast to traditional enterprise networks built around layered controls, cloud architectures are often intentionally internet-accessible by default. When vulnerabilities emerge in common application frameworks such as React and Next.js, attackers face minimal friction. No phishing campaign, no credential theft, and no lateral movement are required; only an exposed service and exploitable condition.
The activity Darktrace observed during the React2shell intrusions reflects techniques that are familiar yet highly effective in cloud-based attacks. Attackers quickly pivot from an exposed internet-facing application to abusing the underlying cloud infrastructure, using automated exploitation to deploy secondary payloads at scale and ultimately act on their objectives, whether monetizing access through cryptomining or to burying themselves deeper in the environment for sustained persistence.
Cloud Case Study
In one incident, opportunistic attackers rapidly exploited an internet-facing Azure virtual machine (VM) running a Next.js application, abusing the React/next.js vulnerability to gain remote command execution within hours of the service becoming exposed. The compromise resulted in the staged deployment of a Go-based remote access trojan (RAT), followed by a series of cryptomining payloads such as XMrig.
Initial Access
Initial access appears to have originated from abused virtual private network (VPN) infrastructure, with the source IP (146.70.192[.]180) later identified as being associated with Surfshark
Figure 1: The IP address above is associated with VPN abuse leveraged for initial exploitation via Surfshark infrastructure.
The use of commercial VPN exit nodes reflects a wider trend of opportunistic attackers leveraging low‑cost infrastructure to gain rapid, anonymous access.
Parent process telemetry later confirmed execution originated from the Next.js server, strongly indicating application-layer compromise rather than SSH brute force, misused credentials, or management-plane abuse.
Payload execution
Shortly after successful exploitation, Darktrace identified a suspicious file and subsequent execution. One of the first payloads retrieved was a binary masquerading as “vim”, a naming convention commonly used to evade casual inspection in Linux environments. This directly ties the payload execution to the compromised Next.js application process, reinforcing the hypothesis of exploit-driven access.
Command-and-Control (C2)
Network flow logs revealed outbound connections back to the same external IP involved in the inbound activity. From a defensive perspective, this pattern is significant as web servers typically receive inbound requests, and any persistent outbound callbacks — especially to the same IP — indicate likely post-exploitation control. In this case, a C2 detection model alert was raised approximately 90 minutes after the first indicators, reflecting the time required for sufficient behavioral evidence to confirm beaconing rather than benign application traffic.
Cryptominers deployment and re-exploitation
Following successful command execution within the compromised Next.js workload, the attackers rapidly transitioned to monetization by deploying cryptomining payloads. Microsoft Defender observed a shell command designed to fetch and execute a binary named “x” via either curl or wget, ensuring successful delivery regardless of which tooling was availability on the Azure VM.
The binary was written to /home/wasiluser/dashboard/x and subsequently executed, with open-source intelligence (OSINT) enrichment strongly suggesting it was a cryptominer consistent with XMRig‑style tooling. Later the same day, additional activity revealed the host downloading a static XMRig binary directly from GitHub and placing it in a hidden cache directory (/home/wasiluser/.cache/.sys/).
The use of trusted infrastructure and legitimate open‑source tooling indicates an opportunistic approach focused on reliability and speed. The repeated deployment of cryptominers strongly suggests re‑exploitation of the same vulnerable web application rather than reliance on traditional persistence mechanisms. This behavior is characteristic of cloud‑focused attacks, where publicly exposed workloads can be repeatedly compromised at scale more easily.
Financial sector spotlight
During the mass exploitation of React2Shell, Darktrace observed targeting by likely North Korean affiliated actors focused on financial organizations in the United Kingdom, Sweden, Spain, Portugal, Nigeria, Kenya, Qatar, and Chile.
The targeting of the financial sector is not unexpected, but the emergence of new Democratic People’s Republic of Korea (DPRK) tooling, including a Beavertail variant and EtherRat, a previously undocumented Linux implant, highlights the need for updated rules and signatures for organizations that rely on them.
EtherRAT uses Ethereum smart contracts for C2 resolution, polling every 500 milliseconds and employing five persistence mechanisms. It downloads its own Node.js runtime from nodejs[.]org and queries nine Ethereum RPC endpoints in parallel, selecting the majority response to determine its C2 URL. EtherRAT also overlaps with the Contagious Interview campaign, which has targeted blockchain developers since early 2025.
Darktrace’s honeypot was exploited just two minutes after coming online, demonstrating how automated scanning, pre-positioned infrastructure and staging, and C2 infrastructure traced back to “bulletproof” hosting reflects a mature, well‑resourced operational chain.
For financial organizations, particularly those operating cloud‑native platforms, digital asset services, or internet‑facing APIs, this activity demonstrates how rapidly geopolitical threat actors can weaponize newly disclosed vulnerabilities, turning short patching delays into strategic opportunities for long‑term access and financial gain. This underscores the need for a behavioral-anomaly-led security posture.
Credit to Nathaniel Jones (VP, Security & AI Strategy, Field CISO)
Edited by Ryan Traill (Analyst Content Lead)
Appendices
Indicators of Compromise (IoCs)
146.70.192[.]180 – IP Address – Endpoint Associated with Surfshark
Runtime Is Where Cloud Security Really Counts: The Importance of Detection, Forensics and Real-Time Architecture Awareness
Introduction: Shifting focus from prevention to runtime
Cloud security has spent the last decade focused on prevention; tightening configurations, scanning for vulnerabilities, and enforcing best practices through Cloud Native Application Protection Platforms (CNAPP). These capabilities remain essential, but they are not where cloud attacks happen.
Attacks happen at runtime: the dynamic, ephemeral, constantly changing execution layer where applications run, permissions are granted, identities act, and workloads communicate. This is also the layer where defenders traditionally have the least visibility and the least time to respond.
Today’s threat landscape demands a fundamental shift. Reducing cloud risk now requires moving beyond static posture and CNAPP only approaches and embracing realtime behavioral detection across workloads and identities, paired with the ability to automatically preserve forensic evidence. Defenders need a continuous, real-time understanding of what “normal” looks like in their cloud environments, and AI capable of processing massive data streams to surface deviations that signal emerging attacker behavior.
Runtime: The layer where attacks happen
Runtime is the cloud in motion — containers starting and stopping, serverless functions being called, IAM roles being assumed, workloads auto scaling, and data flowing across hundreds of services. It’s also where attackers:
Weaponize stolen credentials
Escalate privileges
Pivot programmatically
Deploy malicious compute
Manipulate or exfiltrate data
The challenge is complex: runtime evidence is ephemeral. Containers vanish; critical process data disappears in seconds. By the time a human analyst begins investigating, the detail required to understand and respond to the alert, often is already gone. This volatility makes runtime the hardest layer to monitor, and the most important one to secure.
What Darktrace / CLOUD Brings to Runtime Defence
Darktrace / CLOUD is purpose-built for the cloud execution layer. It unifies the capabilities required to detect, contain, and understand attacks as they unfold, not hours or days later. Four elements define its value:
1. Behavioral, real-time detection
The platform learns normal activity across cloud services, identities, workloads, and data flows, then surfaces anomalies that signify real attacker behavior, even when no signature exists.
2. Automated forensic level artifact collection
The moment Darktrace detects a threat, it can automatically capture volatile forensic evidence; disk state, memory, logs, and process context, including from ephemeral resources. This preserves the truth of what happened before workloads terminate and evidence disappears.
3. AI-led investigation
Cyber AI Analyst assembles cloud behaviors into a coherent incident story, correlating identity activity, network flows, and Cloud workload behavior. Analysts no longer need to pivot across dashboards or reconstruct timelines manually.
4. Live architectural awareness
Darktrace continuously maps your cloud environment as it operates; including services, identities, connectivity, and data pathways. This real-time visibility makes anomalies clearer and investigations dramatically faster.
Together, these capabilities form a runtime-first security model.
Why CNAPP alone isn’t enough
CNAPP platforms excel at pre deployment checks all the way down to developer workstations, identifying misconfigurations, concerning permission combinations, vulnerable images, and risky infrastructure choices. But CNAPP’s breadth is also its limitation. CNAPP is about posture. Runtime defense is about behavior.
CNAPP tells you what could go wrong; runtime detection highlights what is going wrong right now.
It cannot preserve ephemeral evidence, correlate active behaviors across domains, or contain unfolding attacks with the precision and speed required during a real incident. Prevention remains essential, but prevention alone cannot stop an attacker who is already operating inside your cloud environment.
A recent incident detected by Darktrace / CLOUD highlights how cloud compromises unfold, and why runtime visibility is non-negotiable. Each step below reflects detections that occur only when monitoring behavior in real time.
1. External Credential Use
Detection: Unusual external source for credential use: An attacker logs into a cloud account from a never-before-seen location, the earliest sign of account takeover.
2. AWS CLI Pivot
Detection: Unusual CLI activity: The attacker switches to programmatic access, issuing commands from a suspicious host to gain automation and stealth.
3. Credential Manipulation
Detection: Rare password reset: They reset or assign new passwords to establish persistence and bypass existing security controls.
4. Cloud Reconnaissance
Detection: Burst of resource discovery: The attacker enumerates buckets, roles, and services to map high value assets and plan next steps.
5. Privilege Escalation
Detection: Anomalous IAM update: Unauthorized policy updates or role changes grant the attacker elevated access or a backdoor.
6. Malicious Compute Deployment
Detection: Unusual EC2/Lambda/ECS creation: The attacker deploys compute resources for mining, lateral movement, or staging further tools.
7. Data Access or Tampering
Detection: Unusual S3 modifications: They alter S3 permissions or objects, often a prelude to data exfiltration or corruption.
Only some of these actions would appear in a posture scan, crucially after the fact. Every one of these runtime detections is visible only through real-time behavioral monitoring while the attack is in progress.
The future of cloud security Is runtime-first
Cloud defense can no longer revolve solely around prevention. Modern attacks unfold in runtime, across a fast-changing mesh of workloads, services, and — critically — identities. To reduce risk, organizations must be able to detect, understand, and contain malicious activity as it happens, before ephemeral evidence disappears and before attacker's pivot across identity layers.
Darktrace / CLOUD delivers this shift by turning runtime, the most volatile and consequential layer in the cloud, into a fully defensible control point through unified visibility across behavior, workloads, and identities. It does this by providing:
Real-time behavior detection across workloads and identity activity
Autonomous response actions for rapid containment
Automated forensic level artifact preservation the moment events occur
AI-driven investigation that separates weak signals from true attacker patterns
Live cloud environment insight to understand context and impact instantly
Cloud security must evolve from securing what might go wrong to continuously understanding what is happening; in runtime, across identities, and at the speed attackers operate. Unifying runtime and identity visibility is how defenders regain the advantage.
