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Introduction
As the digital world races toward AI-driven innovation, organizations are waking up to a new reality: with great power comes great risk. Artificial intelligence, particularly large language models (LLMs), promises enormous benefitsāfrom boosting productivity to transforming entire industries. But this evolution has also opened doors for cybercriminals looking to exploit emerging vulnerabilities.
Trend Micro is taking a frontline position in this battle. Through groundbreaking research and strategic partnerships, the company is shedding light on the dark corners of AI infrastructure. Their recent submission to the MITRE ATLAS framework isnāt just another case studyāitās a crucial playbook for cybersecurity professionals tasked with protecting the next generation of digital assets.
Letās explore the core of their findings, why it matters, and what it means for the global cybersecurity landscape.
AI Infrastructure Under Threat: A Detailed Overview
Back in 2022, cybersecurity leaders began sounding the alarm over the rapidly expanding digital attack surface. Fast forward to today, and the problem has only intensified. The surge in AI adoption has created a larger, more complex infrastructureāone that’s becoming a magnet for cybercriminals.
Trend Micro is responding to this threat with a two-pronged approach: comprehensive research and real-time defense tools powered by AI. The centerpiece of their latest effort is a case study titled AML.CS0028, recently submitted to the elite MITRE ATLAS threat framework. This submission is historicāitās the first ATLAS case study to document a cloud and container-based attack on AI infrastructure.
Only 31 case studies have made it into MITRE ATLAS since 2020. This makes Trend Microās contribution both rare and critically valuable. The study examines a real-world supply chain compromise that targets the AI development pipeline. It highlights how attackers could poison training data, alter AI model outputs, or even hijack the models altogether.
The team uncovered over 8,000 exposed container registriesādouble what was seen in 2023. Alarmingly, 70% of these registries allowed write access, giving cybercriminals the green light to inject malicious models. Within these environments, they identified 1,453 AI models, many using the Open Neural Network Exchange (ONNX) format, which are susceptible to exploitation.
These findings confirm a broader, unsettling trend: attackers are now setting their sights not only on the models themselves but the entire cloud-based infrastructure that supports them. Organizations could face data theft, sabotage, or total model corruptionāleading to damaged reputations and operational chaos.
Trend Microās proactive submission to MITRE ATLAS represents a powerful step toward defense. The case study offers a reproducible attack simulation and is written in ATLAS YAML format for seamless integration with existing tools. More than just theory, this gives cybersecurity professionals a hands-on method to enhance their incident response strategies.
In line with their commitment to community-driven cybersecurity, Trend Micro is also organizing a specialized Pwn2Own AI competition. The goal? To expose vulnerabilities in widely used AI tools and promote collective learning.
What Undercode Say:
The rapid rise of AI in enterprise environments has created a double-edged sword. On one side, we see the undeniable value that generative AI and machine learning bring to industries worldwide. On the other, there’s a stark reality: the technology is still in its infancy when it comes to cybersecurity.
Trend Microās study serves as a wake-up call. It highlights the systemic vulnerabilities that exist not in the AI models alone, but across the entire supply chain that supports them. This includes everything from cloud environments and open-source dependencies to container registries and model storage formats.
Why is this so critical? Because as businesses continue to integrate AI into essential operations, the potential fallout from a cyberattack grows exponentially. A poisoned AI model doesnāt just malfunctionāit can compromise decisions, leak data, and even manipulate users.
The exposed 8,000+ container registries tell us one thing: organizations are still prioritizing speed over security. The fact that 70% allowed write permissions indicates a massive oversight in basic cyber hygiene. When attackers can upload malicious models into trusted environments, it’s not a question of “if” but “when” an attack will happen.
What makes the AML.CS0028 case study exceptional is its practical utility. It maps out the attack stages, offers detection strategies, and even includes test scenarios for defenders. Plus, its compatibility with MITRE ATT\&CK tools gives security teams a head start in threat modeling and defense.
Trend Microās alignment with MITREās Secure AI initiative and their upcoming AI-focused Pwn2Own competition show a long-term vision. Theyāre not just reacting to threats; theyāre actively building a collaborative future where AI can be both innovative and secure.
The future of cybersecurity isnāt siloed. Itās a global effort, where shared knowledge and proactive measures determine who stays ahead. Trend Microās work with MITRE ATLAS doesnāt just protect their clientsāit sets a new standard for what responsible AI deployment should look like.
Fact Checker Results ā
Verified that AML.CS0028 is the first ATLAS case study involving both cloud and container AI infrastructure
Confirmed over 8,000 exposed container registries, with 70% allowing write access
Found 1,453 vulnerable AI models in ONNX format across those registries šš§ š£
Prediction š®
As AI adoption accelerates, threat actors will increasingly target foundational infrastructure over front-end applications. Expect a surge in AI-specific attack tools and techniques, including model poisoning and data exfiltration from training environments. Regulatory bodies and enterprises will likely mandate AI supply chain audits and security certifications by 2026. Cyber resilience won’t be optionalāit will be a prerequisite for AI-driven success.
References:
Reported By: www.trendmicro.com
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