I’m thrilled to sit down with Matilda Bailey, a renowned networking specialist whose expertise in cellular, wireless, and next-gen solutions has made her a leading voice in the cybersecurity realm. With a deep understanding of the evolving threats facing data centers, Matilda offers invaluable insights into securing critical infrastructure in an era of rapid technological change. In this interview, we dive into pressing issues like supply chain vulnerabilities, the risks of third-party integrations, the impact of AI on cybersecurity, and the often-overlooked dangers of outbound traffic and routing security. We also explore emerging threats like AI voice cloning and the importance of maintaining fundamental security practices in the face of sophisticated attacks.
How have supply chain dependencies evolved into such a significant target for cybercriminals in recent years?
Supply chain dependencies have become a prime target because they’re often the path of least resistance for attackers. As organizations increasingly rely on external providers for everything from hardware to software components, the attack surface expands exponentially. Cybercriminals know that a single compromised vendor can provide access to multiple downstream organizations, amplifying the impact of their efforts. The complexity of modern supply chains also means that many companies don’t even fully understand their own dependencies, making it easier for attackers to exploit gaps that go unnoticed until it’s too late.
What practical steps can data center operators take to thoroughly vet their third-party providers and integrations?
First and foremost, data center operators need to establish rigorous vetting processes that go beyond surface-level checks. This means conducting detailed security assessments of vendors before onboarding, including reviewing their compliance with industry standards and their incident response history. It’s also critical to enforce strict contractual agreements that mandate transparency about their own supply chains. Regular audits and continuous monitoring of third-party activities can help catch potential issues early. Finally, adopting a “trust but verify” mindset—using tools to independently validate the security of integrations—can make a huge difference.
Why are APIs often considered a weak point in data center security despite their widespread use?
APIs are a weak point because they’re essentially open doors designed for connectivity, often prioritizing functionality over security. Many organizations don’t have full visibility into the security posture of the API providers they rely on, and misconfigurations or outdated endpoints can be easily exploited. Attackers see APIs as a trusted entryway—if they can compromise one, they often gain direct access to sensitive systems or data. The sheer volume of API traffic in modern data centers also makes it hard to detect malicious activity amidst the noise, compounding the problem.
How can organizations strengthen their oversight of API providers’ security practices?
Organizations need to start by demanding transparency from their API providers, including detailed documentation of their security protocols and regular updates on vulnerability patches. Implementing robust API gateway solutions can help monitor and control traffic, ensuring that only authorized requests are processed. It’s also wise to conduct periodic security assessments of these providers, either internally or through third-party auditors. Lastly, enforcing strict access controls and encryption standards for API interactions can minimize the risk of unauthorized access even if a provider’s defenses falter.
How is the rise of AI reshaping the cybersecurity landscape for data centers, both in terms of new threats and defensive strategies?
AI is a double-edged sword for data centers. On the threat side, attackers are leveraging AI to automate and scale their campaigns—think faster phishing attacks, more convincing social engineering, or even generating malicious code at an unprecedented pace. On the defense side, AI empowers us to analyze vast amounts of data in real time, identifying anomalies that might signal a breach before it escalates. However, the challenge lies in staying ahead; attackers can also use AI to adapt to our defenses, creating a constant cat-and-mouse game that requires us to innovate continuously.
What unique risks do pre-trained AI models introduce, and how can organizations safeguard against them?
Pre-trained AI models can be a goldmine for attackers because they’re often treated as black boxes—organizations adopt them without fully understanding their internals. If a model is compromised during training or distribution, it could contain hidden malicious code or backdoors that activate under specific conditions. To protect against this, companies should source models only from trusted providers and implement strict validation processes before deployment. Treating these models as critical intellectual property, with restricted access and robust monitoring, is also essential to prevent tampering or theft.
What are the major risks tied to outbound traffic from data centers, and how can they impact an organization’s reputation?
Outbound traffic risks are often underestimated, but they can be devastating. If malicious traffic—like spam or attack commands—originates from a data center’s IP address, it can lead to the organization being blocklisted by other networks, disrupting legitimate operations. Even worse, it can damage the company’s reputation if it’s seen as a source of cyberattacks, eroding trust with partners and customers. This often happens when free VPN services or compromised systems use the data center’s infrastructure as an exit point, making it look like the organization itself is the bad actor.
Can you walk us through the key steps of implementing MANRS actions to enhance internet routing security?
Implementing MANRS—Mutually Agreed Norms for Routing Security—starts with maintaining accurate records in the Internet Routing Registry to ensure your routing information is up to date and verifiable, preventing unauthorized route changes. Collaboration is also key; working with other network operators to share threat intelligence and coordinate defenses strengthens the ecosystem. Finally, deploying tools to validate routing authenticity helps ensure that traffic follows trusted paths. It’s about building a collective commitment to routing hygiene that benefits everyone connected to the internet.
What specific dangers do AI voice cloning attacks pose to data centers, and how can they prepare for this emerging threat?
AI voice cloning, or vishing, is a growing concern because it’s so accessible—tools to create convincing fake audio are widely available, and the hardware needed is cheap. Attackers can impersonate executives or trusted partners to trick employees into revealing sensitive information or granting access to systems. For data centers, this could mean unauthorized entry to critical infrastructure or data breaches. Preparation involves training staff to recognize social engineering tactics, implementing strict verification processes for voice-based requests, and exploring advanced detection tools that can flag synthetic audio.
Looking ahead, what is your forecast for the future of data center security in the face of evolving AI-driven threats?
I believe data center security will become even more complex as AI-driven threats continue to evolve. We’ll see attackers using AI not just for scale but for precision—crafting highly targeted attacks that exploit specific vulnerabilities in real time. On the flip side, I expect AI to play a bigger role in defenses, with predictive analytics and automated response systems becoming standard. The key will be fostering a culture of adaptability; data centers that can quickly integrate new tools and strategies while maintaining strong fundamentals will be best positioned to weather the storm.
