Life Sciences Cybersecurity in 2025

AI has been the main talking point this year, showing up in nearly every product and proposal. But many of the key risks are not new, and most environments are still shaped by issues like legacy infrastructure, incomplete recovery planning, and compliance drift.

At GISEC Global 2025, healthcare-focused sessions reflected this. The emphasis was less on speculative AI topics and more on persistent operational challenges. Not every conversation about AI spaceships exploring the vastness of enterprise architecture leads to anything actionable. Meanwhile, attackers are using AI to accelerate phishing and impersonation, but the underlying techniques remain familiar.

1. Focus on Protecting Identity

Most incidents begin with compromised credentials, not with unpatched systems. Human-driven attacks like phishing and credential reuse are still the main entry point. In Q1 2025, Cisco Talos observed phishing in 50% of real-world incidents. AI is making it faster and more convincing. In hybrid cloud environments, identity is the perimeter.

Phishing-resistant authentication is a must in 2025. Passkeys, now supported by Microsoft Entra ID, are tied to devices and can replace weaker methods like SMS or push notifications. If you are issuing company iPhones, you might as well make full use of them.

Zero Trust is mandatory in 2025. Verify explicitly, enforce least privilege, and monitor continuously. Many life sciences environments rely on implicit trust and overly broad access, especially in Active Directory. It’s worth estimating what it would take to fix that.

Security awareness is part of defense in depth. AI makes phishing harder to detect. Users should keep following taught patterns, questioning context, and reporting things that feel wrong. Good habits matter most. There are plenty of tools to support awareness training. Pick one, roll it out and make the most out of it.

2. Fix What’s Already Broken Before Building New Controls

Legacy systems, missing access reviews, and weak change control are still common in GxP environments. Known vulnerabilities in legacy systems might remain unpatched for years, while it also might not be possible to easily isolate them. The 2025 DBIR reports that 41% of breaches involved known but unremediated vulnerabilities.

At GISEC 2025, the main concerns raised in healthcare sessions were not about AI. They were about unclear ownership, technical debt, and fragile disaster recovery setups.

If your Computer System Validation (CSV) program was created mainly to satisfy auditors but does not reflect how systems are used or maintained, that is worth addressing.

Validation that exists only on paper creates blind spots, especially in legacy infrastructure or SaaS environments with skipped controls. Security is a core part of CSV and GAMP. If access controls, audit trails, or incident handling are weak or missing, the system cannot be considered truly validated, regardless of the documentation.

Before writing new policies for AI, review your existing risk register. You will likely find items that are more urgent, more impactful, and easier to fix.

3. Make Sure Your BCDR Plan Actually Works

Disruptions will occur. Ransomware, outages, and infrastructure failures are not hypothetical. Even if your security controls are perfect, your supply chain never is. Business Continuity and Disaster Recovery (BCDR) plans are often written but untested, or based on outdated assumptions.

A functional BCDR plan includes clear responsibilities, tested recovery steps, and timeframes that reflect how systems operate. Full-scale testing requires coordination across teams and may involve planned downtime, but the investment is rarely wasted. If you sit down and calculate the cost of even a single extended outage, the return on proper BCDR planning becomes obvious. You do not need to invent anything from scratch, relevant ISO or NIST standards provide everything you might need.

If the question “when was the last time you tested the backups?” makes you slightly anxious, the direction should be clear.

4. User Experience is a Security Control

Most policy violations start with good intentions. Someone wants to send a file quickly, get input, or try a tool that helps them work faster. That is how shadow IT begins. It is also how insider threats and data leaks happen.

When secure tools are missing or too limited, people turn to whatever works. That could be personal email, public file shares, or an AI tool in the browser. Blocking these services does not remove the need. Users will find a way.

With AI in particular, what’s pasted there is gone. Even if chat history is cleared, the data still passed through systems you do not control. In most cases, even the vendor cannot pull the data out.

Usability is not a nice-to-have. If that risk matters, the better path is to build secure, usable systems that match how people actually work. This includes internal AI platforms, collaboration tools, and access models that make the secure path the easiest one. That is where we come in.

At MIGx, we help life sciences organizations build secure AI systems that unlock real productivity gains, accelerate time to market, and stay compliant with changing regulatory expectations. We also support broader enterprise IT security and governance, aligning controls with business priorities.

Secure AI System Design:

• Internal platforms tailored to specific use cases, with model integrity protections such as adversarial hardening, cryptographic safeguards, and intellectual property controls
• Privacy-aware architecture using differential privacy, role-based access, and encrypted data pipelines
• Real-time monitoring, incident response playbooks, audit trails, and alignment with AI-specific frameworks like ISO/IEC 42001

Enterprise Security and Governance:

• Business continuity and disaster recovery, from impact assessments to tested implementations
• Identity and access security, including Microsoft Entra ID, Conditional Access, Zero Trust design, and passkey rollout
• GxP-aligned governance support, including reviews of risk registers, access models, and validation documentation