Why Biotech is a Prime Target for Cyberattacks
Biotech, genomics, and precision medicine firms hold some of the world’s most sensitive data—from patient genomes to proprietary drug formulas. This makes them a high-value target for cybercriminals. Genomic data and other health information can fetch far more on the black market than credit card numbers [1]. A single breach can expose priceless research, delay drug development, and even compromise patient safety.
Beyond financial loss, biotech companies must also comply with strict regulations like HIPAA, GDPR, FDA cybersecurity guidelines, and ISO 27001. Failing to secure genomic data can result in legal penalties, reputational damage, and loss of certification. Regulators closely monitor how life science companies protect patient and research data, making cybersecurity a top priority for CTOs and CISOs.
Real-World Biotech Cyber Incidents
COVID-19 Vaccine Trial Disruption (2020): Ransomware locked researchers out of clinical trial data, forcing them to track results manually with pen and paper.[2]
23andMe Data Breach (2023): Attackers exploited weak authentication to leak genetic profiles of 6.9 million users, exposing sensitive ancestry and health data.
Vitagene Cloud Storage Leak: A misconfigured open Amazon S3 bucket exposed customer DNA reports, demonstrating the risks of poor cloud security.
Nation-state actors and industry competitors are known to target biotech firms to steal valuable IP – the US National Counterintelligence Center [3] has flagged biotechnology as a top target for foreign cyber espionage aimed at stealing trade secrets. Traditional penetration testing often misses biotech-specific vulnerabilities like DNA sequencers, IoT medical devices, and AI-driven genomic analysis tools. This is why biotech penetration testing requires a specialized approach.
What is Biotech Penetration Testing?
Biotech penetration testing is a cybersecurity assessment designed specifically for biotech, genomics, and precision medicine companies. It simulates real-world cyberattacks on the unique systems biotech firms rely upon, such as:
Genomic Databases – Protecting on-premise and cloud DNA storage.
Cloud-Based Research Platforms – Securing AWS, Azure, GCP environments.
AI/ML Models – Identifying vulnerabilities in bioinformatics pipelines.
Lab IoT Devices – Ensuring genome sequencers and robotic lab systems are secure.
Clinical Trial Data Systems – Protecting sensitive patient and study information.
Web Portals & APIs – Securing researcher and physician access points.
Unlike generic penetration testing, biotech security assessments include:
Threat Modeling – Identifying unique attack vectors for genomic data.
Regulatory Compliance Checks – Auditing against HIPAA, GDPR, and FDA cybersecurity guidelines.
AI & ML Security Testing – Evaluating adversarial AI attacks and model integrity.
Step-by-Step: How to Simulate a Cyberattack on Genomic Data
1. Define the Scope
Effective biotech penetration testing begins with clearly defining what systems will be tested:
Genomic Data Storage – databases or data lakes (on-premises or cloud) where DNA sequences and patient data are stored.
Cloud Infrastructure – the cloud environments (AWS, Azure, GCP, etc.) hosting research data, analysis pipelines, and collaboration platforms.
AI Models and Analytical Tools – any machine learning models or bioinformatics pipelines that process genomic or clinical data.
Sequencing Labs and IoT Devices – laboratory networks, gene sequencers, robotic lab equipment, and IoT sensors (the Internet-of-Medical-Things) used in research or diagnostics.
Web and API Endpoints – portals for researchers or doctors to access data, APIs for genomic data queries, and mobile or web applications for patients or trial participants.
Defining scope is about listing all these components so nothing important is left untested. Be specific: for example, include the clinical trial management portal but exclude any out-of-scope systems like the corporate HR network (unless they connect to your genomic data environment). The scope sets the boundaries for the “cyberattack simulation” to follow.
2. Threat Modeling: Identifying Likely Attack Scenarios
Before executing simulated attacks, security teams analyze realistic threat scenarios to ensure the penetration test focuses on actual risks, not just generic security checks. This process helps prioritize vulnerabilities based on real-world attack methods.
Key threats include:
Insider Threats – Could an employee copy genomic data before leaving?
Credential Attacks – Could stolen or weak credentials allow unauthorized access to research systems?
Cloud Misconfigurations – Is sensitive genomic data stored in a publicly exposed S3 bucket?
API Exploits – Could an attacker query patient DNA records or research data without proper authorization?
AI Tampering – Can adversaries manipulate training data or introduce adversarial inputs to corrupt research outcomes?
By mapping threats to high-value assets, penetration testers ensure that security assessments address the most pressing risks biotech companies face. Threat modelling ensures the pentest isn’t a blind fishing expedition; it’s guided by plausible attack scenarios (in a real engagement, this might involve creating a formal threat model document linking assets, threats, and security controls). The output of threat modelling is a game plan for the next step, highlighting which attack vectors to try first.
3. Attack Simulation: Hands-on Penetration Testing
Now comes the hands-on hacking – ethically, of course. The team conducts a simulated cyberattack by attempting to exploit vulnerabilities in the scoped systems:
Cloud Security Testing:
Exploit weak IAM policies, misconfigured storage buckets, and leaked access keys.
Attempt privilege escalation within cloud environments.
Identify publicly accessible research data in misconfigured cloud storage.
API & Web Application Hacking:
Probe for SQL injection, broken authentication, and data leakage.
Attempt to bypass authorization controls on genomic APIs.
Check for excessive data exposure through improperly secured API endpoints.
AI/ML Model Exploits:
Test adversarial inputs to manipulate genomic analysis models.
Attempt model extraction to steal intellectual property.
Check for model poisoning attacks that could introduce false research results.
The famous case of malware encoded in DNA that executes when sequenced, while a proof-of-concept, exemplifies the kind of novel attack that AI and biotech systems must be ready for [4].
Medical IoT Device Testing:
Identify vulnerabilities in genome sequencing machines and lab robotics.
Check for default credentials and unpatched firmware on medical IoT devices.
Assess whether an attacker could pivot from IoT systems into critical biotech infrastructure.
Each exploit is documented with clear evidence, ensuring biotech security teams know exactly how to remediate vulnerabilities.
4. Reporting & Mitigation: Strengthening Security Posture
After the penetration test, security teams receive a comprehensive report that details:
Identified vulnerabilities and exploitation methods – A breakdown of security flaws, how they were exploited, and their potential impact.
Technical evidence – Screenshots, logs, and attack scenarios that provide clear documentation of security gaps.
Regulatory and compliance risks – Analysis of how findings align with HIPAA, GDPR, FDA, and other industry regulations, highlighting potential compliance violations.
Actionable remediation steps – Prioritized recommendations to address vulnerabilities, minimize risk exposure, and strengthen security posture.
This final report serves as a roadmap for improving defences and ensuring that security investments effectively mitigate real-world threats.
Conclusion: Why Regular Penetration Testing is Critical
Biotech companies operate at the cutting edge of science and technology—but that also makes them prime targets for cyberattacks. The stakes couldn’t be higher. A breach could compromise years of research, expose sensitive patient data, or derail clinical trials. Regulatory fines and reputational damage are only part of the fallout—once trust is lost, it’s hard to regain.
Cybercriminals aren’t waiting, and neither should you. Proactively identifying security gaps through biotech-specific penetration testing is the smartest way to stay ahead of threats. This isn’t just about compliance; it’s about protecting the future of genomics, precision medicine, and the innovations that define your industry.
Are your genomic databases secure? Could an attacker manipulate your AI-driven research? Is your cloud infrastructure locked down? Hackers won’t wait—and neither should you. The cost of inaction could be millions in lost research, regulatory penalties, and irreversible reputational damage. Protect your biotech breakthroughs before cybercriminals exploit them.
Let’s simulate an attack before they do. Contact us today to test your defences.
