Pen Testing AI and Large Language Models (LLMs)

Detecting Artificial Intelligence (AI) Vulnerabilities

Understanding AI Cybersecurity Risks and How to Mitigate Them

With the rapid rise of AI utilisation, new cybersecurity risks have emerged. Generative AI, such as ChatGPT and Large Language Models (LLMs), offers exceptional benefits in scalability, efficiency, and speed but introduces new cybersecurity challenges. Ensuring the security of your AI applications, including chatbots, is crucial to protect against vulnerabilities like insecure code, data exposure, and expanded attack surfaces. Conducting penetration testing on AI and LLMs is vital for identifying and mitigating these risks, preventing potential exploitation.

Examples of AI Security Integration

Financial Services
AI-driven algorithms are used to detect fraudulent transactions, but they also need robust security measures to prevent tampering and ensure reliability.
AI models assist in patient diagnosis and treatment recommendations. Securing these models against cyber threats is essential to maintain patient trust and data integrity.

AI chatbots enhance customer service by providing quick responses to inquiries. Ensuring these chatbots are secure helps protect sensitive customer data and maintain service quality.

By proactively testing and securing AI systems, we can harness their full potential while safeguarding against emerging threats.

What Cybersecurity Risks Does AI Pose?

As AI technologies become more prevalent, they introduce new and unique cybersecurity risks:

  • Vulnerable Code: AI applications often contain complex code that may have security vulnerabilities. These weaknesses can be exploited by attackers to gain unauthorised access or control.
  • Exposure of Sensitive Data: AI systems typically handle large amounts of sensitive data. If not properly secured, this data can be exposed to malicious actors, leading to data breaches and loss of confidentiality.
  • Larger Attack Surfaces: The integration of AI into various systems expands the attack surface, providing more entry points for attackers to exploit. This increased complexity makes it more challenging to secure every aspect of the AI environment.
  • Bias and Manipulation: AI models can be manipulated to produce biased or incorrect outputs, potentially leading to harmful decisions or actions based on skewed data.

By identifying and addressing these risks, organisations can protect their AI systems and the valuable data they process.

How Does Pen Testing Reduce AI Risk?

When deploying a new AI-based experience, whether internally or externally, you’re introducing a new potential vector of attack. The Open Web Application Security Project (OWASP) and other frameworks have identified critical vulnerabilities in AI and LLMs that provide attackers with significant leverage. Penetration testing (pen testing) plays a crucial role in reducing AI risk by emulating an adversary’s interaction with your AI modules. Here’s how pen testing works:

  • Emulating Adversaries: Pen testers simulate real-world attack scenarios to identify vulnerabilities in AI systems. This process involves interacting with AI modules as an attacker would, probing for weaknesses.
  • Identifying Flaws: Pen tests uncover flaws in AI logic, data handling, and integration points with other systems.
  • Providing Remediation Recommendations: After identifying vulnerabilities, pen testers provide actionable recommendations to fix these issues, enhancing the security of your AI applications.

CyberCrowd can test a wide range of AI applications to ensure their security:

Chatbots in Web Applications
AI chatbots interacting with customers can be tested for security flaws that might expose sensitive data or allow unauthorized access.
GenAI for Customer Guidance
AI tools guiding customers through the buying journey need to be secure to protect customer data and transaction integrity.
Internal Operational Tools

AI systems used internally to improve operational efficiency must be tested to prevent internal threats and data breaches.

Whether deploying a chatbot, using GenAI, or implementing internal AI tools, these applications share common potential flaws and cybersecurity risks that can be identified through CyberCrowd’s pen testing services.

Spend time with our experts and discuss current and future requirements.

Hidden AI Risks and Continuous Pen Testing

AI can introduce risks into your environment even without direct implementation. For example, if an employee uses AI to help write code, it might inadvertently introduce vulnerabilities. Continuous pen testing is essential to identify and mitigate these risks, ensuring ongoing protection for your systems.

Continuous Pen testing can uncover various AI vulnerabilities, such as:

Injection Attacks
Attackers might inject malicious code into AI models to manipulate their behaviour.
Data Poisoning
Attackers can corrupt the data used to train AI models, leading to inaccurate or harmful outputs.
Model Inversion
Unauthorised individuals can infer sensitive data used to train AI models.

CyberCrowd’s elite team of pen testers provides detailed reports on identified vulnerabilities. Our state-of-the-art Pen Testing Client Portal enables real-time data sharing, allowing you to quickly address and remediate security issues.

The CyberCrowd Penetration Testing Client Portal

Our state-of-the-art client portal offers a secure and efficient interface for customers to access and manage their cybersecurity assessments. Gain real-time visibility into testing results, risk scores, and tailored remediation recommendations. This enables swift and effective corrective actions, enhancing your security posture promptly.

Secure Your AI with CyberCrowd

CyberCrowd’s penetration testing services not only identify vulnerabilities but also offer clear remediation advice to strengthen your AI systems. Contact us today to fortify your organisation’s defences and ensure the security of your AI applications.

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Spend time with our experts and discuss current and future requirements.

By leveraging our expertise and advanced testing tools, you can confidently navigate the evolving cybersecurity landscape and protect your AI investments.