De-risk Generative AI: Enterprise TruRisk Platform Advances to Secure AI and LLM Workloads
As we stand at the frontier of technological innovation, artificial intelligence (AI) and large language models (LLMs) are reshaping industries, driving automation, enhancing customer experiences, optimizing processes, and unlocking business opportunities for modern enterprises. However, this rapid advancement also presents a new range of cybersecurity challenges. As organizations rush to adopt powerful AI & LLM tools, they inadvertently expand their attack surfaces, introducing vulnerabilities that traditional security measures are ill-equipped to handle.
In response to these emerging challenges, Qualys is proud to announce the upcoming launch of Qualys TotalAI, a cutting-edge solution designed to secure AI and LLM applications. This new addition to our Enterprise TruRisk Platform will be showcased at Black Hat 2024, and we are thrilled to invite you to join us in exploring how this groundbreaking technology can monitor and reduce your attack surface.
Register now and join us at Black Hat 2024 to check out how Qualys TotalAI can transform your approach to AI security.
The Rising Importance of AI Security
As AI and LLMs become more embedded in business operations, they have become a prime target for cybercriminals. The risks associated with AI and LLMs are not hypothetical; they are real and growing, with potential consequences ranging from intellectual property theft to severe reputational damage. To fully appreciate the need for a specialized security solution, it’s essential to understand some of the common issues associated with AI and LLM technologies:
Discovery of LLM models – The discovery of LLM models within an organization’s infrastructure is often a blind spot for security teams. When left unchecked, can introduce data security and privacy risks. Without proper oversight, LLMs may accidentally expose sensitive information, becoming vulnerable to attacks such as prompt injection or data leakage. Furthermore, the unauthorized or improper use of LLMs can lead to the generation of biased or inappropriate content. The potential for such incidents underscores the need for comprehensive visibility and inventory management of all AI assets within an organization’s ecosystem.
Prompt injection attacks – These attacks involve injecting malicious inputs into the prompts provided to AI models, manipulating the model’s output. This can lead to unintended consequences, such as the disclosure of sensitive information or the execution of harmful actions. Attackers can exploit weaknesses in the model’s prompt processing logic, often embedding commands or queries that the model interprets and executes.
Sensitive information disclosure – LLMs, if improperly secured, can accidentally reveal sensitive data, including internal configurations, user data, or proprietary information. This often occurs due to insecure configurations, flawed application design, or failure to sanitize data properly.
Model theft – Also known as model extraction, this threat involves attackers duplicating a machine learning model without direct access to its parameters or training data. Attackers can use query-based techniques to reverse engineer the model, posing significant risks to intellectual property. Additionally, attackers can gain access to the AI model’s code, architecture, or training data by compromising the infrastructure layer. This is typically done by exploiting a vulnerability or misconfiguration in the system, allowing the attacker to infiltrate the underlying infrastructure and extract sensitive information.
Data leakage – Unauthorized transmission of confidential data can occur through various means, including insecure handling practices or the AI’s inadvertent inclusion of sensitive information in its responses. This can lead to identity theft, financial loss, and competitive disadvantages.
Compliance and reputational risks – The misuse of AI and LLMs can result in compliance violations, especially concerning data protection regulations like GDPR and CCPA. Moreover, the generation of inappropriate or biased content by these models can cause significant reputational harm to organizations.
The potential consequences of an AI security incident are severe, including:
- Direct financial losses from remediation costs, legal fees, and regulatory fines.
- Intellectual property theft of proprietary AI models and algorithms.
- Reputational damage, leading to loss of customer trust.
- Operational disruptions, causing downtime and affecting productivity.
- Legal challenges due to non-compliance with data protection regulations.
Introducing Qualys TotalAI
Recognizing the unique and evolving nature of these threats, Qualys has developed Qualys TotalAI, a comprehensive solution tailored to protect LLM applications. It leverages the robust capabilities of the Enterprise TruRisk Platform and offers complete visibility across the AI stack – infrastructure, packages and models, vulnerability management, and LLM scanning with remediation guidance specifically designed for AI environments.
Key Features of Qualys TotalAI
- Comprehensive discovery and monitoring — One of the fundamental challenges in securing AI environments is having good visibility over AI workloads. Qualys TotalAI offers detailed mapping and monitoring of AI workloads, ensuring that organizations have a clear understanding of their AI infrastructure. This capability is crucial for detecting shadow models—unapproved or risky AI models with unknown origins that can introduce major vulnerabilities.
- Advanced vulnerability management — Data and model theft is real and often results from infrastructure-related vulnerabilities. Qualys TotalAI leverages Qualys’ extensive experience in vulnerability management and extends these capabilities to cover AI-specific threats. This allows customers to proactively harden their AI Infrastructure.
- Robust remediation capabilities – Beyond detection, Qualys TotalAI provides powerful remediation guidance that enables organizations to respond quickly and effectively to identified threats including prioritization with TruRiskTM scoring, patch management, configuration adjustments, and other corrective actions.
- Specialized LLM scanning – Qualys TotalAI includes LLM scanning to target critical vulnerabilities unique to LLM applications, focusing on prompt injection, model theft, and sensitive information disclosure. By addressing these high-risk areas, Qualys TotalAI helps organizations mitigate the most pressing security concerns in the AI landscape.
- Compliance and risk management — Without hardened infrastructure and guard-railed models, enterprises might unknowingly leak sensitive data, leading to compliance violations. Qualys TotalAI is also designed to help organizations maintain compliance with data protection regulations like GDPR and PCI, for avoiding legal penalties and preserving customer trust.
Qualys TotalAI offers a unique combination of advanced technology, comprehensive coverage, and deep expertise in cybersecurity. With Qualys TotalAI, businesses can confidently innovate and grow, knowing they are protected against the most critical AI threats.
Looking Ahead: The Future of AI Security
As AI and LLM technologies continue to evolve, so will the associated security challenges. Qualys is committed to staying ahead of these trends and continuously enhancing our solutions to meet the changing needs of our customers. We believe that a proactive, comprehensive approach to measure, communicate and eliminate AI/LLM threats is essential for ensuring the safe and effective use of these powerful technologies.
Availability and Next Steps
Qualys TotalAI is scheduled to be available in Q4 2024.
Sign up for the Qualys TotalAI Risk Insights Report and early access to Qualys TotalAI.
New to Qualys? Sign up for a 30-day unlimited scope trial of Enterprise TruRisk Platform.
