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GenAI TRiSM, or Generative AI in Trust, Risk, and Security Management, is a crucial subset of the broader AITRiSM market. It encompasses various software segments necessary for building, maintaining, and governing AI models, applications, or agents.
Anomaly detection is an essential capability for mitigating risks related to the content LLMs generate. This includes identifying and addressing improper information disclosure, ensuring compliance with legal and ethical standards, and safeguarding against the manipulation of AI models to produce malicious outputs.
For businesses, this means implementing systems that can dynamically assess and respond to content anomalies in real-time, taking the unique features and behaviors of LLMs into account. Businesses face the challenge of ensuring the integrity and security of the content produced by LLMs.
This extends beyond mere accuracy concerns to encompass broader considerations, such as improper information disclosure, adherence to legal and ethical standards, and protection against the nefarious manipulation of AI models to yield malicious outputs.
The criticality of anomaly detection lies in its ability to proactively identify and address deviations from the expected behavior of LLMs, thereby fortifying defenses against potential risks. By dynamically assessing content anomalies in real-time, businesses can stay ahead of emerging threats and maintain the trustworthiness of their AI-driven outputs.
In addition to securing employee usage of LLMs, there is an even more pressing need to defend applications that utilize LLMs from emerging threat vectors. This includes protection against novel threats like prompt injection, and securing the software supply chain.
Cyber threats are becoming both more numerous and more sophisticated, across the board. But LLM applications carry a heightened risk precisely because they’re relatively new, and because most organizations still have not fully grasped the nature and extent of these risks. Businesses and organizations of all types face a dilemma: they can either sit on the sidelines, and lose to more forward thinking competitors. Or, they must embrace the power of LLMs in their applications, with all the dangers that come along with that.
As more and more organizations make the latter choice, it becomes imperative to not only secure the immediate user experience but also to secure the underlying infrastructure. This comprehensive approach ensures a resilient defense, offering organizations confidence in the secure and responsible utilization of LLM technologies.
A third priority involves ensuring the confidentiality and integrity of data that LLMs use or generate. According to a Gartner security survey, this issue is top of mind for security experts.
Priorities include securing data against unauthorized access and leaks, especially in externally hosted environments, and maintaining compliance with evolving data protection regulations. Given the 'black box' nature of many LLMs, implementing effective governance and control measures over data handling processes is a significant challenge that traditional cyber security tools are not designed to overcome.
The uniquely conversational and context-driven nature of LLM interactions means that legacy tools and controls cannot completely secure these models. To do that, organizations will need to turn to the growing market for TRiSM solutions that focus on LLM security.
Lasso Security excels in all three critical areas: Content Anomaly Detection, Privacy and Data Protection, and AI Application Security.
Our solution actively monitors LLM outputs, ensuring compliance with your organizational standards and preventing sensitive data leakage. In addition, Lasso provides robust defenses to guarantee the security and integrity of LLM-based applications. Our solution is listed in Gartner’s recent Innovation Guide for Generative AI in TriSM.
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It’s time for organizations of all sizes to secure their future - and for almost all of them, that future will be LLM-driven. Connect with the Lasso team to talk about tailored cybersecurity solutions that protect and empower your organization as it makes this transition.
Gartner, Innovation Guide for Generative AI in Trust, Risk and Security Management, By Avivah Litan, Jeremy D'Hoinne, Gabriele Rigon, 12 April 2024
GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates. All rights reserved. Gartner does not endorse any vendor, product, or service depicted in its research publications.
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