Understanding the Security Challenges
The integration of externally hosted LLMs into generative AI applications has become a standard practice due to their powerful capabilities and perceived benefits. However, this practice introduces significant security risks, particularly when enterprises either do not have internal self-managed LLMs or need to route some requests to more capable external LLMs. These interactions expose enterprises to potential security breaches, emphasizing the need for robust security measures.Key Security Risks and Mitigation Strategies
The report identifies several key security risks associated with generative AI, including:- Sensitive Data Leakage: Addressed through data masking, morphing, or tokenization to enhance privacy protection.
- Data Loss: Mitigated by implementing data loss prevention (DLP) measures to maintain data confidentiality and integrity.
- Vulnerable APIs: Secured by deploying API security solutions, including natural language analytics and filters for API payloads.
CalypsoAI's Leadership in AI Security
CalypsoAI's approach to securing generative AI applications involves the deployment of security guardrails for LLM prompts and the establishment of GenAI security gateways or firewalls within the data path. These measures ensure that communication between internal and external AI services is protected, filtering prompts and data to safeguard against potential threats. Additionally, CalypsoAI is at the forefront of addressing the emerging risks in AI agents' cross-organizational communication. AI agents, designed to operate autonomously and interact with external tools, introduce new security vulnerabilities. CalypsoAI's solutions include advanced threat detection, data masking, and the enforcement of geo-location and IP address restrictions for APIs, ensuring a secure environment for AI agent collaboration. Learn more about the CalypsoAI platform here.Next Steps
The report outlines critical recommendations for product leaders in the next six to eighteen months, emphasizing the need for:- Developing security products that can filter and enforce AI agents' communications.
- Participating in the creation of new AI agent communication standards.
- Advancing technologies in topical filtering, role enforcement, and contextualized AI agent behavior.
1 Gartner, Emerging Tech: Secure Generative Communication for LLMs and AI Agents, 12 June 2024. GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
