Large Language Models (LLMs) are rapidly transforming enterprise workflows, but their integration brings new security challenges. Gartner's 2023 AI survey reveals widespread LLM adoption in existing applications, highlighting the urgent need for robust security measures. As technology leaders navigate this landscape, understanding and mitigating LLM-specific risks is crucial to prevent data breaches, API attacks, and compromised model safety.
This whitepaper equips executives with essential knowledge to secure LLM deployments:
- Comprehensive analysis of the top 10 LLM security risks, including data leakage, prompt injection, and model poisoning
- Actionable strategies to mitigate threats, covering data sanitization, API security, and model integrity preservation techniques
- Insights into emerging best practices and the future of LLM security, enabling proactive risk management and competitive advantage
Whitepaper
Large Language Models (LLMs) are rapidly transforming enterprise workflows, but their integration brings new security challenges. Gartner's 2023 AI survey reveals widespread LLM adoption in existing applications, highlighting the urgent need for robust security measures. As technology leaders navigate this landscape, understanding and mitigating LLM-specific risks is crucial to prevent data breaches, API attacks, and compromised model safety.
This whitepaper equips executives with essential knowledge to secure LLM deployments:
- Comprehensive analysis of the top 10 LLM security risks, including data leakage, prompt injection, and model poisoning
- Actionable strategies to mitigate threats, covering data sanitization, API security, and model integrity preservation techniques
- Insights into emerging best practices and the future of LLM security, enabling proactive risk management and competitive advantage
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A Look at LLM Security Threats and Mitigations
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A Look at LLM Security Threats and Mitigations
Explore the critical security challenges posed by Large Language Models (LLMs) in our latest whitepaper. Understand risks and effective mitigation strategies.
Key results
Large Language Models (LLMs) are rapidly transforming enterprise workflows, but their integration brings new security challenges. Gartner's 2023 AI survey reveals widespread LLM adoption in existing applications, highlighting the urgent need for robust security measures. As technology leaders navigate this landscape, understanding and mitigating LLM-specific risks is crucial to prevent data breaches, API attacks, and compromised model safety.
This whitepaper equips executives with essential knowledge to secure LLM deployments:
- Comprehensive analysis of the top 10 LLM security risks, including data leakage, prompt injection, and model poisoning
- Actionable strategies to mitigate threats, covering data sanitization, API security, and model integrity preservation techniques
- Insights into emerging best practices and the future of LLM security, enabling proactive risk management and competitive advantage
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