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LLM Firewall Integration:
A CISO’s Guide to Securing GenAI Applications

In the rapidly evolving landscape of GenAI and Large Language Models (LLMs) integration into business processes, the risks to sensitive data, individual privacy, and intellectual property are escalating. Recognized authorities like OWASP and NIST are pinpointing emerging threats, highlighting the urgent need for robust security measures to protect GenAI applications.

LLM firewalls are designed with specific policies covering data, tone, and topics, and include proactive measures such as warning and session termination. This helps prevent external attacks and control internal misuse while preserving the integrity of your data.

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Securiti incorporates three types of firewalls to defend GenAI against the evolving threats.  

  • LLM Firewall for Prompt: Monitors user prompts to preemptively identify and mitigate potential malicious use. 
  • Retrieval Firewall for Retrieved Data: Monitors and controls the data retrieved during Retrieval Augmented Generation (RAG) process. 
  • LLM Firewall for Response: Ensures LLM responses align with user expectations and maintains a high standard of security.
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Award-winning technology, built by a proven team, backed by confidence. Learn more.

All-in-One Solution For Your Business Needs

The Multi-disciplinary practice to grow trust-equity of your brand and comply with privacy regulations

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Download the CAIO's Guide to Building Safe Enterprise AI. Create safe AI Copilots, securely sync data, curate data for training, and protect interactions with LLM firewalls.

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Top 10 Considerations for Enabling Safe Use of Unstructured Data with GenAI

Without proper oversight, unstructured data could result in sensitive data exposure. This infographic outlines some important considerations to enable safe use of unstructured data for GenAI.

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