Protect your AI applications
with AI Firewall®
Real-time protection, automatically configured to address vulnerabilities of each model.
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Superior protection of AI applications
AI Protection safeguards production applications from attacks and undesired responses in real time with AI Firewall guardrails that can be automatically configured to the specific vulnerabilities of each model, identified with our AI Validation offering. Our detections span hundreds of security and safety categories, powered by our proprietary technology and pioneering research.
Leading guardrail solution powered by proprietary technology
The technology behind our AI Firewall is based on technology developed over the past decade by our founding team. We use a combination of proprietary algorithmic red teaming, threat intelligence pipeline, and policy mappings to automatically generate examples of security and safety failures that update our detections. This gives AI Firewall the broadest coverage and the greatest performance of any guardrail offering.
Advanced detection
and protection
Proprietary techniques including algorithmic red teaming and threat intelligence research are used to continuously update AI Firewall with mitigations against the latest threats.
Algorithmic Red Teaming
Tree of Attacks with Pruning (TAP), Greedy Coordinate Gradient (GCG), and other algorithmic techniques
Threat Intelligence Feed
Prompt injection, jailbreaks, in-the-wild and adversarial techniques gathered from open and closed sources
Poisoning 0.01% of data used by large models led to backdoors
Security vulnerabilities found in NVIDIA’s NeMo Guardrails
Algorithmic jailbreak of GPT-4 and Llama-2 in 60 seconds
ICML Test of Time Award for our work on data poisoning
Award winning and breakthrough research
Our AI Security Research Team continues to pioneer innovative research on topics including data poisoning, adversarial attacks, and robust machine learning to ensure you’re protected against state-of-the-art threats.
Detections across hundreds of security and safety threat categories
Our proprietary taxonomy classifies hundreds of threats which can be the result of malicious actions, such as prompt injection and data poisoning, or unintentional outcomes generated by the model.
Abuse Failures
Toxicity, bias, hate speech, violence, sexual content, malicious use, malicious code generation, disinformation
Privacy Failures
PII leakage, data loss, model information leakage, privacy infringement
Integrity Failures
Factual inconsistency, hallucination, off-topic, off-policy
Availability Failures
Denial of service, increased computational cost
Robust Intelligence is shaping AI Security Standards
Co-developed the AI Risk Database to evaluate supply chain risk
Co-authored the NIST Adversarial Machine Learning Taxonomy
Contributors to OWASP Top 10 for LLM Applications
Simple deployment.
Broad security coverage.
Robust Intelligence makes it easy to comply with AI security standards, including the OWASP Top 10 for LLM Applications.
 Top 10 for LLM Applications | AI Validation Coverage | AI Protection Coverage |
|---|---|---|
| LLM 01: Prompt injection attacks |  |  |
| LLM 02: Insecure output handling | Not applicable | |
| LLM 03: Data poisoning checks | | Not applicable |
| LLM 04: Model denial of service | | |
| LLM 05: Supply chain vulnerabilities | | Not applicable |
| LLM 06: Sensitive information disclosure | | |
| LLM 07: Insecure plug-in design | Not applicable | |
| LLM 08: Excessive agency | Not applicable | |
| LLM 09: Overeliance | | |
| LLM 10: Model theft | Not applicable | |
| OWASP Top 10 for LLM Applications | ||||
|---|---|---|---|---|
| LLM 01: Prompt injection attacks | AI Validation Coverage | AI Protection Coverage | | |
| LLM 02: Insecure output handling | AI Validation Coverage | AI Protection Coverage | Not applicable | |
| LLM 03: Data poisoning checks | AI Validation Coverage | AI Protection Coverage | | |
| LLM 04: Model denial of service | AI Validation Coverage | AI Protection Coverage | | |
| LLM 05: Supply chain vulnerabilities | AI Validation Coverage | AI Protection Coverage | | |
| LLM 06: Sensitive information disclosure | AI Validation Coverage | AI Protection Coverage | | |
| LLM 07: Insecure plug-in design | AI Validation Coverage | AI Protection Coverage | Not applicable | Not applicable |
| LLM 08: Excessive agency | AI Validation Coverage | AI Protection Coverage | Not applicable | |
| LLM 09: Overeliance | AI Validation Coverage | AI Protection Coverage | | |
| LLM 10: Model theft | AI Validation Coverage | AI Protection Coverage | Not applicable | |
Automatically generate guardrail rules to fit each model
While AI Firewall can be used stand-alone, protection is enhanced by our ability to automatically generate guardrails specific to the security and safety vulnerabilities inherent in each model. Either way, it’s simple to get started with our API-based service.
Standard protections
Out-of-the-box protections against hundreds of security and safety threats
Enhanced with auto-configured guardrails
Custom fit guardrails to each model’s specific vulnerabilities with AI Validation
Easy to use
with fast time
to value
It’s simple to deploy AI Firewall. All it takes is one line of code to protect your AI applications. Configure policies and automatically block threats with plugins that connect to your web application firewall (WAF).
Protect multiple AI applications
Single deployment can support AI Firewall protection for multiple applications - you choose SaaS or a cloud agent deployed in your environment.
Enterprise-ready
Blazing fast API delivers low latency and seamless scalability of production workloads.
Customize policies
Configurable policies to fit your application’s use case, such as tolerances for explicit language and what constitutes sensitive information.
Seamless integrations
Integrates seamlessly with your tools and workflows, enabling you to easily add protection to any AI-powered application.
Protect your AI applications
AI Firewall protects your application, no matter your use case or industry, adding an essential security and safety layer. Three of the most common use cases today are:
Foundation Models
Foundation models are at the core of most AI applications today, either modified with fine-tuning or purpose-built. Learn what challenges need to be addressed to keep models safe and secure.
RAG Applications
Retrieval-augmented generation is quickly becoming a standard to add rich context to LLM applications. Learn about the specific security and safety implications of RAG.
AI Firewall seamlessly integrates with your stack
Lena Smart
Chief Information Security Officer
Generative AI introduces an unmanaged security risk, which is compounded when enriching LLMs with supplemental data. Robust Intelligence's AI Firewall solves this critical problem, giving enterprises the confidence to use LLMs at scale. Our partnership makes it easier for customers to use generative AI while also keeping their data secure with guardrails in place.
Roger Murff
VP of Technology Partners
We are seeing rapid adoption of a lakehouse by companies that are forward-thinking about machine learning and AI. Machine learning integrity through continuous testing is one of the keys to their success. We're excited to partner with Robust Intelligence on the Databricks Lakehouse Platform to enable customers to fully realize the value of machine learning and AI.
Toshifumi Yoshizaki
Corporate Senior EVP and CDO
NEC is currently working with Robust Intelligence to evaluate LLM performance and eliminate risk by combining our knowledge and technology. By delivering NEC's Japanese LLM that pursues the highest quality in terms of both performance and safety, we will accelerate the use of AI in various industries, driven by generative AI, and contribute to corporate innovation.