This data sheet provides an overview of the SPLX Platform’s Automated AI Red Teaming capabilities – an essential tool for CISOs, AI security leaders, and engineering teams responsible for identifying and mitigating risks in LLMs, chatbots, and agentic workflows. The platform enables organizations to uncover security gaps through continuous, large-scale red teaming and delivers deep, actionable insights for faster remediation.

Ensure Your AI Systems are Secure Before Every Deployment

• Simulate thousands of attack scenarios across 25+ predefined and custom AI risk categories

• Detect vulnerabilities in LLM apps, RAG chatbots, agentic workflows, and LLM APIs

• Automate red teaming and uncover domain-specific security gaps

Simulate Advanced Attacks Across Realistic Scenarios

• Leverage a continuously updated library of cutting-edge attack strategies and jailbreak techniques

• Simulate interactions from both adversarial and regular user personas to assess system behavior

• Automate testing across all input modalities – from text and images to multi-turn conversations

Accelerate Remediation and Compliance Efforts

• Dynamically harden your system prompts to mitigate up to 85% of discovered risks

• Map vulnerabilities to frameworks like NIST AI RMF, OWASP LLM Top 10, and the EU AI Act

• Get structured reports with detailed attack traces and remediation steps

Precise Drill-Down Into Simulated Attacks

• Analyze red teaming results with full visibility into each attack trace

• Use AI automation to surface the most critical vulnerabilities and patterns

• Prioritize high-risk issues and accelerate your remediation workflow

Eliminate security bottlenecks and deploy safe, trustworthy AI at scale. Download the data sheet to see how SPLX helps reduce manual testing effort by up to 95%, speed up secure deployments, and drive confident AI adoption across the whole enterprise.