| What it sells | - AIShield AISpectraScans AI/ML models and notebooks and performs red teaming of ML and LLM systems to find vulnerabilities such as adversarial attacks, model theft, data poisoning, prompt injections and jailbreaks.
- AIShield Guardian ML FirewallDetects and mitigates adversarial threats such as extraction, evasion and poisoning against deployed machine learning applications, integrating with tools like Splunk and Sentinel.
- AIShield Guardian GenAI GuardrailsFilters inputs and outputs of generative AI applications and LLMs to mitigate prompt injection, jailbreaks, sensitive data exposure and bias, with PII anonymization.
| - WonderSuite[1]A unified platform that combines pre-launch adversarial testing, real-time guardrails, and ongoing production evaluation for GenAI and agentic systems.
- WonderBuild[1]Pre-launch red teaming that stress-tests AI models, applications and agents for prompt injection, jailbreaks, data leakage and policy violations before deployment.
- WonderFence[1]A real-time AI firewall that intercepts unsafe inputs before they reach a model and blocks harmful outputs before they reach users.
- WonderCheck[1]Periodic post-launch red teaming and evaluation that detects model drift, regressions and emerging vulnerabilities in production AI systems.
- Rabbit Hole[1]A proprietary adversarial intelligence dataset of real-world harmful and manipulative AI interaction data that powers the WonderSuite products.
| - Red Teaming[2]Automated testing that generates attacks such as prompt injections and jailbreaks to find application-specific vulnerabilities in AI applications.
- Guardrails[2]Real-time filtering that protects AI applications against jailbreaks and adversarial attacks.
- Model Security[2]Security testing and monitoring for AI models.
- MCP Proxy[2]A proxy that secures Model Context Protocol communications.
- Code Scanning[2]Scanning that finds LLM vulnerabilities in a developer's IDE and CI/CD pipeline.
- Evaluations[2]A framework for testing and evaluating prompts, models and RAG pipelines.
| - AI Asset Management[1][4][5]Discovers models, AI workflows, MCP servers and guardrails across an enterprise and builds an AI-BOM to uncover vulnerabilities and track compliance.
- AI Red Teaming (Probe)Automatically and continuously tests AI systems for vulnerabilities using a database of adversarial attack scenarios.
- AI Runtime Protection[1][4][5]Enforces input and output guardrails during live AI deployments to detect malicious behavior, prompt injections and data leakage.
- AI Governance & Compliance[1][4][6]Maps AI systems to security standards and regulatory frameworks to track alignment with policies.
- Dynamic Remediation[1][7]Converts red teaming findings into system prompt hardening and remediation steps to reduce attack surface.
- Agentic Radar[1]An open-source scanner that visualizes agentic AI workflows and surfaces tool-level vulnerabilities and attack patterns.
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| G2 and Gartner Peer Insights | - G2: Not stated on its pages
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