Specialized AI security services for organizations where modern AI deployments create risk that traditional security approaches were never built to address.
Protection-focused reviews for AI systems in production or pre-deployment, with emphasis on internal behavior, model integrity, and operational risk. We evaluate how your systems route, adapt, and respond under adversarial conditions — covering routing manipulation, activation hijacking, and behavioral exploitation paths that surface-level testing misses. Each assessment produces a detailed risk map tied to your specific architecture and deployment environment.
Adversarial security testing for language models, multimodal models, copilots, agents, and AI-assisted workflows. We simulate real attack scenarios — prompt injection chains, safety alignment bypasses, data extraction through indirect channels, and model behavior manipulation under sustained pressure. Engagements are scoped to your threat model, not a generic checklist. Findings include validated exploit paths with reproducible proof-of-concept demonstrations.
Pre-deployment assessment of open-source and self-hosted models before they enter your environment. We analyze model provenance and supply chain integrity, weight-level anomalies, hidden behaviors triggered by specific input patterns, and configuration risks that emerge when models move from research to production. Designed for teams adopting open-weight models who need confidence before deploying at scale.
Security evaluation for AI systems connected to APIs, search, files, tools, code execution, and memory. We test how models interact with external systems across the full reasoning-to-action chain — including permission boundary testing, tool-use exploitation, unintended data access through chained tool calls, and escalation paths from limited context to broader system access. Critical for any team deploying agentic workflows in production.
Retesting and verification after mitigations, architecture changes, fine-tuning, or model replacement. We measure whether defenses hold after updates, whether new behaviors have been introduced, and whether system changes have created regression risks. Includes before-and-after comparison reporting so your team can track security posture across model iterations and deployment cycles.
HotWAN combines a protection-led services approach with proprietary product direction. Clients engage us for high-value protection and testing today while gaining access to a company building the next layer of AI security capability.