AI Security

AI systems combine data, models, prompts, software, identities, and third-party services. That expanded chain creates failure modes that ordinary application reviews may miss: prompt injection, unsafe tool use, sensitive-data disclosure, model or dataset tampering, excessive agency, and output that is plausible but wrong. Risk also changes after release as data, prompts, models, and user behavior change.

A defensible program begins with intended use and impact. Owners should identify affected people and processes, unacceptable outcomes, trust boundaries, legal constraints, and the level of human authority retained. Controls should then be proportional to consequence. A low-impact internal summarizer and an agent able to change customer records should not share the same approval path.

A practical pattern places policy and identity controls before the AI service; retrieval and tool gateways around external data and actions; and logging, evaluation, and incident handling across the full path. Registries record approved models, datasets, prompts, owners, and versions. Input and output handling can enforce context-specific rules, while least-privilege credentials limit downstream reach.

An Alexa Cybersecurity engagement can assess use cases, map data and model flows, facilitate threat modeling, review supplier assumptions, define evaluation cases, and design control and evidence requirements. Depending on agreed scope, deliverables may include a risk register, target architecture, control backlog, testing plan, logging design, or incident playbook. These are assessment and engineering activities, not a claim that every model defect can be detected or prevented.

Deployment may cover cloud-hosted APIs, private or self-hosted models, endpoint AI, or hybrid designs. The appropriate pattern depends on an agreed assessment of data sensitivity, latency, residency, integration, operator access, and recovery needs. Possible use cases include employee copilots, document retrieval, customer assistants, predictive workflows, and agents that invoke business tools.

Financial services, healthcare, government, energy, retail, and software organizations can adapt the pattern to their obligations and impact tolerance. Related technologies include identity and access management, data loss prevention, API gateways, model registries, secrets management, observability, security information and event management, and software supply-chain controls. Technology selection follows requirements; this page does not represent a certification, product guarantee, or universal managed service.