The new attack surface
Risks we assess and address
Traditional application security remains necessary, but it does not cover how language models interpret instructions, retrieve data, or call tools.
Prompt injection
Direct instructions that override system behavior or safeguards.
Indirect prompt injection
Malicious instructions hidden in documents, emails, or web content the model reads.
Sensitive-data disclosure
Confidential or regulated data surfacing in outputs or logs.
RAG security
Retrieval that ignores document permissions or ingests poisoned content.
Vector database security
Access control, tenancy, and integrity for embedding stores.
AI agent permissions
Least-privilege design for agents that act on users' behalf.
Excessive agency
Agents with more autonomy or reach than the task requires.
Tool / API abuse
Agents manipulated into misusing the tools and APIs they can call.
Secrets exposure
Keys and credentials leaking through prompts, code, or configuration.
Model access
Who and what can call each model, and under which policies.
Identity and access
Authentication, authorization, and user context carried end to end.
Third-party AI risk
Security posture of AI vendors, models, and embedded AI features.
AI logging
Capturing prompts, outputs, retrievals, and tool calls for review.
SIEM integration
Routing AI telemetry into existing detection and response workflows.
AI incident response
Playbooks for AI-specific incidents, from data leakage to agent misuse.
Services
How we engage
AI security assessment
Review of existing AI systems, integrations, and controls with prioritized findings.
AI threat modeling
Structured analysis of how a specific AI solution could be attacked or misused.
Secure AI architecture
Reference designs and control requirements for new AI initiatives.
AI agent security and RAG review
Permission, retrieval, and tool-access analysis for agentic systems.
AI detection engineering
Logging design, SIEM integration, and detection content for AI activity.
AI incident response readiness
Playbooks, escalation paths, and tabletop exercises for AI incidents.
Security assessments identify and reduce risk. No assessment or control set can eliminate all risk.
Find the exposure before an attacker does.
An AI security assessment covers your models, data paths, agents, and integrations.