AI Security Risk Assessment
Map your AI attack surface and priority risks.
Cybergreen AI Security Services
Secure your AI before attackers do.
Find security gaps across your LLMs, agents, APIs, and AI workflows.
For organizations reviewing, launching, or expanding AI-enabled systems.
AI security, simply explained
Understand where the system can fail.
We test how AI handles instructions, data, access, decisions, and actions.
Who we secure
Security for the AI platforms shaping your business.
We secure leading platforms, cloud model services, custom LLMs, and agents.
Custom LLMs
AI Agents
The connected system
Every connection creates a security question.
A useful review follows the path from the user’s request through instructions, retrieval, model behavior, tools, APIs, and business data. The diagram shows why the whole workflow matters.
Why traditional security alone is not enough
An AI feature adds new ways to influence the system.
Application, cloud, and API testing still matter. But they may not reveal what happens when untrusted content changes a model’s instructions, retrieval results, output, or tool choice.
The combined view
Traditional controls
Identity, access, infrastructure, application logic, and data protection.
AI-specific questions
Can the model be manipulated, can retrieval cross a boundary, and can an agent take an unsafe action?
Services offered
Security work matched to your environment.
Choose a focused review or combine services for your AI environment.
LLM & AI Application Review
Review prompts, guardrails, outputs, and application logic.
Adversarial Testing
Test prompt injection, jailbreaks, leakage, and unsafe outputs.
AI API & Integration Testing
Test identity, access, secrets, webhooks, and integrations.
AI Agent & Tool-Use Assessment
Assess tool use, privileges, approvals, and high-impact actions.
Governance & Security Advisory
Prioritize controls and practical remediation.
Scoped AI Red Teaming
Focused adversarial exercises within agreed safeguards.
AI risk landscape
What we assess and test.
We test how attackers could influence inputs, outputs, data, or actions.
Prompt injection
Test whether hostile prompts can override your system intent.
Sensitive data exposure
Trace how confidential data moves through prompts, outputs, and providers.
Agent permissions
Review what your agents can access, call, change, or approve—and whether those actions are constrained.
AI integrations
Assess access, APIs, webhooks, plugins, and connected systems.
RAG and data flows
Examine retrieval boundaries, document access, and poisoning risks.
Governance gaps
Find gaps in ownership, controls, and review points.
Untrusted content can change intent
We test whether external content can steer an assistant toward actions outside the user’s authorization.
Data needs a boundary
We trace where sensitive information travels and whether outputs or integrations respect that boundary.
Actions need authorization
We review permissions and approval points so useful agents can act within defined limits.
How an engagement works
A clear path from uncertainty to action.
Scope, authorization, safeguards, and deliverables are agreed before testing begins.
- 01
Scope the system
Map features, models, data, integrations, and critical actions.
- 02
Assess and test
Review the architecture and run controlled security tests.
- 03
Prioritize the risk
Rank findings by impact and urgency.
- 04
Remediate with confidence
Get practical fixes and a path to validate them.
What you receive
Security insight your teams can use.
Clear evidence and practical guidance for better security decisions.
- Executive summary
- Prioritized findings and evidence
- Attack paths and proof of concept
- AI-specific remediation guidance
- Architecture and data-flow observations
- Stakeholder readout and next steps
AI ecosystem
Security follows the connections.
We secure the boundaries between identity, cloud, data, APIs, and enterprise systems.
Who this service is for
Bring us the AI system you are trying to secure.
Launching, scaling, or reviewing AI? Start with a focused next step.
Fintech and financial-services organizations
SaaS and AI product teams
Enterprises deploying internal copilots or agents
Security, compliance, and risk teams
Why Cybergreen
Security guidance grounded in your actual system.
Structured scope
Clear scope, access, objectives, and safeguards.
Human-validated findings
Findings explained in business context.
Practical next steps
Remediation guidance your team can act on.
Common questions
Before you start.
AI security adds prompt injection, model behavior, retrieval, tool-use, and unsafe-output testing.
Yes. We can assess designs, prototypes, staging environments, or production systems.
It depends on scope: an endpoint, user access, architecture, prompts, policies, logs, or test credentials.
Yes, where they are included in scope. We can review how agents choose tools, handle permissions, process untrusted content, and perform actions through connected services.
You receive a prioritized report and a stakeholder readout. Remediation advisory and retesting can be discussed based on the findings and your preferred next step.
Understand Your AI Security Exposure.
Assess your AI risks and define the next step.
Scoped to your environmentPractical remediation guidance