Put AI to work with clear security controls
AI Security Consulting
Can your AI tools access confidential information or take actions beyond their intended role? GDF reviews AI systems, tests relevant risks and gives security leaders a practical plan for improving controls.
Start with the AI decision your organization is making
You may be introducing an employee assistant, connecting a model to company documents, deploying a customer-facing application or giving an AI agent access to business tools. Each use creates a different set of data, identity and approval questions.
GDF scopes the assessment around the actual application, users, information and actions involved. We bring governance review, security architecture and controlled technical testing together so the findings can guide deployment and remediation.
Protect confidential information and control access
We examine how information reaches the AI system, which users can retrieve it, how permissions are enforced and where prompts and outputs are stored. The review follows data through uploaded files, retrieval systems, external providers and connected applications.
For agents, we review tool permissions, approval steps, credentials and the records of actions taken. The objective is a clear connection between a user's authority and what the AI system is allowed to read or do.
Discuss your AI system and security assessment
Tell us what your AI application can access and what it can do. We can help you choose a governance review, architecture assessment or hands-on security test.
Test the application and the surrounding controls
Controlled testing can examine prompt injection, sensitive-data exposure, authorization, unsafe tool use and application integration. We agree on test accounts, representative data, permitted methods and the environment before testing.
For example, an assessment might test whether a document assistant returns material outside a user's access rights, or whether an agent requests approval before making a consequential change. The findings record the test conditions, observed behavior, affected control and recommended correction.
Explore AI security architecture and AI security testing. AI-assisted penetration testing describes a separate service: how human testers use AI tools in security assessments.
Governance that connects to the technology
We review ownership, approved uses, vendor dependencies, evaluation practices, change management and incident readiness. Policies become actionable when they identify who approves access, what must be tested and which events need review.
The NIST AI Risk Management Framework provides a voluntary framework for managing AI risk. We can organize the engagement around your selected framework and the system's business purpose.
What the assessment delivers
- An agreed system and data-flow description, including users and connected tools.
- A prioritized findings register with supporting test evidence.
- An executive explanation of business impact and decisions.
- Technical remediation steps assigned to the relevant control or application team.
- A validation plan for corrected findings and material system changes.
A useful finding explains the condition, evidence, consequence, correction and retest. Security leaders get a decision summary; engineers get enough detail to act.
Plan the work around your deployment
Bring the intended use, architecture or workflow diagram, data sources, user roles and rollout date. We will help define whether the next step is a focused architecture review, a technical test or a broader governance and risk assessment.
Existing systems also benefit from reassessment after changes to models, permissions, data sources or agent tools. We help define the checkpoints and evidence needed to validate those changes.
Evidence reviewed
- System architecture and data flows
- User roles, permissions and connected tools
- Evaluation records and authorized test results
What you receive
- Prioritized security findings with supporting evidence
- Executive summary and engineering remediation steps
- Validation and retesting plan
Frequently asked
Common questions
Can you assess an AI system before we deploy it?
Yes. GDF can review the design, data flows, access controls, evaluations and logging, then perform controlled testing in an agreed environment. The engagement produces findings and a remediation plan for the deployment team.
Can you review an AI agent that uses business tools?
Yes. We examine tool permissions, credentials, approvals, user authority and action logs, and test selected workflows within the agreed scope.
Can you test whether AI exposes confidential company data?
Yes. We can evaluate retrieval permissions, application access controls and data-handling paths using authorized accounts and representative test material.
Will executives and engineers receive different levels of detail?
Yes. The executive summary explains the decisions and business impact. Technical findings describe the evidence, affected controls, remediation and validation steps.
How do we keep the assessment useful after a model changes?
We identify material changes and a retest plan covering affected data, permissions, integrations and behaviors. The team can use those checkpoints as part of release and change management.
Choose the next step for your AI system
Find regional collection and engagement information or meet the forensic team. Ask about the collection method and report format that fit your matter.
Discuss your AI system and security assessment
Call to discuss your next step and arrange secure information sharing.
What an AI finding looks like
An illustrative finding might show that a support assistant retrieves a document outside the user's permissions. The report identifies the affected connection, the test that reproduced access and the authorization change to verify. This example describes a work product, not a client engagement.