AI security consulting for the attack surface your existing controls do not cover
Our AI security consulting finds the prompt injection, data exposure and excessive tool permissions your existing application controls miss. We map the system’s data flows and rank findings by impact and likelihood, so you fix what matters first.
We reply within 4 business hours.
What is AI security consulting?
AI security consulting assesses and remediates risks specific to AI systems: prompt injection, data leakage through model outputs, over-permissioned agent access, insecure tool use, model supply chain risk and vendor data handling. These differ from traditional application security concerns and therefore require specific testing.
Your penetration test did not cover this
Traditional application security testing looks for injection into interpreters, broken authentication and misconfiguration. However, it does not test whether a document uploaded by a customer can instruct your AI to exfiltrate other customers’ data.
Meanwhile, prompt injection has no complete technical fix, and over-permissioned agents can take actions nobody authorized. In addition, retrieval systems leak content across permission boundaries when filtering happens after retrieval rather than before.
Test the AI-specific attack surface explicitly
We assess the failure modes specific to AI systems: injection through every input path including retrieved documents, leakage through outputs, agent permission scope, tool use safety and vendor data handling.
Then we remediate: architectural controls that bound impact rather than relying on the model to refuse, because relying on a model to refuse is not a security control.
What our AI security consulting includes
Prompt injection is the defining problem. For example, instructions embedded in any content the model processes, a document, a web page, an email, a retrieved passage, can influence its behavior. Because there is no complete fix, the mitigation is architectural: bound what the model can do so injection cannot cause serious harm.
Data leakage is the second: models returning content from other tenants, other users, or documents the requester should not access. Retrieval systems that filter after retrieval rather than before are the common cause.
Agent permissions are the third and increasingly the most consequential. After all, an agent with broad system access and a prompt injection vulnerability is a serious problem. Yet teams frequently deploy the two together.
Our AI security consulting services include an LLM security assessment, prompt injection protection and AI data security reviews across every input path. AI application security is tested the way an attacker would approach it.
- Prompt injection testing across every input path including retrieved content
- Data leakage assessment: cross-tenant, cross-user and permission boundary
- Agent permission review: what can it actually do if compromised
- Tool use safety: blast radius of every function an agent may call
- Vendor and supply chain assessment: data handling, retention, subprocessors
- Architectural remediation that bounds impact rather than relying on refusal
Is AI security consulting right for your business?
Organizations with AI in production handling sensitive data, particularly where the AI has access to systems or serves multiple tenants.
It also helps security teams asked to approve an AI deployment without an established framework for assessing it. That describes most security teams.
AI risk assessment services suit teams asked to approve AI systems they cannot fully see into. We leave you with AI governance and risk controls that your security team can maintain.
- Organizations with production AI handling sensitive or regulated data
- Multi-tenant AI products needing isolation assurance for customers
- Teams deploying agents with write access to business systems
- Security functions asked to approve AI deployments without a framework
- Companies whose customers are asking AI security questions in procurement
- Regulated firms needing documented AI risk assessment
What AI security consulting can do for your business
The right threats tested
Injection, leakage and permission escalation assessed specifically, which standard penetration testing does not cover.
Architectural controls, not refusals
Impact bounded by design rather than relying on the model declining, which is not a security control.
Tenant isolation proven
Documented isolation assurance that survives a customer security questionnaire.
Agent blast radius understood
Explicit assessment of what an agent could do if compromised, before that becomes a live question.
Vendor risk documented
Data handling, retention and subprocessor arrangements assessed and recorded for compliance.
A framework your team keeps
An assessment approach your security function can apply to future AI deployments independently.
Problems AI security consulting solves
Penetration tests missing AI risks
Standard testing not covering injection or leakage. An AI-specific assessment therefore closes the gap.
Retrieval leaking across permissions
Filtering after retrieval exposing content. Instead, pre-retrieval filtering fixes it architecturally.
Over-permissioned agents
Broad system access with injection exposure. However, least-privilege scoping bounds the risk.
Security asked to approve blind
No framework for assessing AI. That is why we provide one your team retains.
Customer security questionnaires
Buyers asking AI-specific questions. Documented isolation and controls then answer them.
Vendor data handling unclear
Uncertainty about retention and training use. Our assessment, therefore, documents the actual position.
What every AI security consulting engagement includes
Everything below is in scope on a standard engagement. Nothing here is an upsell discovered halfway through the build.
Threat modeling
AI-specific threat model covering injection paths, data flows, trust boundaries and agent capability.
Prompt injection testing
Adversarial testing across every input path including user input, uploaded documents, retrieved content and tool results.
Data leakage assessment
Testing for cross-tenant, cross-user and permission boundary leakage through model outputs and retrieval.
Agent permission review
Assessment of every tool an agent may call, its blast radius, and what a compromised agent could achieve.
Retrieval security
Verification that permission filtering happens before retrieval rather than after, which is the common leak path.
Vendor assessment
Model provider data handling, retention, training use and subprocessor arrangements documented against your requirements.
Architectural remediation
Controls that bound impact structurally rather than depending on model refusal behavior.
Assessment framework handover
A repeatable framework your security team can apply to subsequent AI deployments.
Which AI models and tools do we use for AI security consulting?
We are not tied to one vendor. Accordingly, accuracy, cost per task, latency and permitted data location guide our model and infrastructure choices.
How we deliver AI security consulting, step by step
Every assessment follows the same five stages. We test the AI-specific attack surface before recommending any control.
Discovery
First, we map data flows, trust boundaries, input paths and every tool an agent may call.
AI Strategy
Next, we build an AI-specific threat model and rank risks by impact and likelihood.
Pilot Build
Then we run injection and leakage testing across every input path, including uploaded documents and retrieved content.
Implementation
After that, we implement architectural remediation, such as least-privilege scoping and pre-retrieval filtering, and verify it by retest.
Optimization
Finally, we hand over a repeatable assessment framework your security team can apply to future AI deployments.
How much does an AI security consulting project cost?
AI security consulting is priced on the AI systems in scope, the data they can reach and what their agents are allowed to do. You get a fixed written price before testing starts, with findings your security team can act on immediately.
Book a free 30-minute call and tell us which AI systems you are being asked to approve. We will tell you the risks most likely to matter and how deep an assessment needs to go.
- A written savings estimate before any paid work
- Fixed scope and fixed price, agreed up front
- Full ownership of everything we build for you
- An honest recommendation when the numbers do not work
Figures are internal measurements across recent engagements, reported to every client monthly in writing.
AI security consulting FAQs
Does our existing penetration test cover AI risks?
Almost certainly not. Standard application security testing looks for injection into interpreters, broken authentication and misconfiguration. However, it does not test whether a document a customer uploads can instruct your AI to retrieve other customers’ data. Nor does it test what an agent with write access could do if manipulated. For example, on a recent engagement a system that had passed a standard penetration test had a cross-tenant retrieval leak.
Can prompt injection be fully prevented?
No, and any vendor claiming otherwise is overselling. Instructions embedded in content the model processes can influence its behavior. Moreover, no filter reliably catches all of them. Therefore, the correct response is architectural: assume injection may succeed and bound what the model can do. That way, success is not catastrophic. For example, least-privilege tool scoping, approval gates on consequential actions and output validation limit impact regardless of whether injection works.
What is the most common serious finding?
Retrieval permission filtering applied after retrieval rather than before. It looks correct because the filtered content does not appear in the response. However, the content has already entered the model context, so an attacker can extract it through injection. It is a common implementation shortcut and a genuine data leak.
How do we assess model provider risk?
By reading the actual terms rather than the marketing, and documenting the position. Key questions include whether the provider trains on your data and what retention applies. We also check whether zero-retention is available for your use case, which subprocessors are involved, and where processing occurs. We document this against your compliance requirements, and terms change, so we verify current rather than remembered positions.
Can you help us answer customer security questionnaires?
Yes, and this is an increasingly common reason for engagement. Enterprise buyers are asking AI-specific questions that most vendors cannot answer confidently. A documented assessment with evidence, however, answers them properly. In one recent engagement, for instance, the assessment documentation unblocked deals that had stalled in security review.
What does an AI security assessment cost?
It depends on how many AI systems are in scope, the data they touch and what their agents can do. The assessment is priced in writing before testing starts, and remediation or vendor documentation is quoted separately if you want it. Book a free 30-minute consultation to scope the assessment.
Ready to scope your AI security consulting project?
Book a free 30-minute consultation. Bring one workflow. You will leave with a realistic estimate of what it would cost to automate and what it would save.