AI Security Reviews
Independent security reviews for AI and LLM-powered features. We look at how prompts are constructed, how retrieval and tools are wired in, where sensitive data flows, and how the model supply chain is governed — mapped to the OWASP LLM Top 10 and the NIST AI Risk Management Framework (AI RMF).
Common reasons teams come to us
- An enterprise buyer sent an AI security questionnaire and the team needs a defensible answer.
- A new LLM-powered feature is close to launch and no independent security review has happened.
- Prompt injection, data leakage, and abuse risk have been raised but not tested.
- Foundation models, plugins, and tool integrations have expanded faster than the review process.
- Leadership wants an internal AI risk and review process aligned to NIST AI RMF.
- OWASP LLM Top 10 has been referenced in a customer contract or vendor security policy.
Talk through your scope, timeline, and customer pressure on a 30-minute call.
- Product teams shipping LLM-powered chat, copilot, or agent features
- SaaS and fintech companies embedding third-party foundation models
- Teams answering customer AI security questionnaires
- Security leaders establishing an internal AI risk and review process
- OWASP LLM Top 10 review — prompt injection, insecure output handling, training data poisoning, model DoS, supply chain, sensitive info disclosure, insecure plugins, excessive agency, overreliance, model theft
- NIST AI RMF (AI 100-1) alignment across Govern, Map, Measure, Manage
- Prompt injection and jailbreak testing on user-facing surfaces
- Data leakage review — training data, retrieval sources, embeddings, logs
- Model supply chain review — providers, weights, plugins, tool use
- Guardrail, evaluation, and abuse-monitoring design review
- Customer-facing AI security narrative and questionnaire responses
What an AI security review covers
OWASP LLM Top 10
Prompt injection, insecure output handling, sensitive info disclosure, excessive agency, and the rest of the Top 10.
NIST AI RMF alignment
Govern, Map, Measure, and Manage functions mapped to your AI development lifecycle.
Prompt injection & jailbreak testing
Hands-on adversarial testing against user-facing chat, copilot, and agent surfaces.
Data & retrieval flow review
Where sensitive data enters prompts, embeddings, retrieval sources, and model logs.
Model supply chain & tools
Foundation model providers, weights, plugins, function-calling, and tool integrations.
Guardrails & abuse monitoring
Evaluation, guardrail, and abuse-monitoring design so risk stays visible in production.
- Ship AI features with a defensible security posture, not vibes
- Get ahead of enterprise AI security questionnaires and procurement blocks
- Turn OWASP LLM Top 10 and NIST AI RMF into concrete engineering actions
- Reduce prompt injection, data leakage, and third-party model risk
- AI architecture and data flow notes
- Findings mapped to OWASP LLM Top 10 and NIST AI RMF
- Prompt injection and abuse test results
- Prioritized remediation and guardrail recommendations
A clear path from scope to remediation
- 01
Scope
Identify AI features, models, data sources, retrieval, and tool integrations in scope.
- 02
Map
Diagram prompts, context, retrieval, tools, outputs, and downstream systems.
- 03
Test
Run prompt injection, data leakage, and abuse tests against user-facing surfaces.
- 04
Assess
Score against OWASP LLM Top 10 and NIST AI RMF, and rate business risk.
- 05
Report
Deliver findings, remediation, and customer-facing AI security narrative.
Explore other ControlSolid services
Readiness & Gap Assessment
The core ControlSolid engagement — cybersecurity readiness and gap assessment for SaaS, fintech, healthcare, payment, and technology teams preparing for audits, customer security reviews, and compliance deadlines.
Learn more →Web Pen Testing
Manual web app and API penetration testing aligned to OWASP, with severity-ranked findings, reproduction steps, and remediation retest.
Learn more →- Application & cloud security reviews →Underlying architecture and cloud posture that AI features depend on.
- Web application penetration testing →Traditional web and API testing for surfaces that host LLM features.
- vCISO & customer security reviews →Ongoing support for AI-specific questionnaires and enterprise procurement conversations.
- SOC 2 Type 1 & Type 2 readiness →Compliance foundation most buyers expect alongside a credible AI security story.
Need a clear view of your security gaps?
Start with a focused readiness call. We'll discuss your customer pressure, compliance goals, application risk, and the best next step.