LLM application security
AI Security Assessment
Threat modelling and red-team reviews for LLM, RAG and agent applications: prompt injection, data exfiltration, tool abuse and the OWASP LLM Top 10.
LLM features open new attack paths: injected instructions in documents, leaked system prompts, over-permissioned tools. We test for them and harden the design.
What you get
- Threat model of your AI features and data flows
- Red-team findings with reproducible payloads
- Guardrails: input/output filtering, tool permissions, isolation
- Re-test and sign-off after fixes
Deliverables
- Assessment report mapped to the OWASP LLM Top 10
- Remediation plan and, optionally, the implementation
- Regression tests for the findings
Stack we use
Want to learn it instead? AI Application Security & LLM Red Teaming
From requirements to production
- 01Requirements
A discovery call, then a written scope with acceptance criteria and a realistic estimate.
- 02Design
Architecture, data model and API contracts agreed before code is written.
- 03Build
Short iterations with demos; code reviewed, typed and documented as we go.
- 04Test
Unit, integration and end-to-end tests; QA passes against the acceptance criteria.
- 05Deploy
Docker, CI/CD and cloud setup with monitoring, then a production handover.
- 06Support
Production bug fixing, performance tuning and improvements after launch.
Ways to work together
Fixed-scope project
A written scope, milestones and a fixed price. Best for a defined feature, integration, migration or redesign.
Monthly retainer
Reserved engineering hours every month for ongoing development, maintenance and production support.
Hourly & advisory
Architecture reviews, code reviews, pairing sessions and second opinions, billed by the hour.
Recent work
W3Colleges: a full redesign that kept every URL
This site is our own case study: a new design system, article reader, listing pages, search, login, hub pages and a CI/CD pipeline, delivered as a child theme without touching WordPress core, while 400+ articles, their URLs and SEO metadata stayed intact.
Questions
Is this a penetration test?
It is an application-level security review focused on the AI features and their integrations, not infrastructure penetration testing.
Start a project
Tell us what you are building.
Share the goal, the current state and your timeline. You get a written reply with questions, a suggested approach and an estimate — no sales call required.