AI Security

AI security for the data, tools and actions that matter.

Your AI application may read private information and act through connected tools. We assess the agreed data and action boundaries, test realistic abuse cases and implement prioritized controls within the commissioned scope.

Scope your AI security review →

DIRECT ANSWER

AI Security reviews the system around an LLM: identities, retrieval, memory, connected tools and actions. Findings, agreed fixes and retests make the tested boundaries and remaining limitations explicit.

Best for

  • An existing AI feature with private data, tools or write permissions
  • A team that needs a bounded security review and actionable remediation

Consider another approach

  • Building a new AI product or planning organization-wide adoption
  • An ordinary web app that was generated with AI but has no AI features

Review what the application can reach and change

Map users, service identities, model providers, retrieval sources, memory and tools. Define the actions that need explicit authorization. This is about a product that uses AI. If the immediate problem is a fragile AI-generated codebase, start with Vibe Coding Rescue; if the product still needs building, use AI Agents & Products. A broad pre-investment or pre-acquisition review that only flags AI risks among other findings is Technical Due Diligence; adversarial testing of the agreed boundaries stays here.

Test the controls around the model

Choose cases from your application’s actual authority. A convincing answer and a successful demo do not establish that data access or tool execution is authorized.

Data and tenant boundaries

Check which identity can retrieve, read and retain each source. Include revoked permissions, restricted records and shared memory where relevant.

Tools and approvals

Scope tool permissions and validate sensitive actions in the executing system. Check how approvals are bound to the actor, target and exact requested action.

Untrusted content

Exercise agreed prompt-injection, retrieval or tool-output abuse cases and trace their effect on data and actions.

Containment and evidence

Review relevant execution limits, credential scope, sandboxing and audit records. Scope the running infrastructure with Cloud Security when needed.

Illustrative acceptance: one tenant cannot retrieve another tenant’s record

Using synthetic data, a user from tenant A asks the agent for tenant B’s record. The data-access layer denies the request even when the model formulates the tool call. An authorized request inside tenant A still succeeds. Record the build, policy and retrieval configuration, expected result, observed behavior and logs. This is an illustrative test, not a customer outcome or proof of coverage across every tool.

Turn a confirmed finding into a verified change

Assessment and remediation are separate commitments. Agree coverage, permitted actions and retest scope before work starts.

  1. Assessment

    Receive the system map, agreed abuse cases, reproducible findings, coverage gaps and a prioritized remediation plan.

  2. Remediation and retest

    Commission selected code or configuration fixes. Retest the affected behavior and agreed regressions against a recorded system version.

  3. Continued review

    Agree which changes to tools, retrieval, policies, memory, prompts or providers trigger another review. Define cadence and responsibilities separately.

Prepare a bounded environment and a named decision owner

Provide the intended task, tool list, identity model, data classes, known findings and an appropriate test environment. Agree test accounts, permitted actions, load and spending limits, and stop conditions. Authorization belongs in the executing system; prompt wording and filters are additional controls. The OWASP AI Agent Security guidance describes these boundaries and repeatable abuse-case testing.

Keep the results useful to the people running the product

You receive the agreed findings, changes, test records and remaining limitations. Distinguish answer-quality evaluation from access and action checks. DevSecOps covers how changes are released; Cloud Security covers runtime infrastructure. Specialist involvement is defined in the engagement. Our Trust Center explains data handling and service levels. There is no implied 24/7 coverage, formal certification or promise that every attack will be prevented.
// proof

AI engineering experience, with its scope visible

Twinsoft AI documents LLM integration, codebase refactoring and infrastructure work for a pilot-ready product. It demonstrates that delivery scope; it is not presented as a completed AI red-team assessment.

Twinsoft AI

Live
2 weeks To Sellable MVP

Took a vibe-coded prototype to enterprise pilot-ready, no shortcuts.

Python Flask LLMs
AI 2026

These are selected projects, not our full portfolio. We have shipped 100+ products since 2018.

Questions before you start

The service focuses on applications that use an LLM, agent or AI-connected tools. An ordinary AI-generated app may instead need Vibe Coding Rescue, functional QA or a separately scoped application-security review.
Access and sensitive actions need controls in the data or execution system. Prompt rules, filters and model evaluations can support those controls, but do not replace authorization.
We scope the actual sources, identities, tools and permissions. Using a protocol or retrieval framework alone does not establish that its integration enforces the required access boundaries.
General QA does not automatically include a comprehensive AI security assessment or penetration test. We agree the relevant additional scope and acceptance separately.
It records the observed behavior for the tested cases and configuration. The report also identifies untested areas, blocked checks and remaining risks.
We can scope implementation of selected findings and a retest. You can also take the assessment to your own team; the findings and agreed deliverables remain yours.

Choose your next step

Scope your AI security review

Describe what the AI reads, which tools it can call and the actions that need control. Share a non-sensitive outline, without private prompts, documents or access keys.

Scope your AI security review →