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AI Security Review

Test your AI before strangers do.

A public chatbot is an open text box connected to your data. We probe it the way a curious or hostile user would, fix what we find, and check it tells people plainly that it is AI.

Included with every AI build we deliver

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In short

An AI security and transparency review tests a chatbot, voice agent or AI workflow for the ways it can be misused or can mislead people. FIMM tries prompt-injection attacks, checks whether the system can be tricked into exposing private data or misusing its tools, confirms that users are told they are talking to AI, verifies there is a clear path to a human, and checks that conversations are logged. It is included with every AI build we deliver, and we review bots built by others too.

Prompt injection LLM security AI disclosure Human hand-off OWASP LLM Top 10 AI logging
What we build

What we build.

A

Prompt-injection testing

We try direct and hidden instructions, including ones planted in documents and web pages the bot reads, to make it ignore its rules. Findings are fixed in the prompts, filters and architecture, then retested.

B

Data-exposure checks

We test whether the system can be talked into revealing other customers' details, internal documents, system prompts or keys, and whether retrieval respects user permissions.

C

Tool and action limits

For agents that can send email, issue refunds or change records, we check that every action is limited, validated and, where it matters, approved by a person first.

D

AI disclosure

We confirm users are told they are dealing with AI, in chat and on calls. That matches EU AI Act Article 50 for EU-facing clients and the chatbot disclosure rules some US states have adopted.

E

Human hand-off

We test that people can reach a human easily, that complaints and sensitive topics are escalated, and that the hand-off carries the conversation history across.

F

Logging and review

Conversations and actions are logged with sensible retention, so you can investigate a complaint, spot misuse and show what the system did and why.

How it ships

How a security review runs.

On every AI build we deliver, this review runs before launch as a standard step; for bots built elsewhere, we run the same tests against your live or staging system.

01

Map

We document what the AI can see, what it can do, who uses it and where it is deployed.

02

Attack

Structured testing against common AI risks, including the OWASP Top 10 for LLM applications.

03

Fix

On our builds we fix the issues directly; on third-party bots we hand your team or vendor a prioritized fix list.

04

Report

A plain-language report of what was tested, what was found, what was fixed and what to monitor.

Frequently asked

Common questions.

What does the review cost?
It is included with every AI build we deliver, because we will not launch an assistant we have not tested. We can also run the same review on a chatbot built by another vendor, with access to a staging or live instance.
What is prompt injection?
Prompt injection is when someone writes text that tricks an AI into ignoring its instructions, for example to reveal hidden data or take an action it should not. It can be typed directly or hidden in a document or web page the AI reads.
Do we have to tell customers they are talking to AI?
In many cases, yes. EU AI Act Article 50 requires it for systems serving people in the EU, and several US states have chatbot disclosure rules. We set up clear disclosure; we provide technical implementation and do not give legal advice, so confirm your obligations with counsel.
Can you review a chatbot another company built?
Yes. With access to a staging or live instance and a description of what it connects to, we run the same tests and give you a prioritized list of fixes your vendor or team can apply.
Is this a penetration test?
It is a focused test of the AI layer: prompts, retrieval, tools, disclosure and hand-off. It does not replace a full penetration test of your network or application by an independent security firm, and we will tell you when you need one.
Do you keep testing after launch?
Logs and alerts are set up so misuse is visible. Clients on an ongoing support plan get periodic retests, especially after prompt changes, model upgrades or new connected tools, which are when new weaknesses usually appear.
Does this make our AI compliant?
It covers the technical controls that most AI rules expect: disclosure, human oversight, data protection and records. Compliance itself depends on your business and jurisdiction, so we document what we built for your legal advisor to assess.
More services

Explore what else we build.

01

AI Automation

Support agents, lead qualification, and back-office workflows that run themselves, with guardrails and human escalation.

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02

Web & SaaS

SaaS products and MVPs with accounts, billing and dashboards, built to launch fast and scale cleanly.

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03

Mobile Apps

Native-feeling iOS and Android products, from prototype to store, backend included.

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