# Security testing for AI chatbots and LLM apps

> Pentesting for AI chatbots and LLM apps: prompt injection, jailbreaks, data leakage, unsafe tool use and RAG exposure. Fix it before attackers find it.

URL: https://cibervault.com/services/ai-security/

Your chatbot talks to customers, reads your data and can call your tools. We attack it the way real adversaries do — then show you how to lock it down.

## What's covered

- Direct & indirect prompt injection attacks
- Jailbreaks and guardrail bypasses
- System-prompt, secret and customer-data leakage
- Unsafe tool, plugin and API actions
- RAG / knowledge-base data exposure
- Abuse, cost and rate-limit attacks

## Process

1. **Map** — We map what your assistant can see, say and do — data sources, tools and integrations.
2. **Attack** — Hands-on adversarial testing of prompts, documents, tools and the surrounding app.
3. **Report** — Findings with real transcripts, impact and practical fixes.
4. **Harden** — Guardrails, least-privilege tool design and monitoring recommendations.

## What you get

- Attack transcripts proving each finding
- Risk ranking by business impact
- Concrete guardrail and architecture fixes
- Guidance for safe ongoing changes

## FAQ

**Why does an AI chatbot need a pentest?**

LLM apps can be manipulated through their inputs. A crafted message or document can make a chatbot leak data, ignore its instructions or misuse the tools it's connected to — normal app pentests don't cover this.

**Which AI platforms do you test?**

Chatbots and LLM features built on hosted models or self-hosted local models — what matters is how your app uses the model, its data and its tools.

**Can you also build a private, local AI instead?**

Yes — see our AI & Automation service for local AI deployments with no cloud dependency.

## Contact

- Book a free 30-minute risk call: https://cibervault.com/contact/
- Email: info@cibervault.com (reply within 24 hours; 24/7 emergency incident support)
- Coverage: worldwide, remote-first — headquarters in Beirut