What is AI chatbot penetration testing?

AI chatbot penetration testing is a structured security assessment that simulates real-world attacks against your AI chatbot system. Our security engineers test for prompt injection, jailbreaking, data exfiltration, RAG poisoning, context manipulation, and API abuse — the same vulnerabilities catalogued in the OWASP LLM Top 10.

How much does AI chatbot penetration testing cost?

Our pricing is EUR 2,400 per man-day. A standard assessment for a production chatbot typically requires 2–5 man-days depending on the number of integrations, knowledge sources, and API endpoints in scope. We provide a fixed-price quote after a free scoping call.

What is included in the deliverables?

You receive a detailed written report covering: executive summary, attack surface map, findings ranked by CVSS-equivalent severity, proof-of-concept attack demonstrations, remediation recommendations with effort estimates, and a re-test slot to verify fixes.

Why is FlowHunt qualified to test AI chatbots?

We built FlowHunt — one of the most capable AI chatbot and workflow automation platforms available. We understand how LLM-based chatbots work at the architecture level: how system prompts are constructed, how RAG retrieval pipelines can be poisoned, how context windows are managed, and how API integrations can be abused. That insider knowledge makes our assessments deeper and more accurate than generalist security firms.

Do you test chatbots built on other platforms?

Yes. We test AI chatbots built on any platform — GPT-based, Claude-based, Gemini-based, or open-source LLMs — whether deployed via API, embedded widget, or custom infrastructure. Our methodology is model-agnostic.

What is the OWASP LLM Top 10?

The OWASP LLM Top 10 is the industry-standard list of the most critical security risks for applications built on large language models. It covers prompt injection, insecure output handling, training data poisoning, model denial of service, supply chain vulnerabilities, and more. Our testing methodology maps directly to all 10 categories.

How long does a chatbot penetration test take?

A standard scoped assessment takes 2–5 man-days of active testing, plus 1 man-day for report writing and review. Total calendar time from kick-off to final report is typically 1–2 weeks.

AI Chatbot Penetration Testing

Your chatbot is your new attack surface. We simulate the full range of LLM-specific attacks — prompt injection, jailbreaking, RAG poisoning, data exfiltration, and API abuse — and deliver a prioritized remediation report. Built by the team behind FlowHunt.

Request a Security Assessment Learn About Our Methodology

AI Chatbot Security Testing

Traditional penetration testing methodologies were not designed for AI systems. LLM-based chatbots have unique attack surfaces — natural language interfaces, RAG retrieval pipelines, tool integrations, and context window management — that require specialized testing techniques.

What Makes AI Chatbots Different to Test

Unlike traditional web applications, AI chatbots process natural language and can be manipulated through the very interface they were designed to use. A chatbot that passes all conventional security checks can still be vulnerable to prompt injection, jailbreaking, and RAG poisoning attacks.

Prompt Injection (OWASP LLM01): Attackers embed instructions in user input or retrieved content to override your chatbot's intended behavior.
Jailbreaking: Technique-based attacks bypass safety guardrails to make your chatbot produce policy-violating or harmful outputs.
RAG Poisoning: Malicious content injected into your knowledge base causes your chatbot to retrieve and act on attacker-controlled data.
Data Exfiltration: Crafted prompts extract PII, credentials, API keys, or business intelligence from your chatbot's accessible data.

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Our Testing Methodology

Every engagement follows a structured, OWASP LLM Top 10-aligned methodology. We map every finding to a recognized vulnerability category so your team can prioritize remediation with confidence.

Phase 1 — Reconnaissance & Attack Surface Mapping: We document all input vectors, system prompt structures, RAG pipelines, tool integrations, and API endpoints.
Phase 2 — Active Attack Simulation: We execute the full OWASP LLM Top 10 attack catalog including prompt injection, jailbreaking, context manipulation, token smuggling, and indirect injection.
Phase 3 — Data Exfiltration Testing: We attempt to extract system prompt contents, PII from connected data sources, API credentials, and business-sensitive information.
Phase 4 — API & Infrastructure Testing: We test authentication, rate limiting, authorization boundaries, and API endpoint abuse scenarios.
Phase 5 — Reporting & Remediation Guidance: Detailed report with findings, proof-of-concept payloads, severity ratings, and prioritized remediation steps.

Download Methodology Overview

ATTACK COVERAGE

What We Test

Our assessments cover every major attack surface specific to LLM-based AI chatbots

Prompt Injection: Direct and indirect injection attacks including role-play manipulation, multi-turn sequences, and environment-based injection through retrieved content
Jailbreaking: Safety guardrail bypass techniques including DAN variants, persona attacks, token smuggling, and multi-step manipulation sequences
RAG Poisoning: Knowledge base contamination attacks that cause your chatbot to retrieve and act on malicious, attacker-controlled content from your own data sources
System Prompt Extraction: Techniques to reveal confidential system prompt contents, business rules, safety instructions, and configuration secrets that should remain private
Data Exfiltration: Attacks that extract PII, API credentials, internal business data, and sensitive documents from the chatbot's connected data sources and context
API & Auth Abuse: Rate limit bypass, authentication weakness exploitation, authorization boundary testing, and denial-of-service scenarios against LLM API endpoints

Pricing & Packages

Transparent, complexity-based pricing. Every engagement starts with a free scoping call to define the assessment boundaries and provide a fixed-price quote.

Basic Assessment (2 man-days / EUR 4,800): Simple chatbot with a single knowledge base and no external tool integrations. Covers prompt injection, jailbreaking, system prompt extraction, and basic data exfiltration.
Standard Assessment (3–4 man-days / EUR 7,200–9,600): Chatbot with RAG pipeline, 1–3 external tool integrations, and user authentication. Full attack simulation plus API endpoint testing.
Advanced Assessment (5+ man-days / EUR 12,000+): Autonomous AI agents, multi-step workflows, complex tool ecosystems, or multiple chatbot instances. Includes threat modeling workshop.
Re-test included: All packages include a free re-test slot within 30 days of report delivery to verify remediation.

Per Man-Day: EUR 2,400
Scoping Call: Free

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Why FlowHunt Is Uniquely Qualified

We don't just test chatbots — we built one of the most advanced AI chatbot platforms available. That insider knowledge makes our security assessments deeper and more accurate.

We Built the Platform: FlowHunt is a production AI chatbot and workflow automation platform. We understand LLM architecture, RAG pipelines, and tool integrations from the inside.
We Know the Failure Modes: Years of operating FlowHunt in production means we have encountered and patched real vulnerabilities — not just theoretical ones from research papers.
OWASP LLM Top 10 Aligned: Our methodology maps to every category in the OWASP LLM Top 10, providing a standardized, auditable assessment framework.
Developer-Friendly Reports: Findings are written for engineering teams — with specific code-level recommendations, not just high-level observations.
Full Confidentiality: All engagements are covered by NDA. Attack payloads, findings, and system details are never shared or reused.
Fast Turnaround: Standard assessments complete within 1–2 weeks from kick-off. Urgent assessments available for time-sensitive situations.

What You Receive

Every engagement delivers a structured, actionable security report — written for both executives and engineering teams.

Executive Summary: Non-technical overview of findings, risk posture, and remediation priorities for leadership.
Attack Surface Map: Full diagram of your chatbot's components, data flows, and identified entry points.
Findings Register: All vulnerabilities with severity (Critical / High / Medium / Low / Informational), CVSS-equivalent score, and OWASP LLM Top 10 mapping.
Proof-of-Concept Demonstrations: Reproducible attack payloads for every confirmed finding, so your team can verify and understand the vulnerability.
Remediation Guidance: Specific, prioritized fixes with effort estimates — including code-level recommendations where applicable.
Re-test Report: Follow-up assessment within 30 days confirming which findings have been successfully remediated.

Request a Sample Report

Book Your AI Chatbot Security Assessment

Tell us about your chatbot — platform, integrations, and what you want to protect. We'll respond within 1 business day with a scoping questionnaire and available dates.

AiMingle, s.r.o.
Čistovická 1729/60
163 00 Praha 6
Czech Republic, EU

+421 2 33 456 826

support@flowhunt.io

Frequently asked questions

: AI chatbot penetration testing is a structured security assessment that simulates real-world attacks against your AI chatbot system. Our security engineers test for prompt injection, jailbreaking, data exfiltration, RAG poisoning, context manipulation, and API abuse — the same vulnerabilities catalogued in the OWASP LLM Top 10.
: Our pricing is EUR 2,400 per man-day. A standard assessment for a production chatbot typically requires 2–5 man-days depending on the number of integrations, knowledge sources, and API endpoints in scope. We provide a fixed-price quote after a free scoping call.
: You receive a detailed written report covering: executive summary, attack surface map, findings ranked by CVSS-equivalent severity, proof-of-concept attack demonstrations, remediation recommendations with effort estimates, and a re-test slot to verify fixes.
: We built FlowHunt — one of the most capable AI chatbot and workflow automation platforms available. We understand how LLM-based chatbots work at the architecture level: how system prompts are constructed, how RAG retrieval pipelines can be poisoned, how context windows are managed, and how API integrations can be abused. That insider knowledge makes our assessments deeper and more accurate than generalist security firms.
: Yes. We test AI chatbots built on any platform — GPT-based, Claude-based, Gemini-based, or open-source LLMs — whether deployed via API, embedded widget, or custom infrastructure. Our methodology is model-agnostic.
: The OWASP LLM Top 10 is the industry-standard list of the most critical security risks for applications built on large language models. It covers prompt injection, insecure output handling, training data poisoning, model denial of service, supply chain vulnerabilities, and more. Our testing methodology maps directly to all 10 categories.
: A standard scoped assessment takes 2–5 man-days of active testing, plus 1 man-day for report writing and review. Total calendar time from kick-off to final report is typically 1–2 weeks.

Book Your AI Chatbot Penetration Test

Get a comprehensive security assessment of your AI chatbot from the team that builds and operates FlowHunt. We know exactly where chatbots break — and how attackers exploit it.

Request a Security Assessment Try it now

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