How to Choose an AI Penetration Testing Vendor (Without Getting Burned)

Why Most AI Pentests Miss the Point

You shipped a chatbot, a copilot, or an AI-powered search feature. Your VP of Engineering is asking whether it’s been security tested. Your compliance team needs evidence for the SOC 2 audit. So you start Googling for AI penetration testing vendors.

Here’s the problem: most pentest firms that claim to test AI are actually just running their standard web application test and calling it an “AI assessment.” They’ll scan your API endpoints, check for SQL injection, and hand you a report. But they won’t test the AI itself — the prompts, the model behavior, the data flows, the failure modes that are unique to LLM-powered applications.

What to Look For in an AI Security Testing Vendor

1. Ask About Their AI-Specific Methodology

Any vendor worth hiring should be able to walk you through their specific approach to testing AI systems. If their methodology doesn’t include prompt injection testing, jailbreak assessment, data leakage probing, and output safety validation — they’re running a web app pentest with an AI label on it.

At minimum, their testing should map to the OWASP Top 10 for LLM Applications. If they can’t name those 10 categories without looking them up, keep looking.

2. Ask Who Will Actually Do the Testing

The biggest bait-and-switch in the pentest industry: a senior expert sells you the engagement, then a junior analyst does the work. Ask directly: “Who will be hands-on-keyboard testing my application?” and get that name in the contract.

For AI testing specifically, the tester needs experience with adversarial ML — not just web application security. These are different skill sets. A great web app pentester might have no idea how to test for prompt injection or model extraction.

3. Check Their Testing Scope

AI systems don’t exist in isolation. Your chatbot sits on top of a web application, talks to an API, queries a vector database, and calls an LLM. A proper AI security assessment tests the entire stack — not just the AI layer.

Ask: “Does your assessment cover the application, the infrastructure, AND the AI components?” If they only test one layer, you’ll need to hire a second firm for the rest.

4. Look at Their Report Format

You need two things from a pentest report: something your board can understand and something your engineers can act on. The best vendors deliver both — an executive summary with business impact and risk ratings, plus a technical report with proof-of-concept exploits and step-by-step remediation guidance.

5. Ask About Retesting

A pentest without retesting is like a health checkup without follow-up. You fix the vulnerabilities, but how do you prove they’re actually fixed? Make sure retesting is included — not sold as an add-on.

6. Compare Response Time

The average pentest firm takes 4-6 weeks to start an engagement. By the time they deliver the report, your AI has been in production for two months with unknown vulnerabilities. Look for vendors who can start within days, not weeks.

Red Flags When Evaluating Vendors

They lead with automated scanning. AI systems need manual testing by human experts. Automated scanners can’t test for prompt injection, social engineering attacks on AI, or business logic flaws in AI-powered workflows.

They can’t explain OWASP Top 10 for LLMs. This is the industry standard framework for AI security. If they’re not using it, they’re making up their methodology as they go.

They quote without scoping. Every AI system is different. A vendor who gives you a price without understanding your architecture is either going to underdeliver or overcharge.

They don’t include remediation guidance. Finding vulnerabilities is only half the job. You need to know exactly how to fix each one.

What a Good AI Pentest Engagement Looks Like

A proper engagement follows this pattern: scoping call to understand your architecture, fixed-price quote based on actual scope, 2-week testing window, two reports (executive and technical), live findings walkthrough with your team, and a 30-day retesting window to verify your fixes.

Total timeline from first call to clean report: typically 4-6 weeks. Total cost for a mid-market SaaS application with AI features: typically $12,000-$20,000.

If this sounds like what you need, book a free scoping call — we’ll review your application and give you a fixed-price quote with no obligations.