# Find the vulnerabilities in your AI before someone else does

> AI security testing from CyberAccord is an adversarial assessment of the LLM features, retrieval-augmented generation (RAG) pipelines, and AI agents you build or deploy. We test for prompt injection, sensitive data leakage, and misuse of connected tools. It suits companies shipping AI features or answering customer questions about AI security.

Source: https://www.cyberaccord.com/services/security-testing/ai-security-testing · Last reviewed: 2026-10-21

Your LLM features, RAG pipelines, and AI agents create attack surfaces a standard pentest does not cover. We test them the way an attacker would and show you how to fix what we find.

## Key facts

- **Methodology:** OWASP Top 10 for LLM Applications
- **Frameworks:** NIST AI RMF, MITRE ATLAS
- **Team credentials:** AIGP, CISSP, CEH, CCSP
- **Typical timeline:** Typically 1–3 weeks
- **Findings:** Human-validated, with reproduction steps

## Why AI features need their own security test

An LLM treats instructions and data as the same thing: text. That creates attack classes, such as prompt injection, that traditional web and API testing does not look for. When a model can read internal documents or call tools on a user's behalf, a successful attack can expose data or take actions you never intended.

Most pentest scopes do not include LLM behavior by default. If your last test covered your web app and API but not the AI layer, that layer has likely never been tested.

## What we test

We work through the risk categories in the OWASP Top 10 for LLM Applications, prioritizing the ones that apply to your design.

- Direct prompt injection and jailbreaks that bypass your instructions and safety controls
- Indirect prompt injection hidden in web pages, documents, emails, or other content the model reads
- Sensitive information disclosure, including system prompt leakage and exposure of other users' data
- RAG weaknesses: retrieval that ignores user permissions, poisoned documents, and vector store exposure
- Excessive agency: agents and tool integrations that can be tricked into unauthorized actions
- Improper output handling, where model output reaches browsers, databases, or code without validation
- Unbounded consumption that can drive up cost or degrade service

## Who needs AI security testing?

Software companies adding chat assistants, copilots, or agents to their products; organizations deploying internal AI tools connected to company data; and anyone whose customers have started asking about AI security in vendor reviews.

If you also need to meet AI governance requirements, such as the EU AI Act, testing results provide useful evidence alongside your risk management documentation.

## What you get

- Map of your AI attack surface: models, prompts, data sources, tools, and trust boundaries
- Prioritized findings with severity, reproduction steps, and example payloads
- Specific remediation guidance written for your engineers
- Executive summary suitable for customer security reviews
- Debrief with your engineering team
- Re-test of fixed findings

## How it works

1. **Scope the AI attack surface.** On a short scoping call we map your LLM features, RAG pipelines, agents, and tool integrations, and agree on what to test.
2. **Adversarial testing.** Our testers work through the relevant OWASP LLM risk categories by hand, including indirect injection through the content your system ingests.
3. **Report and debrief.** You receive a prioritized report of every exploitable issue, and we walk your engineers through the fixes.
4. **Verify fixes.** We re-test resolved findings and update the report so you can share current results.

## Frequently asked questions

### Is this the same as a regular penetration test?

No. A standard web or API pentest follows traditional attack patterns and does not test how an LLM can be manipulated. AI security testing targets prompt injection, data leakage, unsafe tool use, and RAG exposure. Many teams need both.

### We use a third-party model like GPT or Claude. What is there to test?

Quite a lot. The model provider secures the model, but you control the system prompt, the data the model can retrieve, the tools it can call, and what happens to its output. Most serious AI vulnerabilities live in that application layer, which is what we test.

### What do you need from us to start?

Access to the AI feature or API endpoint in a test or staging environment, test accounts at the relevant permission levels, and a short explanation of what data and tools the system can reach. Setup usually takes little of your team's time.

### Can you test AI agents that take actions?

Yes. Agents that send email, query databases, or call internal APIs are a priority because a successful injection can turn into a real action. We test whether an attacker can make the agent exceed the permissions you intended.

### Does AI security testing help with the EU AI Act?

It can support it. The Act expects high-risk AI systems to be accurate, resilient against manipulation, and secure, and adversarial testing produces evidence for that. It is not a full compliance program on its own, which our EU AI Act readiness work covers.

## Related

- [Penetration Testing](https://www.cyberaccord.com/services/security-testing/penetration-testing): Manual, senior-led penetration testing of web apps, APIs, mobile apps, and networks, with prioritized findings and a re-test of fixes.
- [Security Testing](https://www.cyberaccord.com/services/security-testing): Vulnerability assessments, penetration tests, AI security tests, source code analysis, and phishing and social engineering tests, with prioritized fixes.
- [EU AI Act](https://www.cyberaccord.com/compliance/eu-ai-act): EU AI Act readiness: provider and deployer classification, risk-tier mapping, gap analysis and a roadmap aligned to the Act's phased dates.
- [NIST](https://www.cyberaccord.com/compliance/nist): NIST gap assessments against CSF 2.0, SP 800-171 and SP 800-53, with scored findings and a prioritized remediation plan.

## Contact CyberAccord

- Book a free consultation: https://www.cyberaccord.com/contact
- Phone: +1 (832) 429-5665
- Email: info@cyberaccord.com
- Office: 8990 Kirby Dr, Suite 220, Houston, TX 77054