AI Security
Your AI, tested like an attacker would.
Adversarial testing and governance for LLMs, AI agents, and the applications you're building AI into. We find what your AI can be turned into.
AI Security Services
AI reaches production faster than security teams can test it. Chatbots, copilots, coding agents, and AI features wired into your applications all add attack surface that traditional testing misses. We test AI the way an attacker will: adversarial testing of the LLMs and agents you deploy, security review of the applications you're wiring AI into, and governance assessment of the AI already running in your environment.
AI & LLM Penetration Testing
We test your deployed AI systems adversarially (prompt injection, jailbreaking, agent manipulation, data extraction) using the same attacker mindset we bring to every engagement.
AI Agent Security Testing
AI agents don't just answer, they act. We test the tools, permissions, and autonomy behind your agents: MCP servers, over-permissioned coding agents, and the injection paths that turn an agent against your own systems.
AI Application Security Review
We review how your applications integrate AI -- data flows to models, output handling, agent connections, RAG pipelines -- finding the vulnerabilities that live at integration points.
AI Security Assessment
We inventory every AI tool in your environment -- chatbots, copilots, agents, embedded SaaS AI -- and assess governance, access, and data handling against current frameworks.
How We Test AI
We bring the same attacker mindset we use on every engagement, adapted to the models, agents, and integrations that make AI a different target. Automated tooling where it helps, manual adversarial work where it counts.
Scoping & AI Discovery
We map what AI you're running and how it's exposed: models, agents, integrations, and the tools and data they can reach.
Adversarial Testing
We attack the AI the way a real adversary would: prompt injection, jailbreaking, data and embedding extraction, and tool and MCP abuse. Where an exploit lands, we push into post-exploitation, escalating and pivoting from the AI into the systems it connects to.
Review & Governance
Where the risk is structural, we review the integration's architecture and assess the controls and policies around your AI.
Reporting & Remediation
Findings are documented with evidence, mapped to AI frameworks, ranked by risk, and paired with fixes we verify on retest.
What You Get
Findings you can act on, evidence you can trust, and a path to fixing what matters.
Findings Report
Every issue documented and mapped to the OWASP Top 10 for LLM Applications (2025), the OWASP Top 10 for Agentic Applications (2026), and MITRE ATLAS, so findings translate directly to your program.
Proof-of-Concept Exploits
Reproduction steps and evidence for each finding, so your team can see exactly what an attacker could do and confirm the fix.
Risk-Ranked Roadmap
Findings prioritized by real-world impact and remediation effort, so you know what to fix first.
Executive Summary
A plain-language read of your AI risk for leadership and the board, without the jargon.
Remediation Guidance
Specific, technical recommendations for each finding, written to work with your developers and your stack.
Free Retest
After you remediate, we verify the fixes so you can close findings with confidence.
Why Breach Craft for AI Security
Real offensive operators
The team that runs our red team and penetration tests runs the AI work. You get an attacker's mindset, not a checklist reviewer.
We test what AI does, not just what it says
Prompt tricks are the start. The real risk is tool access, permissions, and actions, so that's where we push hardest.
Framework-mapped findings
Everything maps to the OWASP Top 10 for LLM Applications (2025) and Agentic Applications (2026), MITRE ATLAS, and NIST's AI guidance, so results plug straight into your program.
Adversarial through governance
We cover the full range: attacking a live agent, reviewing an AI integration's design, and inventorying the shadow AI already running in your environment.
Common Questions
What is AI security testing?
AI security testing evaluates the AI systems you deploy (LLMs, chatbots, copilots, and agents) for the ways an attacker can manipulate or abuse them. It covers adversarial testing such as prompt injection, jailbreaking, data extraction, and tool and MCP abuse; security review of AI-integrated applications; and governance assessment of the AI already running in your environment. At Breach Craft, findings map to the OWASP Top 10 for LLM Applications (2025) and Agentic Applications (2026), MITRE ATLAS, and NIST's AI guidance. The goal is to find what your AI can be turned into before someone else does.
Which AI security service do I need?
It depends on what you're protecting. To attack a live model or agent, start with AI & LLM Penetration Testing or AI Agent Security Testing. To secure an application you're building AI into, start with an AI Application Security Review. To find and govern the AI already in your environment, start with an AI Security Assessment. If you're not sure, we'll help scope it.
Do you test third-party AI or only custom-built?
Both. For third-party AI (vendor chatbots, SaaS AI features, ChatGPT integrations), we test how you've configured and connected it. For custom-built AI, we go deeper into model behavior, RAG pipelines, and agent architecture.
What frameworks do you test against?
Our primary references are the OWASP Top 10 for LLM Applications (2025), the OWASP Top 10 for Agentic Applications (2026), and the OWASP MCP Top 10 for agent tooling. We map findings to MITRE ATLAS, focusing on its LLM, RAG, and agentic techniques and align governance to the NIST AI Risk Management Framework and its Generative AI Profile (NIST AI 600-1), with the CSA MAESTRO agentic threat model and ISO/IEC 42001 as further references. Every finding in the report cites its specific framework and category.
How is this different from a regular penetration test?
The mindset is the same. The attack surface is different. AI adds prompt manipulation, model behavior, tool and agent abuse, and data extraction paths that traditional application and network testing don't cover.
Related Reading
Your AI Governance Policy Won't Stop a Prompt Injection
Why AI governance is necessary but adversarial testing is what proves your AI holds up.
Why Breach Craft for AI Security Risk Assessment
How our AI assessment works and where active testing fits in.
OWASP AI Security: LLM & Agentic Top 10
The primary frameworks we map AI findings to.
NIST AI Profile
NIST's AI risk guidance for governance and program maturity.
Industries We Serve
Organizations across these industries rely on our ai security services.
Ready to Strengthen Your Defenses?
Schedule a free consultation with our security experts to discuss your organization's needs.
Or call us directly at (445) 273-2873