GET STARTED

01

AI Penetration Testing and Assurance

Five SErvices. One Standard.

Access is the attack surface. Your AI touches data, tools, and business systems worth stealing or abusing. We pressure-test that access hands-on, from the model and its agents down to the cloud underneath, and show what’s exploitable.

Offense for Every Layer of AI

Five services in three practices. Each one attacks your AI from a different angle, from testing a single system to emulating a determined adversary.

Red Team & Readiness

Emulate a real adversary chasing one objective, then find out whether your team notices and responds. AI Red Team & Readiness

Meet Your Program Where It Is

Day one rarely calls for a red team. Map your exposure first, attack the AI system you rely on most next, then retest it when it changes.

Map the Attack Surface

AI Threat & Exposure Assessment

Chart what your AI can reach, from data and permissions to vendor boundaries, and pinpoint the attack paths worth testing.

Ideal for: Copilots, third-party AI, internal RAG, low-code automations, and early agents that have never had a structured security review.

What you get:

  • Clear understanding of your systems, how data moves, and who can reach it
  • AI inventory and threat model, mapped to MITRE ATLAS and OWASP
  • Ranked risk register, recommended test scope, and a stakeholder workshop

Attack the Full Stack

AI Penetration Testing

Hands-on penetration testing across your AI stack, from the model and application to agents and cloud, confirming which weaknesses an attacker can actually exploit.

Ideal for: LLM applications and chatbots, AI agents, RAG pipelines, and custom or fine-tuned models, plus the cloud and third-party integrations behind them.

What you get:

  • Executive summary tied to business impact
  • Technical report with severity ratings, proof-of-concept, and cross-layer attack chains
  • Remediation workshop, plus optional retesting

Test as Your AI Evolves

Continuous AI Penetration Testing

Keep testing as your AI changes. We retest across the full stack on a set schedule and whenever you swap a model, add an agent or data source, or change prompts or permissions.

Ideal for: AI systems with a completed penetration test whose models, prompts, agents, tools, data sources, or permissions keep changing.

What you get:

  • Ongoing testing as you add models, agents, and integrations
  • Validated findings as new exposures appear, with fix guidance
  • Fix verification and trend reporting over time

Advanced and Specialty

Emulate a Real Adversary

AI Red Team & Readiness

Emulate a real attacker across your entire AI pipeline, then test your detection with purple teaming and your response with tabletop exercises.

Ideal for: Mature security programs that want to validate real-world resilience, especially after a major AI rollout or when facing targeted threats.

What you get:

  • Attack graphs and narratives mapped to MITRE ATT&CK and ATLAS
  • Detection and response gaps, prioritized with risk context
  • Findings walkthrough and debrief with your security team

Secure the AI You Host

Self-Hosted AI Security Assessment

Find and test the AI you run yourself: exposed model servers like Ollama and vLLM, MCP servers, the model files you download, and the GPUs underneath.

Ideal for: Organizations running AI on hardware they control, from one workstation running Ollama to shared GPU servers and MCP servers.

What you get:

  • Inventory of every model server, MCP server, and AI endpoint you run
  • Validated findings on exposure, model files, and isolation
  • Findings walkthrough, prioritized fixes, and optional retesting

Match the Test to the Question

Proposals blur these terms. Here’s exactly what each engagement answers, so the work you buy fits the decision you need to make.

How the engagements compare
EngagementWhat it answersHow it runsRight for
AI Threat & Exposure AssessmentWhat can our AI actually reach, and what deserves a test?Threat modeling plus architecture, permission, and data-flow analysis. Nothing is actively exploited.Teams early in AI adoption or leaning on vendor AI
AI Penetration TestingWhich weaknesses across this system’s stack are exploitable, and what would they cost us?Hands-on attacks on the model, application, agents, and infrastructure of one defined system; nothing is reported until it’s validated.One live or pre-launch AI system that has a named technical owner
AI Red Team & ReadinessCould a realistic adversary reach a specific goal, and would we notice?Multistep adversary emulation across people, cloud, pipelines, models, and tools, plus purple teaming and a tabletop.Mature programs that have logging, response plans, and clear system ownership
Continuous AI Penetration TestingDid this change reopen an old weakness or open a new one?Targeted retesting across the stack on a schedule and after material changes, built from your penetration test findings.Systems that already finished an AI penetration test
Self-Hosted AI Security AssessmentCould an attacker reach the AI we run on our own hardware?Discovery, fingerprinting, and hands-on testing of every model server, MCP server, and model file you host.Teams running models on workstations, GPU servers, or MCP servers they control

Built Into Every Engagement

Whatever you choose, the standard doesn’t bend. Findings are validated, and the results hold up for engineers, risk owners, and executives alike.

AI Is All We Do

Offensive security for AI is our entire focus: models, applications, agents, and the infrastructure beneath them.

Senior-Led, Start to Finish

The person who scopes your engagement runs the testing and walks your team through the fix.

Real-World Attacks

Expert testers chain weaknesses the way an adversary would, with controlled automation adding breadth, instead of replaying a checklist.

Validated Findings

Nothing reaches your report until we’ve reproduced the attack path and confirmed its impact, with requests, prompts, traces, and proof-of-concept artifacts.

Root Causes, Ranked Fixes

The broken safeguard or flawed design assumption behind each finding, plus near-term and longer-term fixes in priority order.

Rules and Limits in Writing

Boundaries, off-limits actions, and stop procedures are set before testing starts, and every report states its method, scope, and what wasn’t tested.

AI Security Testing Explained

What is AI penetration testing?

Think of it as a hands-on attack on a working AI system at every layer: the model, the application, its agents and tools, and the cloud infrastructure it relies on. Frostfire Labs delivers it as AI Penetration Testing.

Should I choose an AI penetration test or an AI red team?

Choose a penetration test when you want broad, systematic coverage of one defined system. Choose a red team when you want to chase one defined objective, linking weaknesses across identities, data, models, tools, and business processes like a determined attacker, and to learn whether your team notices and responds. We use “red team” only for that kind of exercise.

Where should we start?

Not sure what your AI can reach, or what deserves a test? Start with the AI Threat & Exposure Assessment. Already have a defined system and a technical owner? Go straight to AI Penetration Testing. Your scope review will confirm the right first step.

Can you test AI that runs on a third-party provider’s platform?

Yes, within limits. We test the pieces you control, such as your prompts, retrieval, application, tools, permissions, and integrations, and how they call the provider’s model, staying inside the provider’s own published terms for use and testing.

Is automated AI security testing enough?

No. Automation is great at replaying known injection and bypass tricks in bulk. It struggles with multi-step chains, say a hidden instruction in a shared file that talks an agent into emailing a customer record to an outside address, and it can’t judge what that chain would cost your business. We lean on automation for breadth and on human testers for chaining and judgment.

Will AI security testing make us compliant?

No. Testing alone can’t make an organization compliant, and certifying compliance isn’t something we do. You get a clear record instead: what we tested, what we found, which frameworks each finding maps to, and, if retesting is in scope, whether your fixes held. Bring it to auditors, insurers, customers, and regulators.

Does any law require an AI penetration test or an AI red team?

Generally, no. No broad U.S. law currently obliges most organizations to purchase something labeled an “AI red team” or an “AI penetration test.” Rules that do apply tend to call for traditional penetration testing, independent review, documentation, and model testing and validation, and we’ll show you which of those our work supports and which need other specialists. Applicability turns on your organization and jurisdiction, so check with counsel. This isn’t legal advice.

Will testing disrupt our production systems?

Testing follows defined rules of engagement, and we favor staging or test environments. Any production work stays inside set rate, cost, and data limits, with clear stop procedures.

Find the Test That Fits

Tell us what you’re building or running. We’ll recommend an engagement and a scope that fits.