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.
Attackers Find Gaps. We Find Them First.
Offensive security for AI. We attack your models, agents and data the way real adversaries do.
Phished sessionStolen token
1
Client-controlled system
Staff accountIdentity
2
AI assistantAssistant
3
Firm-wide searchOver-permissioned
4
Restricted mattersData
5
Bulk summary outExternal
An attacker uses a phished session token to get into a staff account, then uses the firm’s AI assistant to search every file that account can reach, including restricted matters the user never opened, and moves summaries of that data outside the organization.
- 1–2Stolen session bypasses MFA and lands in a staff account
- 3–4Assistant finds files the user could reach but never opened
- 5Weeks of recon happen in minutes
FindingAccount takeover → AI-accelerated exposure
Core Services
Three Pillars of AI Offense
No two AI systems break the same way. We shape each engagement around your data, your architecture, and the threats that worry you most.
AI Threat & Exposure Assessment
Chart what your AI can reach, from data and permissions to vendor boundaries, and pinpoint the attack paths worth testing.
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
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.
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
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.
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
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.
What We Test
Test Past the Prompt
The prompt is one door. Your AI also inherits risk from what it retrieves, which identities it trusts, which tools it calls, where its output lands, and the infrastructure underneath. A prompt-only test can walk right past the path that matters.
A jailbreak score grades the model. We attack the whole system, from input to action, and confirm which weaknesses carry real business impact.
Attack surfaces in scope:
- Application logic and API behavior
- Identity, access, and tenant isolation
- Retrieval pipelines, memory, and data provenance
- Model guardrails and unsafe output handling
- Agents and their tools, plugins, and MCP servers
- Cloud configuration, secrets, and logging
- Business logic and high-consequence actions
How We Test
Adversary-Driven. Safety-Bound.
Real attackers chain small flaws into serious incidents. Our four-phase method hunts down those hard-to-find chains, confirms them, and explains them, with every move designed to show risk without causing avoidable operational harm.
Scope and Plan
We lock down system boundaries, threat assumptions, off-limits actions, and stop conditions, all tied to the business impact you care about most.
Recon
We chart what an attacker could touch: the application and model, retrieval and data, identities and tools, APIs, and the cloud beneath them.
Exploit and Chain
Hands-on testers run abuse cases built for your system while controlled automation adds breadth. Then we link weaknesses the way a real attacker would.
Validate and Debrief
We reproduce each path, confirm impact, cut false positives, and name the safeguard that gave way. Then we walk your team through root causes and ranked fixes.
Key Outcomes
Findings You Can Act On
Each engagement leaves you with fewer unknown attack paths, sharper remediation priorities, and findings solid enough to decide whether an AI system should launch, scale, or wait.
Expose Confirmed Attack Paths
Every chain is reproduced and confirmed before it reaches your report, so your team spends its time on real risk, not scanner noise.
Prioritize by Business Impact
Each finding names the data, decision, or action at stake, so severity reflects consequence rather than a generic score.
Target Root Causes
We trace each finding to the broken safeguard or flawed design assumption behind it, then rank each fix by how much risk it removes.
Align Executives and Engineers
Executives get a plain-language risk narrative. Engineers get reproducible findings and a live remediation workshop on the fixes they’ll ship.
Each report also spells out method, scope, limitations, and what went untested, so you know exactly where the testing ends.
Industries
Built for High-Consequence AI
We work where AI touches client files, donor and resident records, proprietary designs, and privileged material, and where a single leak, crossed boundary, or rogue action carries a concrete cost.
Engineering
AI over drawings, specifications, bids, and project files, pressure-tested for leaks of proprietary designs and client data, and for automations that reach into project systems.
Non-Profit
AI that handles donor, member, grant, and program records, tested so an assistant or chatbot can’t expose the people you serve or the people who fund you.
Local Government
AI in resident services, permitting, records requests, and internal operations, tested for exposure of resident data and for tools that reach into the systems behind them.
Manufacturing
AI across production, quality, supply-chain, and engineering data, tested for leaks of proprietary processes and for agents that can act on operational systems.
Law Firms
AI over privileged, confidential, and client-owned material, pressure-tested for retrieval leakage between matters, broken client separation, and loose tool permissions.
Accounting and CPA Firms
AI that works with tax returns, financial statements, payroll, and client records, tested for cross-client leakage, exposed credentials, and assistants that reach further than they should.
Why Frostfire Labs
Four Reasons Teams Call Us First
Plenty of security firms now offer AI testing. Here’s what sets ours apart.
AI Is All We Do
We don’t split our attention across networks, web apps, and compliance audits. Every engagement we run targets an AI system, so we know how assistants, agents, retrieval, and model servers actually break, and which fixes your engineers can ship.
The Whole System in One Engagement
Most AI tests stop at the prompt. We test the agent, the tools and data it reaches, the identities it acts as, and the model underneath, including models you host yourself, backed by our own GPU lab.
Senior Expertise, Start to Finish
The expert who scopes your engagement is the one who tests it and walks your team through the results. No hand-offs to junior staff, no subcontractors, no resellers.
No Products to Sell
We don’t sell security software or platforms, and our fee doesn’t change with what we find. Every recommendation is about your risk, not an upsell. Read our independence commitments.
Informed By
- OWASP Top 10 for LLM Applications
- OWASP Top 10 for Agentic Applications
- OWASP Machine Learning Security Top 10
- MITRE ATLAS
- NIST AI Risk Management Framework
- NIST adversarial ML taxonomy
Frameworks shape the method. Your architecture and business consequences shape the findings.
Get Started
Tell Us Where to Aim.
Describe the AI you’re shipping or already running, and what you need tested. We’ll match you to the right engagement and shape a scope that fits.