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Plug in your models, agents, tools, and data sources.
Adaptive offensive security and quality control for Artificial Intelligence.
Continuous red-teaming, regression testing, and intelligent model routing — built for enterprise deployments.
The SnowCrash Lab Solution is sought by
Logos shown for illustrative purposes; not endorsements.
What SnowCrash delivers
Continuous Red Teaming Engine
Automated adversarial testing, custom attack library, CI/CD + runtime monitoring
Quality Control Platform
Evaluations & benchmarks, known defects + exploit database, evidence for governance & audit
Safety Router
Routes requests to safer models, enforces policy + controls tools, fails safe when risk rises
Why now
Models change weekly. Every upgrade, fine-tune, or new tool integration can shift behavior and security posture. Most failures are found after launch—when a jailbreak leaks data or an agent takes an unintended action. SnowCrash continuously tests, tracks regressions, and enforces safer routing so issues are caught before they hit production.
Common failure modes we cover
- Jailbreaks and policy bypass
- Prompt injection (especially in tool-using agents)
- Data exposure via retrieval (RAG), plugins, or tool outputs
- Unauthorized or unintended tool/agent actions (e.g., tickets created, emails sent, code executed)
- Unsafe or non-compliant outputs (harassment, self-harm, illegal instructions, intentional sabatoge)
- Model drift and regressions after vendor updates
- Wide variance across models (strong at some tasks, unsafe or weak at others)
How It Works
01
02
Attack
Run automated adversarial suites and custom attack libraries.
03
Measure
Score risk and quality; capture reproducible evidence.
04
Route
Enforce policy and route to the safest-effective model (fail safe when risk rises).
05
Report
Generate audit-ready findings and send alerts/tickets to your workflow.
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