Enterprise

Secure your AI platform.

Full attack surface coverage — runtime monitoring, model health, agent security, supply chain analysis, and audit-ready compliance. Everything SPR{K3 builds, deployed for your infrastructure. No access to your systems required.

What you get

◈ Scan

Static analysis of your ML codebase. Pickle, torch.load, trust_remote_code, supply chain, CI/CD exposure. 760+ detection patterns from real CVE research.

◇ Defend

Runtime process monitoring. Impossible-state detection via decay correlator. Agent mesh across your infrastructure. Metadata only — never reads file contents.

▣ Defend Agents

Prompt injection, tool misuse, heartbeat anti-tamper, relay poisoning detection. All detection client-side, server sees metadata only.

⬡ BrainGuard

LLM cognitive health monitoring. Degradation, poisoning, sandbagging, reasoning consistency. Five attack pattern classes specific to your application layer.

Who this is for

Security Teams

Running ML in production with no runtime visibility into what models and pipelines are executing. The assessment finds the exposure. Defend closes the gap.

AI Platform Suppliers

Building infrastructure other teams run ML on. A single unsafe deserialization in your platform is a vulnerability in every customer environment.

Compliance Officers

Auditors want evidence. NIST AI RMF reports generated from actual findings, not self-assessments.

ML Platform Teams

Managing training clusters, serving infrastructure, model registries. Full stack visibility from code to runtime.

Engagement options
01

ML Security Findings Report

Documented vulnerabilities specific to your ML stack. Scope gap analysis, propagation paths, remediation guidance.

02

Vendor Scope Gap Audit

Maps every ML component to its vendor threat model. Identifies where vendor assumptions don't hold in your topology.

03

BrainGuard Assessment

Five cognitive attack pattern classes across your LLM application layer. Context integrity, pipeline taint, reasoning consistency.

04

Supply Chain Audit

Cross-repository temporal correlation across your entire ML dependency tree. Package integrity, model provenance.

05

ML Security Readiness Report

Pre-deployment certification. SOC 2 evidence, board reporting artifact, NIST AI RMF mapping.

06

Continuous Monitoring Retainer

Weekly scans, prioritized triage, early warning on coordinated attacks. Direct access to the research team.

07

Runtime Defense Layer

Defend deployed into your ML pipeline. Passive or active mode. Auto-updating pattern registry. Decay correlator for impossible-state detection.

IR

Incident Response Retainer

4-hour SLA. When the next supply chain attack hits, we scan your stack and tell you affected or clean.

Track record
14
CVEs across
NVIDIA bulletins
760+
Detection patterns
in registry
7
Major vendors
confirmed findings
<3%
False positive rate
vs 30% industry
NVIDIA   META   MICROSOFT   GOOGLE   AMAZON   HUGGINGFACE   INTEL

Response within 1 business day. No access to your systems required.