AccuKnox [Gen-AI CNAPP Security]

AI SPM builds an agentless inventory of every model, agent, dataset, and pipeline across cloud and on-prem, which means you finally see the models your teams spun up without telling anyone. It flags shadow AI, like unapproved notebooks or rogue MCP servers. It also generates an AI Bill of Materials per model with EU AI Act risk tiering built in. The pitch is simple. Continuous visibility without installing anything on the workloads themselves.

AccuKnox sandboxes each AI agent at runtime using eBPF and Linux Security Modules, so enforcement happens outside the application and a misbehaving agent can't reach tools it was never granted access to. It enforces least-privilege tool access and blocks unauthorized calls before they run. It also watches for memory poisoning and cascading hallucinations. You get all of this without changing agent code. That matters a lot when agents are already deployed.

Most prompt firewalls inspect one message at a time. AccuKnox tracks the whole conversation, which lets it catch jailbreaks that unfold over 5-15 messages where the harmful intent only becomes clear several turns in. It masks PII, PHI, and card numbers in real time and blocks leaked API keys and credentials. The same policy can be applied in several places. Think API gateway, SDK, browser plugin, and Copilot Studio.

The platform scans the five major model formats for supply-chain tampering and deserialization attacks, which matters because a compromised model pulled from a public repo can quietly leak data long after deployment. It flags integrity problems in public Hugging Face or GitHub models before you deploy them, and it scans training data for PII and PHI. Re-scans run automatically. Every fine-tune triggers one, tagged to the OWASP LLM Top 10 and MITRE ATLAS.

AI DR ingests AWS, Azure, and GCP logs continuously and catches unapproved deployments as they happen, so a workload that appears outside your pipeline gets flagged before it has time to spread across the estate. It correlates signals across layers to reconstruct multi-step attack chains. It makes exposed model endpoints private automatically. Incidents then push into Jira, ServiceNow, Slack, or PagerDuty with forensic context attached.

Beyond AI, the platform covers classic cloud-native security: image scanning, Kubernetes policy enforcement, and runtime defense against container attacks. It uses the same policy engine as the AI modules. A misconfiguration in code stays linked to the container and model affected downstream. That traceability is the core differentiator against posture-only scanners. Posture tools alone won't give you it. Not even close.

Every finding is auto-tagged to frameworks such as OWASP, MITRE ATLAS, NIST AI RMF, and the EU AI Act, so the same evidence serves a security review, a model risk assessment, and a regulatory audit without a second pass. The platform classifies an EU AI Act risk tier the moment a model is discovered and generates audit-ready reports on demand. No more weeks of manual evidence-gathering. It supports governance across 12+ frameworks from one dashboard, in SaaS or air-gapped mode.

AccuKnox runs on-premise, air-gapped, and across public cloud, private cloud, and edge or IoT environments, so the same platform follows your workloads whether they sit in a hyperscaler region or a factory floor. For regulated industries that can't send telemetry to a vendor cloud, the air-gapped option is the practical path. The trade-off? Self-hosted setups usually add operational overhead you'd avoid with pure SaaS.