Security for LLMs.
Atrial AI Security operates inline across every conversation powered by an LLM — inspecting traffic in both directions, in real time.
Every AI security vendor is solving for attacks against the model. We also solve for exploitation through the model.
Two distinct attack surfaces. The prompt-injection category covers one of them. We cover both — with the second being a category most security stacks don't see yet.
Attacks against the model
Technical attack vectors at the request/response boundary. Well-understood category, table stakes for AI security — we ship all of this out of the box.
- ✓Prompt injection (direct and indirect)
- ✓Data leakage from prompts
- ✓Jailbreaking and policy bypass
- ✓Model extraction attempts
Exploitation through the model
Business logic and behavior at the session level. The OWASP LLM Top 10 hasn't formally defined this yet — and most stacks have no instrumentation for it.
- ✓Multi-turn manipulation & trajectory analysis
- ✓Business logic abuse & policy exception-chasing
- ✓Agentic AI detection — tool-call & autonomous-action abuse
- ✓Cross-session attack coordination
Inbound, session, outbound, async.
Every conversation inspected in both directions. Stateful analysis across turns — not just per-message classification. Topology-agnostic; sits wherever the LLM-processing endpoint lives.
Before it reaches the model
- Prompt injection — direct and indirect
- Jailbreak taxonomy (behavioral, not strings)
- PII / sensitive ingress classification
- Policy preflight against declared intent
Across the whole conversation
- Trajectory analysis turn-over-turn
- Agentic AI detection — tool-call & autonomous-action abuse
- Cross-session identity correlation
- Business logic abuse — refund, privilege & exception coercion
Before the reply leaves
- Secret & credential egress redaction
- PII egress controls
- Grounding enforcement vs. approved sources
- Policy postflight on every response
After the fact, across tenants
- Progressive, multi-day campaigns
- Anomaly correlation across endpoints
- Behavior drift alerting
- Full audit & replay queryable history
One platform. Scored for your business.
Generic AI security catches generic attacks. Atrial AI Security ships with industry-specific risk signals out of the box and tunes its scoring to your company's policies, products, and risk appetite — then keeps a complete record of every conversation so you can investigate and improve over time.
Scoring tuned to your sector and your business logic.
Out-of-the-box risk patterns and severity weights aligned to the threat model your industry actually faces. Scoring conversations at the intent layer against how your business is supposed to operate.
Every conversation stored, queryable, replayable.
Complete inspected traffic persisted in the analytics backend. Investigate incidents after the fact, replay sessions against new policies before you ship them, and validate coverage against real history.
Tuned and watched, around the clock.
Atrial AI Security is a managed service. Our 24/7 SOC tunes detections to your environment, triages alerts, and escalates incidents that need a human — so your team gets coverage, not a console.
"Organizations are increasingly recognizing business logic abuse as one of the most critical LLM security risks."— Bright Security, The 2026 State of LLM Security
Contact us.
Tell us a little about your environment and we'll get back to you within one business day. We can scope a proof-of-value against your real traffic — no production changes required — so you can see exactly what we'd catch.