Stop AI
going off-script.
Prompt injection. Compliance breaks.
Agents acting beyond their remit.
AI does not just leak data, it can be manipulated and misused. Anzenna detects prompt injection, compliance violations, and risky agent behavior with the context to act before harm is done.
New tools, new attack surface.
AI tools introduce failure modes traditional security never had to model. A poisoned document triggers prompt injection. A copilot is steered into a compliance violation. An autonomous agent takes an action far beyond what anyone intended.
Point tools see fragments. A prompt firewall inspects one model's traffic. It has no view of the identity behind the request, the data the agent can reach, or whether the behavior is normal for that user.
Preventing misuse means reasoning about the whole picture: the actor, the tool, the data, and the intent, together.
Inventory is the floor. Runtime is the test.
An MCP server can be approved on Monday and behave like an exfiltration tool on Thursday. Anzenna learns what normal looks like for each agent and the person running it, then weighs live behavior against that baseline, so manipulation and drift surface as they happen.
- Prompt injection and jailbreak patterns matched against the request and its source.
- Agent tool-call volume, targets, and data movement scored against a rolling baseline.
- Compliance and policy breaks mapped with the identity and data context behind them.
Three ways AI goes wrong.
Misuse is rarely one event. Anzenna reads the actor, the tool, and the intent together.
A poisoned document triggers prompt injection, steering an assistant off task.
A copilot is pushed into handling regulated data it was never cleared for.
An autonomous agent takes write actions far beyond its intended remit.
A written case, not a silent failure.
A confirmed signal opens a case the agent has already reasoned through.
Catch misuse in context.
Anzenna grounds AI behavior in the same behavioral graph it uses for insider risk, so misuse surfaces as a reasoned case, not an isolated signal.
- 01
Baseline behavior
Learn what normal AI usage looks like per person, role, and agent across your stack over a rolling behavioral window.
- 02
Detect manipulation
Flag prompt injection, jailbreak patterns, and agents taking actions inconsistent with their purpose or the user's intent.
- 03
Map compliance risk
Surface usage that breaks policy or regulatory boundaries, with the data and identity context regulators expect.
- 04
Contain
Quarantine, revoke, or escalate with a fully-reasoned case file and a transparent audit trail.
Firewalls see one model.
Anzenna sees the whole picture.
Prompt firewalls and point tools inspect a single model's traffic. Anzenna reasons over identity, behavior, and data context across your stack, so misuse surfaces with the evidence to act.
| Capability | Anzenna | Prompt firewalls |
|---|---|---|
| Detects prompt injection & jailbreaks | ✓ | ✓ |
| Sees the identity & data behind a request | ✓ | ✗ |
| Catches risky autonomous-agent actions | ✓ | ✗ |
| Maps compliance violations | ✓ | Limited |
| Output | Prioritized, reasoned case file | Blocked request |
| Coverage | Whole stack, 130+ sources | Per-model proxy |
Common questions.
What kinds of AI misuse does Anzenna detect?+
Prompt injection and jailbreak attempts, compliance and policy violations, and autonomous agents taking actions beyond their intended remit. Because Anzenna is grounded in identity and behavior, it weighs each against the actor and the data involved.
How is this different from a prompt firewall?+
A prompt firewall inspects one model's traffic in isolation. Anzenna adds the identity behind the request, the data the tool can reach, and whether the behavior is normal, so you act on real risk instead of blocking blindly.
Does it cover autonomous AI agents?+
Yes. Anzenna baselines agent behavior and flags actions that fall outside an agent's purpose or the user's intent, with a case file showing exactly what happened and why it was risky.
Will it help with AI compliance reporting?+
Anzenna produces a transparent, fully-reasoned audit trail for every flagged event, which gives compliance teams the identity and data context they need to demonstrate control.
Govern AI end to end.
Keep AI on the rails.
Thirty minutes. Your environment. No agents to deploy.