Runtime AI Defense

Detect prompt injection, tool misuse, and data exfiltration in real time. 19 purpose-built detection rules evaluate every agent interaction with policy-driven allow, deny, and review decisions across 5 enforcement modes.

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AI Agents Are the New Attack Surface

Autonomous agents execute tool calls, access data, and make decisions without human oversight. A single prompt injection can turn a helpful assistant into a data exfiltration vector.

77%

Of LLM apps vulnerable to injection

12min

Avg time to exfiltrate via agent

Detection rules shipping today

<50ms

P95 evaluation latency

How Runtime Defense Works

Every agent interaction is evaluated against the active rule set before execution proceeds.

# Runtime defense pipeline

1.INTERCEPT — Agent request captured at the proxy/SDK layer

2.PARSE — Extract prompt, tool calls, parameters, and context window

3.EVALUATE — Run 19 detection rules against parsed request

4.SCORE — Aggregate rule matches into threat confidence score

5.DECIDE — Apply policy: monitor / alert / review / deny / kill

6.ENFORCE — Execute decision: pass-through, queue, or block

7.LOG — Record full evaluation trace in tamper-evident audit chain

19 Detection Rules Across 4 Categories

Prompt Injection

6 rules

Direct injection, indirect injection via tool output, jailbreak attempts, role-play hijacking, system prompt extraction, instruction override

Tool Misuse

5 rules

Unauthorized tool invocation, parameter tampering, tool chaining abuse, privilege escalation via tools, shadow tool calls

Output Scanning

4 rules

PII leakage in responses, credential exposure, internal URL disclosure, training data regurgitation

Data Exfiltration

4 rules

Encoded payloads in outputs, steganographic channels, bulk data extraction, cross-context data transfer

5 Enforcement Modes

MONITOR

Log all detections silently. Agents proceed uninterrupted while security teams gain visibility.

ALERT

Notify security teams in real time via webhook, Slack, or Teams when a rule fires.

REVIEW

Queue flagged actions for human approval before execution. Agent pauses until reviewed.

DENY

Block the action immediately and return a safe fallback response to the agent.

KILL

Terminate the agent session entirely. Used for critical threats like confirmed exfiltration.

Beyond Guardrails: Full Runtime Defense

Capability	LLM Guardrails	WAF Rules
Prompt injection detection		—
Tool call validation	—	—
Output scanning		—
Data exfiltration detection	—	—
Policy-driven enforcement	—
Agent session termination	—	—
Tamper-evident audit trail	—	—
Sub-50ms latency	—

Built for Production Agents

Zero-Latency Architecture

Evaluation runs in parallel with request parsing. P95 latency under 50ms means agents stay fast while staying safe.

Context-Aware Scoring

Rules consider the full conversation history, not just the current turn. Multi-turn injection attempts are caught at the sequence level.

Granular Policy Engine

Set different enforcement modes per rule, per agent, per environment. Dev agents can run in monitor mode while production agents enforce deny.

Incident Forensics

Every blocked or flagged request preserves the full context window, tool call parameters, and evaluation trace for post-incident analysis.

MCP Server Governance

Inventory, trust-score, and govern Model Context Protocol servers

AI Agent Relationship Graph

Map agent-to-tool-to-identity relationships and blast radius

Secure Your AI Agents at Runtime

19 detection rules. 5 enforcement modes. Sub-50ms latency. Start your 14-day Business trial.