Enterprise Security
Production-Grade AI Security
MissingDots implements defense-in-depth security for AI inference pipelines. Every layer is designed to prevent, detect, and respond to threats before they impact your users.
Defense-in-Depth Architecture
LAYER 1
Input Validation Layer
Multi-stage prompt sanitization and injection detection
- Recursive prompt injection detection using adversarial classifiers
- Unicode normalization and homoglyph attack prevention
- Context window manipulation detection
- Instruction hierarchy enforcement via delimiter analysis
LAYER 2
Retrieval Security
Secure context assembly and source verification
- Document provenance tracking with cryptographic hashes
- Access control enforcement at retrieval time
- Cross-tenant data isolation in multi-tenant deployments
- Poisoned document detection via embedding anomaly analysis
LAYER 3
Generation Guardrails
Output filtering and grounding verification
- Real-time PII detection and redaction across 50+ entity types
- Hallucination scoring with source attribution requirements
- Toxic content filtering using ensemble classifiers
- Schema validation for structured output enforcement
LAYER 4
Runtime Protection
Active monitoring and threat response
- Behavioral anomaly detection for jailbreak attempts
- Rate limiting with adaptive throttling per user context
- Session isolation and state management
- Automatic escalation to human review for high-risk queries
Agent Preflight Certification
Before your AI agents go to production, MissingDots runs comprehensive validation across security, reliability, and behavioral dimensions.
Adversarial Robustness
- Prompt injection resistance (direct and indirect)
- Jailbreak attempt handling
- System prompt extraction prevention
- Role confusion attack mitigation
Data Security
- PII leakage testing across response types
- Training data extraction resistance
- Cross-context information bleed detection
- Sensitive pattern recognition accuracy
Behavioral Consistency
- Response determinism under adversarial perturbation
- Refusal consistency for out-of-scope queries
- Graceful degradation under context overflow
- Multi-turn conversation state integrity
Operational Reliability
- Latency distribution under load
- Error rate across edge cases
- Fallback behavior verification
- Recovery from partial context retrieval failures
Sample Preflight Report
{
"agent_id": "support-assistant-v2",
"timestamp": "2026-02-05T10:30:00Z",
"overall_status": "PRODUCTION_READY",
"scores": {
"adversarial_robustness": 0.94,
"data_security": 0.98,
"behavioral_consistency": 0.91,
"operational_reliability": 0.96
},
"tests_passed": 147,
"tests_failed": 0,
"warnings": 3,
"recommendations": [
"Consider increasing refusal threshold for financial advice queries",
"Add explicit guardrail for competitor product comparisons"
]
}Ready to Secure Your AI Pipeline?
Run a free preflight check on your AI agent and get a detailed security assessment report.