Every request to your AI app flows through the AIRS AI Gateway — a transparent security layer that inspects, classifies, and enforces policies on both prompts and responses in real time.
Attackers embed adversarial instructions inside user input to hijack the AI model's behavior. AIRS detects and blocks these attacks in real time — before they reach the LLM.
Click a sample prompt or type your own, then hit Send.
Send a prompt to see analysis.
Users attempt to trick models into ignoring safety guidelines using roleplay, hypotheticals, or encoding tricks. AIRS uses behavioral pattern matching to catch these attempts.
Simulate common jailbreak techniques:
| Detection Category | Status | Sensitivity | Action |
|---|---|---|---|
| DAN / Jailbreak Prompts | Enabled | Strict | Block + Alert |
| Roleplay Overrides | Enabled | Strict | Block + Alert |
| Hypothetical Framing | Enabled | Moderate | Warn + Log |
| Encoding Obfuscation | Enabled | Strict | Block + Alert |
| Toxic / Harmful Content | Enabled | Strict | Block + Alert |
AIRS scans both incoming prompts and outgoing responses for sensitive data — SSNs, credit cards, emails, API keys, and more — then redacts or blocks before data leaves your environment.
Paste text with sensitive data and watch it get redacted:
Configure fine-grained security policies for your AI API endpoints — rate limiting, model access control, topic restrictions, and response filtering — all without changing application code.
Build a request and see how AIRS guardrails respond:
# Point your existing OpenAI client at the AIRS Gateway
client = openai.OpenAI(
api_key="your-openai-api-key",
base_url="https://airs-gateway.prismacloud.io/v1",
default_headers={
"X-AIRS-Profile": "production-strict",
"X-AIRS-App-ID": "my-ai-app-001",
}
)
# All requests automatically protected — no code changes needed
response = client.chat.completions.create(
model="gpt-4",
messages=[{"role": "user", "content": user_input}]
)
# AIRS raises AIRSBlockedException for blocked requests
from airs_sdk import AIRSBlockedException
try:
result = client.chat.completions.create(...)
except AIRSBlockedException as e:
print(f"Blocked: {e.reason} | Threat: {e.threat_category}")
Get full visibility into AI traffic patterns, threat detections, and policy enforcement — all in one unified security dashboard.
"event_id": "airs-evt-8f3a2c",
"timestamp": "2026-10-12T09:14:22Z",
"app_id": "my-ai-app-001",
"action": "BLOCKED",
"threat_category": "prompt_injection",
"confidence": 0.97,
"user_id": "usr_anon_4821",
"prompt_hash": "sha256:a3f9...",
"policy_profile": "production-strict"
}
Demo Complete!
You've seen how Prisma AIRS secures AI applications at every layer — from the prompt to the response — without changing your existing code.