AI Security
Akamai Firewall for AI
Traditional WAFs and API gateways weren't designed for AI traffic. The attack surface is different: threats are embedded in natural language, behavior is harder to baseline, and a single malicious prompt can cause far more damage than a malformed HTTP request. Akamai Firewall for AI addresses this with a purpose-built behavioral analysis layer that integrates directly with Zuplo.
Where Firewall for AI fits in the stack
Zuplo's three AI-focused products each address a different layer of the AI stack. Firewall for AI runs alongside all three — mirroring traffic passively for behavioral analysis without adding latency.
Controls who can call your AI APIs
Authentication, rate limiting, and routing at the API layer. AI agents are treated as first-class API consumers — subject to the same policies as human callers, with per-consumer token budgets and request limits.
Firewall for AI mirrors traffic here to analyze prompts sent by AI agents.
Controls what your AI workloads spend
Token-based rate limiting, model routing, and semantic caching across LLM providers. Prevents runaway spend from misbehaving agents and reduces cost through intelligent caching.
Firewall for AI mirrors both requests and LLM responses to detect prompt injection and data exfiltration.
Controls what AI agents can do
RBAC, centralized registry, and audit logs for MCP servers. Governs which AI agents can invoke which tools across the organization.
Firewall for AI can analyze tool calls routed through MCP Gateway for anomalous behavior.
How the integration works
AI request arrives at Zuplo
Auth and rate limiting applied first — Firewall for AI does not sit in the request path.
Request mirrored to Akamai Firewall for AI
A copy of the request is sent asynchronously. Zero latency added to the response.
Behavioral analysis runs in Akamai
Models trained on AI attack patterns analyze the prompt for injection, jailbreaks, and anomalous patterns.
Blocklist updates pushed to Zuplo
Identified threats are pushed back as blocklist updates. Enforcement applies immediately — no manual intervention.
LLM response mirrored on the way back
Response content is also analyzed for data exfiltration before delivery to the caller.
Closed-loop enforcement: Akamai detects the threat. Zuplo enforces the block. No manual handoff — the two products operate as a single system.
What it detects
Prompt injection
Malicious instructions embedded in user input designed to override system prompts or hijack model behavior.
Jailbreaks
Inputs engineered to bypass content policies, safety constraints, or role restrictions set on the LLM.
Data exfiltration
LLM responses that contain sensitive data — PII, credentials, confidential content — being returned to an unauthorized caller.
Anomalous agent behavior
Unusual call patterns from AI agents that deviate from expected usage — high-frequency probing, systematic enumeration, or privilege escalation attempts.
Firewall for AI complements — not replaces — Zuplo's API-layer controls. Rate limiting, authentication, and token budgets in the gateway block volumetric and access-control issues. Firewall for AI adds behavioral analysis for threats that only become visible in the content of requests and responses.