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See Wallarm's API Protection In Action
Talk to an Expert
Solution · Enforce
Enforce.
Detection is fine. Stopping the attack is better.
A jailbroken agent discounts tickets before anyone notices. An over-permissioned role accesses data it should not. A compromised session is detected after the fact, and containment means restarting pods, rotating credentials, and explaining downtime. Detection without enforcement is alerts in a queue. Wallarm enforces in real time. Block at the connection. Revoke sessions by user identity or trace ID. No pod restart, no deploy cycle.
Inline blocking
Kernel-level revoke
Decade in production
The Problem
Containment shouldn't
require a redeploy.
When the alert fires, you have minutes, not a release cycle.
One-Request Exploits
97%
Of API vulnerabilities can be exploited with a single request. By the time the alert fires, the attack is already complete.
Source: Wallarm, API ThreatStats Report 2025
AI Tools at Critical Risk
72%
Of corporate AI tools in active use are at high or critical risk. Detection without inline enforcement is alerts in a queue while the AI keeps running.
Source: Cyberhaven, 2025 AI Adoption and Risk Report
API Attack Vector · 2025
#1
APIs were the leading attack vector in 2025. Agentic AI multiplies the attack surface every quarter.
Source: Wallarm, API ThreatStats Report 2025
Outcomes
What changes with Wallarm.
Stop attacks at the data plane, not at the alert queue
Malicious requests are blocked inline, before they reach the application. Injections, account takeovers, business logic abuse, and prompt injection get dropped in real time. The security team gets a record. The application gets to keep running.
Revoke a session in seconds, by user
When a session is compromised, the operator revokes it by user identity or trace ID from the dashboard. The connection drops at the kernel within seconds. No pod restart. No credential rotation. No "we'll get to it in the next deploy."
Enforce policy on AI traffic, the same way you do for APIs
The security team already has policy, audit, and incident response for API traffic. Wallarm extends the same model to AI: provider allowlists per namespace, pattern-match blocking on outbound LLM calls, guardrails scoped to agents, assets, and environments.
Custom rules without forking the platform
Security engineers author detection rules and enforcement policies in Common Expression Language. Block the specific pattern you saw last week. Suppress the finding you've decided is accepted risk. Every action lands in an audit log.
Capabilities
How Wallarm does it.
1
Inline blocking
Real-time inline blocking
Wallarm inspects API and AI traffic and blocks malicious requests inline. Injections, account takeovers, business logic abuse, prompt injection, AI logic abuse, and API abuse stop at the request. No application changes required. Backed by more than a decade of production deployments at scale.
API Security →2
Kernel revoke
Kernel-level session revocation
When an operator kills a session by user identity or trace ID, in-flight calls drop at the kernel within seconds. No pod restart. No credential rotation. No deploy cycle. The connection ends; the application keeps running.
AI Hypervisor →
3
LLM enforcement
Inline LLM call enforcement
A transparent in-cluster proxy terminates outbound TLS for known LLM hosts, evaluates the request against pattern-match block rules, returns a 403 on match, and records the block event. Provider allowlists per namespace become enforceable rather than aspirational.
AI Hypervisor →
4
Guardrails
Guardrails and enforcement pipelines
Condition-based policy rules with severity and scope (agents, assets, environments) route events to Slack, Splunk HEC, Elastic Security, Sumo Logic, PagerDuty, Jira, or a custom webhook. The same governance model the team already uses for application traffic.
AI Hypervisor →5
Logic abuse
Business logic and AI abuse detection
Wallarm correlates requests into sessions and identifies workflow manipulation, scraping, credential stuffing, prompt injection, and AI logic abuse from real production traffic, not from scan noise. Attacks that "look valid" still get caught.
API Security →6
Spec enforcement
Specification enforcement
Where API or MCP specifications exist, Wallarm enforces them as a positive security model. Only known-good traffic passes. Useful as a default for AI infrastructure where the schema is well-defined and the threat surface is moving fast.
API Security →
The AI Control Loop
Discover. Observe. Enforce. Govern.
Not four separate products. One platform, one continuous loop where each step feeds the next automatically.
Enforce
You Are Here
Stop AI behavior that violates policy. Block at the connection level.
GET A DEMO
Ready to see what
your AI is actually doing?
"I would absolutely recommend Wallarm, in a heartbeat. They do what they say on the tin. Meaning what they say they can do, they really do."
Rob Davies · VP of Engineering & Lead Architect, Revenera
Inline enforcement runs inside your environment. No traffic leaves your boundary.