Complementary Security

Lakera Guard + Agent Action Firewall

Complete AI agent security requires protecting both the input and the output. Learn how Lakera and Agent Action Firewall work together to secure your agentic AI systems.

Why Input Security Isn't Enough

Prompt injection defense protects your AI from malicious users. But what happens after the AI decides to act? When your agent connects to Jira, Slack, databases, or APIs—who's watching what it actually does?

The AI Agent Security Gap

Lakera Guard
Protects the INPUT
Prompt injection, jailbreaks, toxic content
AI Agent
Makes decisions
LLM reasoning & tool selection
Agent Action Firewall
Protects the OUTPUT
Action policies, approvals, audit trails

Feature Comparison

Different problems require different solutions. Here's how the two platforms compare:

CapabilityLakera GuardAgent Action Firewall
Prompt injection defenseCore feature
Jailbreak preventionCore feature
Content moderationCore feature
Multi-language support (100+)Core feature
Action-Level Security
Policy-based action control (OPA/Rego)Core feature
Human approval workflowsCore feature
Cryptographic audit trailsCore feature
Proof Packs (compliance bundles)Core feature
Usage limits & quotasCore feature
Visual workflow editorCore feature
Both Platforms
PII/Data leak detectionIn promptsIn actions
API-first integrationYesYes
Model-agnosticYesYes

When You Need Both

If your AI agents take real-world actions, you need security at both ends of the pipeline.

🤖

Customer Support Agents

Lakera: Block prompt injections in customer messages
AAF: Require approval before issuing refunds over $500

📝

Document Processing Agents

Lakera: Detect poisoned content in uploaded documents
AAF: Audit trail of all database writes with hash verification

🔧

DevOps Automation Agents

Lakera: Prevent jailbreaks that could expose infrastructure
AAF: Block production deployments, require human approval for destructive ops

💼

Enterprise Workflow Agents

Lakera: Multi-language content safety for global teams
AAF: Policy enforcement on Jira, ServiceNow, Slack actions

The Right Question to Ask

Lakera Guard asks:

“Is this prompt safe?”

  • • Is someone trying to manipulate the AI?
  • • Does this contain harmful content?
  • • Is there hidden instruction injection?

Agent Action Firewall asks:

“Should this action execute?”

  • • Does this violate our security policies?
  • • Does a human need to approve this?
  • • Is there a complete audit trail?

Different Technical Approaches

Lakera: AI-Powered Detection

Uses machine learning trained on millions of attack patterns to probabilistically detect malicious prompts. Learns continuously from their Gandalf platform with 80M+ prompts.

Best for: Evolving threats, content safety, multi-language attacks

AAF: Deterministic Policy Engine

Uses OPA (Open Policy Agent) with Rego policies for binary allow/deny decisions. No probabilistic filtering—100% certainty on every action decision.

Best for: Compliance requirements, audit trails, human oversight

Pricing Transparency

Lakera Guard

Free tier available. Enterprise pricing requires sales contact. Part of Check Point portfolio.

Usage-based pricing model

Agent Action Firewall

$199/month for Pro

Public pricing. Self-serve signup. No sales calls required.

Free tier: 500 actions/month

Complete Your Agent Security Stack

Already using Lakera? Add Agent Action Firewall to protect the other half of your AI pipeline.

No credit card required. 500 actions/month free forever.