AI Firewall

AI firewalls sit in line with AI traffic and enforce content, context, and behavioral policy. They are most often deployed as a runtime control alongside LLMs, copilots, and agent gateways.

AI firewalls typically inspect for:

• Prompt injection: Direct and indirect injection patterns in input streams.
• Sensitive data: PII, secrets, and regulated data crossing trust boundaries.
• Policy violations: Content categories or actions disallowed by enterprise policy.
• Anomalous behavior: Unusual prompt frequencies, sizes, or response patterns.
• Toxicity and abuse: Harmful content in both user input and model output.

Because AI traffic is increasingly bidirectional and includes tool calls, a useful AI firewall must inspect more than prompts and responses. Coverage across retrieval, tool invocation, and agent-to-agent traffic is what separates a true AI firewall from a content filter.

Programs that operate AI firewalls well also tune them continuously against red team output and observed attack telemetry, so policy keeps pace with adversary techniques.

How PointGuard AI Helps

PointGuard's AI Runtime Guardrails act as the AI firewall layer across LLM and agent deployments, and the MCP Security Gateway extends that inspection into every tool the agent reaches. The combination provides AI firewall coverage at every choke point an attacker would otherwise exploit.

Learn More

• OWASP Top 10 for LLM Applications
• NIST AI 100-2 Adversarial ML Taxonomy
• MITRE ATLAS