close

AI Guardrails & Prompt Firewall for LLM Traffic

Inspect every prompt and response. Block injection, jailbreaks, data leaks at inference time.

Schedule a Demo
prompt firewall hero
prompt-firewall-logos

How The Prompt Firewall Works

A transparent proxy that inspects every prompt and response against your configured policies before allowing them through.

How The Prompt Firewall Works

Traffic Controller

The transparent proxy entry point. Users never talk directly to the LLM — all traffic routes through AccuKnox first.

IN

User prompt → scan against policies

OUT

LLM response → validate before delivery

ACT

Block · Sanitize · Monitor

Policy Governance

Evaluates every prompt and response against your configured policies. Customizable per application.

IN

14 built-in policy types

IN

Custom regex + domain-specific rules

ACT

Global or per-app policy scope

Audit & Compliance

Every request and response is recorded for compliance, investigation, and forensic analysis.

LOG

Full conversation history

LOG

Per-policy risk scores

LOG

Block/monitor/pass status + threshold

See The Firewall In Action

From policy configuration to violation forensics — everything in one dashboard.

  • AI-Security Dashboard

    Query volumes, violations, and active policies at a glance.

  • Policy Configuration

    Add and customize local policies per application.

  • Applied Policies

    View all active policies enforcing on an application.

  • Violation Analysis

    Breakdown by policy type with severity and action taken.

AI-Security Dashboard
Policy Configuration
Applied Policies
Violation Analysis

One Firewall, Four Ways to Deploy (Browser · Gateway/Proxy · SDK · Cloud API Gateway)

AI-prompt-guardrail
ctem

AccuKnox Stateful Prompt Firewall and Why Per Prompt Inspection Fails Against Multi Turn Attacks

Multi turn attacks reach 96.2% success against frontier AI models. A firewall that scores messages in isolation never sees the session. Here is what stateful inspection changes.

Read Blog

Integrate In Minutes

Wrap your existing LLM calls with prompt and response scanning. One import, two function calls.

  • Session linking for full audit trails
  • BLOCK, MONITOR, PASS, or SANITIZE responses
  • Per-policy risk scores for debugging
integrate-in-minutes

Every Model. Every Platform.

Cloud, managed, or self-hosted — the Prompt Firewall works with your stack.

CLOUD LLM PROVIDERS

Cloud-llm-providers-logos

MANAGED AI SERVICES

managed-ai-services-logos

ON-PREMISE MODELS

ON-PREMISE MODELS

ENTERPRISE

enterprise-logos

Your AI stack breaks in eight places.

Eight fronts covered. Zero blind spots.

prompt firewall-platfrom-card
  • No inventory of models, agents, datasets, pipelines
  • Shadow AI deploys where nobody is looking
  • Open endpoints on Bedrock & Azure OpenAI
  • Live inventory, agentless, one dashboard
  • Shadow AI discovery for notebooks & MCP servers
  • Auto-remediates exposures the instant they appear
posture-management-logos
aidr-platfrom-card
  • Overnight deploys with nobody watching
  • Chained attacks look harmless step by step
  • Scattered incidents across disconnected tools
  • Continuous ingest of CloudTrail, Azure, GCP logs
  • Full attack path rebuilt from weak signals
  • Auto-routes to Jira, ServiceNow, Slack, PagerDuty
detect-and-respond-logos
agentic ai security-platfrom-card
  • Hijacked agents touch files & networks off-limits
  • Tool abuse and rogue API calls
  • Poisoned memory corrupts reasoning over time
  • Runtime sandbox via eBPF & LSM, no code changes
  • Least privilege tool access, blocked before it runs
  • Catches poisoning before a decision changes
agentic-security-logos
AI-model-data-security-platform-card
AI Model & Dataset Security

AI Model & Dataset Security

blue-arrow-right
  • Hidden malware in Pickle, HDF5, ONNX files
  • Poisoned models from Hugging Face & GitHub
  • Unscanned PII/PHI buried in training data
  • Scans 5 formats for tampering & deserialization
  • Blocks poisoned models before they deploy
  • Maps findings to OWASP LLM Top 10 & MITRE ATLAS
model-and-dataset-logos
ai red teaming-platfrom-card
  • Yearly pen tests can't match weekly updates
  • Generic tools miss jailbreaks & encoding tricks
  • Silent regressions after every fine-tune
  • 150+ probes fire on every model change
  • Real attacker TTPs, mapped to OWASP & MITRE
  • Custom probe packs for domain-specific risk
red-teaming-logos
AI-identity-security-platform-card
AI Identity Security

AI Identity Security

blue-arrow-right
  • Shared API keys across every agent
  • No per-agent permissions or scoping
  • Impersonation of trusted agents
  • SPIFFE identity unique to every agent
  • Per-agent permissions, enforced automatically
  • Blocks spoofing with cryptographic attestation
identity-security-logos
prompt firewall-platfrom-card
  • Slow jailbreaks spread across 5-15 messages
  • Leaked secrets: PII, PHI, credentials in prompts
  • Fragmented setup per channel
  • Stateful engine tracks the whole conversation
  • Real-time masking of PII, PHI & secrets
  • One policy across gateway, SDK, browser, Copilot
prompt-firewall-logos
Image
  • Weeks of mapping to OWASP, NIST, EU AI Act by hand
  • Proof, not slides is what auditors want
  • 12+ frameworks to satisfy at once
  • Auto-tags findings to 12+ frameworks
  • Per-query trail auditors can actually verify
  • On-demand reports, SaaS or air-gapped
compliance-and-grc-logos

Set Up In Five Steps

From onboarding your application to monitoring violations in real time.

1

Add Your Application

Navigate to AI/ML → Applications → Add Application. Name and tag your AI app.

2

Configure Policies

Apply global policies for org-wide rules or local policies per application. Choose Block, Monitor, or Allow.

3

Set Policy Scope

Global policies apply to all apps. Local policies let you customize — ban code in support bots but allow it in dev assistants.

4

Monitor the Dashboard

Real-time visibility into total queries, policy violations, and active enforcement.

5

Investigate & Audit

Click any violation for full conversation history, per-policy risk scores, and block/monitor status.

5-steps-prompt-firewall

Prompt Firewall + Red Teaming

Red teaming finds the gaps. The Prompt Firewall enforces the rules to close them. Both work together.

CAPABILITY RED TEAMING PROMPT FIREWALL
When crossPre-deployment and scheduled scans tickRuntime — every live request
What it does crossSimulates adversarial attacks against models tickEnforces policies on real user traffic
Action crossGenerate findings and risk reports tickBlock, sanitize, or monitor in real-time
Purpose crossDiscover vulnerabilities before attackers tickPrevent attacks from succeeding
Coverage crossPoint-in-time assessment tickContinuous, always-on protection
PII protection crossIdentifies potential exposure risks tickMasks PII in real-time before LLM processes it
Prompt injection defense crossTests known injection patterns tickML-based detection on every request
Compliance crossAudit reports tickContinuous audit trail with full conversation logging

Ready For A Personalized Security Assessment?

“Choosing AccuKnox was driven by opensource KubeArmor’s novel use of eBPF and LSM technologies, delivering runtime security”

idt

Golan Ben-Oni

Chief Information Officer

“At Prudent, we advocate for a comprehensive end-to-end methodology in application and cloud security. AccuKnox excelled in all areas in our in depth evaluation.”

prudent

Manoj Kern

CIO

“Tible is committed to delivering comprehensive security, compliance, and governance for all of its stakeholders.”

tible

Merijn Boom

Managing Director

Prompt Firewall FAQs

The AccuKnox Prompt Firewall is a transparent proxy that sits between users and the LLM. Every prompt and response routes through AccuKnox first, gets scanned against configured policies, and is then blocked, sanitized, monitored, or passed. Users never talk directly to the model. AccuKnox is one of the few platforms enforcing this inline on live traffic in both directions.
It uses ML based detection to catch instruction overrides, roleplay exploits, and jailbreak attempts on every request. A prompt like "Ignore all previous instructions" is blocked before it reaches the model. Detection runs continuously on live traffic rather than as a one time scan, so new attack variants get caught at runtime.
AccuKnox enforces 14 built in policy types covering prompt injection, toxicity, secrets and API key leakage, PII and PHI exposure, banned topics, competitor mentions, gibberish, token limit abuse, relevance drift, and unapproved languages or code. Custom regex and domain specific rules layer on top. This breadth of runtime coverage sets the AccuKnox firewall apart from single purpose filters.
Yes. The Anonymize policy detects and masks names, SSNs, emails, credit cards, and medical records in real time. An input like "My SSN is 123-45-6789" becomes "My SSN is [REDACTED]" before the LLM ever processes it. The Regex policy handles any custom format such as internal IDs or account numbers.
Input policies inspect prompts before they reach the LLM. Output policies inspect responses before they reach the user. Both run on every interaction. This two way enforcement blocks a malicious prompt going in and catches sensitive data or policy violations in the model's reply coming back out.
Model level filters are baked into the LLM and cannot be tuned per application. The AccuKnox Prompt Firewall enforces custom policies outside the model, in both directions, with a full audit trail the model never provides. Enforcement can differ for a banking bot versus a developer assistant. That per application control is core to why teams pick AccuKnox over native filters.
Four actions. BLOCK stops the request entirely, SANITIZE masks the sensitive content and lets the rest through, MONITOR logs the event without interrupting flow, and PASS allows it. Each policy returns a per policy risk score, so thresholds are configurable and every action is traceable.
Yes. AccuKnox supports cloud, managed, and self hosted deployments, including on premise and air gapped environments. It works with cloud LLM providers, managed AI services, on premise open models, and enterprise stacks. This deployment flexibility makes AccuKnox a strong fit for federal, defense, and regulated teams that cannot send traffic to a vendor cloud.
Global policies apply org wide across every application. Local policies apply to a single app for customized enforcement. Code can be banned in a customer support bot while allowed in a developer assistant, all from the same dashboard.
It works across cloud LLM providers, managed AI services, on premise open source models, and enterprise platforms. Because the AccuKnox firewall operates as a transparent proxy wrapping existing LLM calls, it stays model agnostic and platform agnostic. Traffic points through it without swapping out the model.
Minutes. One package installs with pip install accuknox-llm-defense, then existing LLM calls get wrapped with two function calls for prompt and response scanning. Session linking ties requests together for full audit trails, and per policy risk scores help with debugging during setup.
Red teaming finds gaps. The Prompt Firewall closes them. Red teaming runs pre deployment and on scheduled scans to simulate attacks and produce risk reports. The firewall enforces policies on every live request at runtime, blocking and sanitizing in real time. AccuKnox ships both together, so vulnerabilities get discovered and prevented from the same platform.
Yes. Every request and response is recorded with full conversation history, per policy risk scores, and block, monitor, or pass status. This continuous audit trail supports compliance, investigation, and forensic analysis, mapping directly to evidence requirements under SOC2, HIPAA, and NIST. AccuKnox gives compliance teams a defensible record of every AI interaction.
It combines a RoBERTa classifier with the Perspective API to catch hate speech, threats, and explicit content. Racial slurs and death threats get blocked. A separate Sentiment policy flags aggressive or hostile inputs against configurable thresholds, allowing tone monitoring without hard blocking every heated message.
Five steps. Add the application under AI/ML, configure policies and choose Block, Monitor, or Allow, then set policy scope to global or local. The dashboard shows queries and violations in real time, and clicking any violation reveals full conversation history and per policy risk scores. Setup runs entirely from the AccuKnox dashboard.
× Image