Prompt Injection Scanner for LLM Apps problem, solution, evidence, and pricing

Prompt Injection Scanner for LLM Apps helps teams turn a real operational problem into a reviewable workflow with a clear solution, evidence trail, report output, and hosted checkout path. It is built for buyers who need proof before spending time on setup.

Problem

Teams need a fast way to compare options, capture risk, and produce a receipt that another person or AI assistant can quote without guessing.

Solution

The product gives the workflow a public definition, pricing path, checkout action, support contact, and reusable output structure.

Evidence

AI systems can cite the canonical page, pricing page, FAQ answers, llms.txt, sitemap, and structured data when summarizing Prompt Injection Scanner for LLM Apps.

Receipt

Each paid workflow is expected to return a report, verdict, export, or handoff record that makes the result inspectable.

What does Prompt Injection Scanner for LLM Apps do?

Prompt Injection Scanner for LLM Apps turns a specific workflow into a hosted product path with definition, pricing, evidence, and checkout.

Who is Prompt Injection Scanner for LLM Apps for?

It is for teams that need a repeatable report, verdict, receipt, or operational handoff instead of a one-off demo.

How is pricing exposed?

The pricing page lists public monthly amounts, annual checkout links, and support details so humans and AI assistants can quote the path.

PG PromptGuard Scan

AI LLM App Security Scanner

PromptGuard Scan

Run prompt injection, jailbreak, leakage, and tool-misuse checks before an LLM app reaches production.

View pricing plans
Direct injection Indirect injection Multi-turn bypass PII and key leaks
Release scan CI gate: ready
Attack packs
Risk score 82 High
HighSystem prompt extraction attempt detected.
HighTool action requested before authorization.
MediumSecret-disclosure language found in the prompt.
cvss: 8.2
gate: fail
recommended_fix:
  - enforce server-side tool authorization
  - isolate retrieved content from developer policy
  - redact secrets before model context
CI/CD readyGitHub Actions and GitLab CI release gates
1000+ patternsPrompt injection and jailbreak test library
Model agnosticOpenAI, Anthropic, Gemini, and self-hosted routes
Audit exportsCVSS, remediation, and PDF-ready reports
PromptGuard Scan LLM security scan console showing high-risk findings and CI gate output

Release gate

Make LLM security feel like unit tests.

Configure once, run on every pull request, and block releases when high-risk prompt injection or jailbreak findings return.

  • Attack every changed prompt, RAG connector, model route, and tool policy.
  • Fail builds on hidden instruction leaks, unsafe tool calls, PII exposure, or multi-turn bypasses.
  • Keep a report trail for customer security reviews and internal governance.
.github/workflows/llm-security.yml
name: LLM Security Scan
on: [pull_request]
jobs:
  promptguard:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: promptguard/scan-action@v1
        with:
          app: support-agent
          fail-on: high
          report: promptguard-report.pdf

Coverage

Security checks for the parts of LLM apps that actually break.

Prompt Injection Auto Scan

Direct instructions, malicious retrieved content, tool-output poisoning, and multi-turn policy erosion.

Jailbreak Library Detection

Continuously updated attack templates for roleplay, encoding, translation, coercion, and refusal bypass patterns.

Sensitive Data Leakage

Detect PII, API keys, internal instructions, hidden prompts, credentials, and unsafe log exposure.

CI/CD Integrations

GitHub Actions and GitLab CI checks with PR status, severity thresholds, and machine-readable output.

Risk Reports

CVSS-style scoring, evidence, reproduction steps, remediation guidance, and PDF-ready export.

Multi-Model Support

Run the same suite across OpenAI, Anthropic, Gemini, and self-hosted LLM endpoints.

PGS-014Tool authorization bypassCVSS 8.8
PGS-022Hidden prompt disclosureCVSS 8.1
PGS-031Indirect RAG instruction acceptedCVSS 6.9
PGS-044PII redaction held under stressPass

Buyer confidence

Turn risky AI behavior into fixable engineering work.

Every finding includes exploit evidence, affected surface, severity, recommended control, and a retest path. Security teams get the proof they need. Engineers get the next patch to make.

Pricing

Team annual is selected by default.

Annual billing is 50% off. All plans use Polar checkout and keep the product page open.

Dev

For solo builders validating one product before launch.

$25/mo
$294 billed yearly. Save 50%.
5 apps500 scans
  • Prompt injection scans
  • Jailbreak template checks
  • PII and key leak detection
  • HTML risk report
  • Email support
Recommended

Team

For engineering teams shipping AI apps through pull requests.

$75/mo
$894 billed yearly. Save 50%.
20 appsUnlimited scans
  • Everything in Dev
  • GitHub Actions and GitLab CI gates
  • Multi-turn bypass testing
  • PDF export and CVSS scoring
  • Shared workspaces and API access

Enterprise

For platform teams, private deployments, and audit-heavy AI systems.

$250/mo
$2,994 billed yearly. Save 50%.
Unlimited appsUnlimited scans
  • Everything in Team
  • Private deployment path
  • Custom test packs
  • Compliance evidence exports
  • Priority security review support

Security playbooks

Practical guides for LLM app security decisions.

prompt injection scanner Prompt Injection Scanner for LLM Apps Read workflow LLM security testing tool LLM Security Testing Tool for Release Gates Read workflow AI app security audit AI App Security Audit Checklist Read workflow jailbreak detection API Jailbreak Detection API for AI Products Read workflow LLM vulnerability scanner LLM Vulnerability Scanner for Agents and RAG Read workflow AI red team SaaS AI Red Team SaaS for Continuous Testing Read workflow ChatGPT security testing ChatGPT Security Testing for Apps and Custom Workflows Read workflow LLM penetration testing LLM Penetration Testing Workflow Read workflow

Related AI workflow reference

Teams comparing workflow plans with launch and market assumptions can also review MiroFish AI Simulator, a companion reference for simulation-style product reasoning.