PromptBrake is a hosted LLM API security testing platform that runs 60+ real attack prompts across 12 security checks against your live AI endpoints. It tests for prompt injection, jailbreak overrides, data leaks, unsafe tool behavior, memory exposure, and output bypass attempts. Scans complete in 3-8 minutes and return clear PASS/WARN/FAIL results with evidence and remediation guidance. Built for engineering teams shipping AI features who need a repeatable security baseline without waiting for a full pentest.

• 13 Security Test Categories: Covers prompt injection, indirect injection, jailbreak overrides, data leakage, tool misuse, memory/context exposure, and encoded output bypass attempts across 60+ attack scenarios.
• Fast Scan Turnaround: Most scans finish in 3-8 minutes depending on endpoint response time and test profile.
• Evidence-Backed Results: Every failure shows the triggering prompt, the reason it was flagged, and sanitized request/response payloads so you can reproduce and fix the issue.
• CI/CD Integration: Supports GitHub Actions and GitLab CI with automated scan gating, so every prompt change, model update, or tool modification triggers a security check before release.
• No Security Expertise Required: Clear PASS/WARN/FAIL scoring with step-by-step remediation playbooks lets engineering teams fix issues without a dedicated security team.
• Privacy-First Design: Scan data is never sent to another model. API keys are used in memory during the scan and never stored. Evidence is saved only for failed tests.
• Two Test Profiles: Scout (Lite) runs 6 core checks for quick validation. Pro (Full) runs all 13 categories with 60+ attack scenarios for thorough coverage.

• Quick Setup and Fast Results: Point it at your API endpoint and get actionable findings in minutes, not days or weeks.
• No Security Background Needed: The PASS/WARN/FAIL scoring with evidence logs and remediation guidance makes results accessible to any developer.
• Repeatable Testing After Changes: Re-run the same checks after prompt edits, model swaps, or retrieval changes to confirm fixes and catch regressions.
• CI/CD-Ready Workflow: Pro accounts can automate security scans in the deployment pipeline and enforce release gates on critical failures.
• Focused Scope Reduces Noise: Endpoint-first testing avoids the complexity of full pentests while covering the most common LLM attack vectors.

• Not a Full Application Pentest: PromptBrake focuses on endpoint-level testing only and won't catch vulnerabilities outside the LLM API layer.
• No Runtime Protection: It's a pre-release scanner, not a real-time firewall. You'll still need a separate runtime guard for production traffic.
• Fixed Attack Library: Unlike open-source frameworks such as Promptfoo, you can't customize or extend the attack scenarios to match domain-specific threat models.

• Pre-Launch Security Check: Before releasing an AI-powered feature, run a full scan to validate that your endpoint resists prompt injection, data leaks, and tool abuse. Get a clear security baseline with evidence you can share with stakeholders or customers.
• Post-Model-Change Validation: After swapping from GPT-4 to Claude or upgrading to a new model version, re-run the same 12 security checks to confirm your defenses still hold under the new model's behavior.
• CI/CD Security Gating: Integrate PromptBrake into your GitHub Actions or GitLab CI pipeline so every prompt edit or retrieval change automatically triggers a security scan. Block releases when critical failures are detected.
• Startup Due Diligence: Founders preparing for customer reviews, SOC 2, or enterprise sales can generate security scan reports showing their AI endpoints have been tested against known attack patterns.
• Team Security Baseline Without a Pentest: Small engineering teams without dedicated security staff can establish a repeatable security testing workflow in minutes instead of scheduling and waiting for expensive manual pentests.