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Ship AI features without shipping vulnerabilities. PromptBrake is a pre-release security testing platform for LLM-powered APIs โ point it at your endpoint and run repeatable scans for prompt injection, data leaks, unsafe tool use, and output bypasses, mapped to the OWASP LLM Top 10.
Each finding includes evidence logs and remediation guidance, so you know exactly what to fix. Compare runs to catch regressions, and plug the same checks into CI to gate risky releases.
Works with OpenAI, Claude, Gemini, and custom LLM-backed endpoints. Also includes free tools such as an LLM security checklist, a prompt injection payload generator, and an OWASP LLM test case mapper to help teams validate their setup early.
Python Fabric
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PromptBrake's answer:
Choose PromptBrake when you want a security check, not a security project. Open-source tools like Promptfoo and Garak are powerful, but expect you to design your own test suite, write probes, and interpret raw output โ that's a week of setup before your first useful result. Manual AI pentests deliver depth but cost $5,000โ$20,000 per audit and run at best quarterly. PromptBrake fits the gap: an opinionated, repeatable suite you can run before every release, with results your engineers can act on without a security background. If your team ships AI features faster than a security calendar can keep up, that's the workflow PromptBrake is built for.
PromptBrake's answer:
Backend: Python with Flask, SQLAlchemy, Flask-Migrate (Alembic), and Gunicorn. Database: SQLite. Auth and identity: Firebase Authentication. Payments: Stripe. Frontend: server-rendered Jinja2 templates with vanilla JavaScript and CSS โ no SPA framework. Infrastructure: AWS (EC2), with Cloudflare in front for WAF and CDN.
PromptBrake's answer:
PromptBrake is the only LLM API security scanner built as a product, not a framework. While open-source tools like Promptfoo and Garak give you a flexible harness for building your own red-team workflow, PromptBrake gives you an opinionated 12-test suite (60+ real-world attack scenarios, OWASP LLM Top 10-aligned) that runs against your endpoint with zero configuration. Every finding comes with PASS/WARN/FAIL verdicts, evidence logs, and concrete remediation steps โ so engineers know exactly what broke and how to fix it. Compare any two runs to track regressions and fixes between releases, and drop the same scans into CI as a release gate. Works with OpenAI, Claude, Gemini, and custom LLM-backed endpoints. No security team, no harness setup, no agent install โ point it at your endpoint and ship with confidence.
PromptBrake's answer:
Engineering teams shipping LLM-powered APIs who are accountable for security but don't have a dedicated security team. That includes startup engineers wiring an AI feature into production, platform teams adding LLM endpoints to existing apps, and solo builders who need a credible security check before launch. The common thread: they own an AI endpoint, they're shipping fast, and they need a repeatable answer to "is this safe to release?" without hiring a pentester or building a red-team harness from scratch.
PromptBrake's answer:
If you've shipped an LLM-powered API, you've probably had this moment: someone asks, "Is it secure?" and you don't know where to start. OWASP publishes a Top 10 for LLMs. Headlines warn about prompt injection, jailbreaks, data leaks, and tool abuse. Blog posts disagree on what to test and how to test it. Open-source frameworks hand you a toolkit and assume you already know what to do with it. Manual pentests cost probably $5,000 to $20,000 and take weeks to schedule. Most engineers shipping AI features aren't security researchers โ they need a credible answer before the next release goes out. That's the gap PromptBrake was built for. One opinionated suite. Twelve tests covering what actually matters. PASS/WARN/FAIL results with evidence and remediation in plain language. Point it at your endpoint, see what's broken, fix it, ship. Security testing shouldn't require becoming a security expert first.
Based on our record, Python Fabric seems to be more popular. It has been mentiond 2 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Thanks, will take a look at that curl thing. We are still using this and been working for us for ~15 years (python 2, ported to python 3) and this is just an example of how to take https://fabfile.org to the extreme but still is not the best way to do it. We only ~50 servers so it is not a massive fleet. The convenience of typing `fab ` to do things under control is still better than nothing :). - Source: Hacker News / over 1 year ago
I've used Rake and Fabric for somewhat similar (but less ambitious) stuff in the past and I'm thinking that Fabric might be a pretty good fit for this task as well, but I'd still like your input. Are there other tools I should look into? I've heard goodthings about Puppet but just looking at their site (it contains the word Enterprise ) gives me the feeling that it might be overkill for a one man operation. Source: about 4 years ago
Android Studio - Android development environment based on IntelliJ IDEA
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Firebase - Firebase is a cloud service designed to power real-time, collaborative applications for mobile and web.
ZeroThreat.ai - Fastest AI-Powered AppSec & Automated Pentesting Platform
Xcode - Xcode is Appleโs powerful integrated development environment for creating great apps for Mac, iPhone, and iPad. Xcode 4 includes the Xcode IDE, instruments, iOS Simulator, and the latest Mac OS X and iOS SDKs.
Aikido Security - Secure your code, cloud, and runtime in one central system. Find and fix vulnerabilities fast and automatically.