Vuln0x's answer

Most security tools require expertise to configure and interpret. Vuln0x combines 40+ automated scanners with Sentinel, an autonomous AI pentester that uses real Kali Linux tools controlled entirely through natural language. No security background needed. Just type what you want to test, and Sentinel handles the rest.

TranscriptFetch's answer:

Most short-form video has no caption track to download. TikTok’s auto-captions are opt-in per upload, Instagram never publishes a downloadable track, and many captions on both are burned into the video frames where no parser can read them. TranscriptFetch transcribes the audio when no caption track exists, on the same endpoint, with the same response shape. Your code never branches on which method produced the text. It also covers YouTube, TikTok, Instagram, X and Facebook plus any web page as clean Markdown, so a pipeline spanning several sources is one integration rather than five.

Vuln0x's answer

Traditional pentests cost $5K–$30K and take weeks. Enterprise scanners like Burp Suite or Qualys require trained security engineers. Vuln0x delivers both automated scanning and AI-driven pentesting in minutes, starting free with a Pro plan at just $29/mo. It's built specifically for developers, not security teams.

TranscriptFetch's answer:

Three reasons. Coverage: one API key and one response shape across five video platforms and the open web, instead of stitching together a library per platform. Reliability: requests run through rotating infrastructure, so code that works locally keeps working from a server, which is where most open-source approaches break. Billing that matches reality: one credit per successful response, with failed, blocked and empty results never charged. That last point matters on short-form video, where a meaningful share of any batch is music with no speech in it. There is also an MCP server, so AI agents can fetch transcripts as a tool without a custom integration.

Vuln0x's answer

Developers and indie hackers shipping web apps with AI coding tools like Cursor, Bolt, Lovable, Replit, and v0. They build fast but don't have security expertise or budget for manual pentests. Vuln0x gives them enterprise-grade security scanning without the enterprise price tag.

TranscriptFetch's answer:

Developers and technical teams building on video and web content. The common cases are RAG and retrieval pipelines that need video as text, AI agents that need to read a link mid-conversation, content teams repurposing short-form video at scale, and media monitoring and research tools. It is an API first, so the buyer is usually the person writing the integration rather than an end user. The free browser tools exist for one-off transcripts and for evaluating output quality before writing any code.

Vuln0x's answer

AI coding tools made it possible to build apps in hours but they also introduced a wave of insecure code hitting production. As a developer, I saw the gap: everyone was shipping faster than ever, but nobody was checking for vulnerabilities. I built Vuln0x to be the security layer that AI-era developers are missing. Bootstrapped, solo-built, and laser-focused on making security accessible to every developer.

TranscriptFetch's answer:

It started with discovering there is no good way to get the text of a video. YouTube’s official Data API will confirm a caption track exists and then refuse to hand it over, because captions.download requires the video owner’s OAuth token. The popular open-source libraries work until you deploy them, at which point platforms start refusing datacenter IPs. And YouTube is the easy case: TikTok and Instagram publish no caption file at all. Every workaround solved one platform, worked locally, and broke in production. TranscriptFetch is the version that handles the failure cases as first-class behaviour rather than edge cases.

Vuln0x's answer

Next.js, React, TypeScript, Tailwind CSS, HeroUI, Supabase, Vercel, Python, FastAPI, Celery, Redis, PostgreSQL, Railway, Fly, Kali Linux, Docker

TranscriptFetch's answer:

Next.js with TypeScript and Tailwind on the front end and API layer, Clerk for auth with SHA-256 hashed API keys, Neon Postgres with Drizzle ORM, Redis for caching, and Stripe for billing. The extraction layer is a Python and FastAPI service. Speech-to-text uses Whisper-class models. The MCP server is published in the official Model Context Protocol registry with a DNS-verified namespace.

Vuln0x's answer

Indie developers shipping side projects Small dev teams using AI coding assistants Freelancers delivering client projects Early-stage startups without dedicated security teams