This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
VulX Watch
Catch security risks hiding in your vibe-coded apps
VulX Watch continuously checks AI-written code for security risks like committed secrets, vulnerable dependencies, fake packages, injection patterns, and SQL/RLS issues. Connect a GitHub repo or MCP to get clear findings with evidence, severity, file locations, and suggested fixes. Built for AI-generated code, VulX never rewrites, runs, or tests your app, it reads, verifies, and surfaces what needs attention inside Claude or Cursor.
VulX Watch offers security for the code your AI writes.
AI can build and ship an entire app in hours. The problem? Most builders don't know what security risks the AI may have introduced or what they should even look for.
VulX Watch continuously reads your AI-written code and surfaces what matters: committed secrets, vulnerable dependencies, fake packages, injection patterns, and SQL/RLS issues.
Why VulX is different:
Not another scanner: no PRs, setup, or manual scans. Connect a repo and VulX keeps watching.
Nothing VulX finds can break your build. A scanner sitting in CI has to stay quiet about anything uncertain, because every false positive stops someone's work. VulX isn't in that path, so it can surface the things a gate would have to suppress and tell you how sure it is instead. A borderline finding costs you ten seconds of reading. That's what the confidence levels are for.
Independent from your AI: the tool that wrote your code shouldn't be the one checking its own work.
Evidence-first: every finding shows what was found, where it is, why it matters, and how confident VulX is.
Built for AI workflows: ask VulX about findings directly from Claude or Cursor via MCP.
AI-readable: VulX keeps security guidance in AGENTS.md so your AI has the right constraints when writing the next change.
No auto-fixes: VulX explains the fix in plain English; your own AI reviews and implements it.
Who it's for:
AI-native developers, indie hackers, startups, and teams building with Cursor, Claude, Lovable, Replit, Bolt, v0, and other AI coding tools.
Use it when:
→ You've shipped an AI-built app and want to know what's hiding in it → You're iterating quickly and don't want security to become a bottleneck → You want ongoing checks without adding another security workflow
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About VulX Watch on Product Hunt
“Catch security risks hiding in your vibe-coded apps”
VulX Watch was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #23 on the daily leaderboard. VulX Watch continuously checks AI-written code for security risks like committed secrets, vulnerable dependencies, fake packages, injection patterns, and SQL/RLS issues. Connect a GitHub repo or MCP to get clear findings with evidence, severity, file locations, and suggested fixes. Built for AI-generated code, VulX never rewrites, runs, or tests your app, it reads, verifies, and surfaces what needs attention inside Claude or Cursor.
VulX Watch was featured in Artificial Intelligence (477.8k followers), Security (2.9k followers) and Vibe coding (660 followers) on Product Hunt. Together, these topics include over 126.1k products, making this a competitive space to launch in.
Who hunted VulX Watch?
VulX Watch was hunted by Rohan Chaubey. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how VulX Watch stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Rohan Chaubey
VulX Watch offers security for the code your AI writes.
AI can build and ship an entire app in hours. The problem? Most builders don't know what security risks the AI may have introduced or what they should even look for.
VulX Watch continuously reads your AI-written code and surfaces what matters: committed secrets, vulnerable dependencies, fake packages, injection patterns, and SQL/RLS issues.
Why VulX is different:
Not another scanner: no PRs, setup, or manual scans. Connect a repo and VulX keeps watching.
Nothing VulX finds can break your build. A scanner sitting in CI has to stay quiet about anything uncertain, because every false positive stops someone's work. VulX isn't in that path, so it can surface the things a gate would have to suppress and tell you how sure it is instead. A borderline finding costs you ten seconds of reading. That's what the confidence levels are for.
Independent from your AI: the tool that wrote your code shouldn't be the one checking its own work.
Evidence-first: every finding shows what was found, where it is, why it matters, and how confident VulX is.
Built for AI workflows: ask VulX about findings directly from Claude or Cursor via MCP.
AI-readable: VulX keeps security guidance in AGENTS.md so your AI has the right constraints when writing the next change.
No auto-fixes: VulX explains the fix in plain English; your own AI reviews and implements it.
Who it's for:
AI-native developers, indie hackers, startups, and teams building with Cursor, Claude, Lovable, Replit, Bolt, v0, and other AI coding tools.
Use it when:
→ You've shipped an AI-built app and want to know what's hiding in it
→ You're iterating quickly and don't want security to become a bottleneck
→ You want ongoing checks without adding another security workflow
Free while we build it.
Connect a GitHub repo: https://app.vulx.ai/signup
Or add VulX to Claude/Cursor via MCP: https://mcp.vulx.ai/mcp
Tell us where a finding doesn't land. That's exactly what we want to improve.