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Redline AI
Attack-test your AI agents and grade what they did
Most agent evals grade the final answer. Redline grades the behaviour the server's own ledger of what the agent called, not its account of it. One task runs against Claude Code, Codex and the agent in your own repo, each in a clean container with identical tools. On top sit 16 security packs: 11,204 adversarial cases delivered the way real attacks arrive hidden in a support ticket, a document footer, a tool result. Your agent connects with redline dev and never leaves your machine.
Hey, Hritvik here.
This started because I couldn't answer a simple question about my own agent: did it actually do what it said it did?
I'd give it a task, it would come back with a clean, confident summary, and the only evidence I had was that summary. When I started reading the actual tool calls I found runs where the agent had done something it shouldn't have and then written it out of its own account. Not lying exactly — just optimising for a tidy answer.
So the first version of Redline did one thing: put the transcript next to the server-side ledger of what the agent actually called. That turned out to be the whole product. The transcript is what the agent said. The ledger is what it did.
The security packs came later, and by accident. I wrote a single indirect-injection task to see whether my agent would fall for a phishing link hidden in a support ticket. It did. So did Claude Code. So did Codex — and then it told me it hadn't clicked anything. That's now 16 attack families and 11,204 cases, all delivered in-band rather than pasted into a prompt.
The thing I fought with longest was making your agent testable without asking you to deploy it anywhere. It ended up as redline dev — your agent runs on your machine, in your repo, with your credentials, and Redline just drives it and grades it alongside the others.
If you've shipped an agent with real tool access: what's the failure that actually worries you? That's what I want in the packs next.
About Redline AI on Product Hunt
“ Attack-test your AI agents and grade what they did”
Redline AI was submitted on Product Hunt and earned 4 upvotes and 1 comments, placing #42 on the daily leaderboard. Most agent evals grade the final answer. Redline grades the behaviour the server's own ledger of what the agent called, not its account of it. One task runs against Claude Code, Codex and the agent in your own repo, each in a clean container with identical tools. On top sit 16 security packs: 11,204 adversarial cases delivered the way real attacks arrive hidden in a support ticket, a document footer, a tool result. Your agent connects with redline dev and never leaves your machine.
On the analytics side, Redline AI competes within Developer Tools, Artificial Intelligence and Security — topics that collectively have 997.9k followers on Product Hunt. The dashboard above tracks how Redline AI performed against the three products that launched closest to it on the same day.
Who hunted Redline AI?
Redline AI was hunted by hritvik Gupta. 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.
For a complete overview of Redline AI including community comment highlights and product details, visit the product overview.
hritvik Gupta