We just cracked the AI jailbreak problem!
Our new adversarial guardrail slashes attack success from 82% → 6% while keeping latency under 85ms
How?
We built an AI attacker to constantly jailbreak our own defender.
No more:
❌ Data leaks from prompt injections
❌ Agents going rogue
❌ Waiting for attacks to patch
Instead: Self-evolving RL red-team duking it out with a 5-layer defense stack that self-patches in real time 24/7
When our attacker finds a bypass, we instantly block & patch. It's like having a world-class hacker on your security team, but one that only works for you.
Who's ready to stop playing defense and start hunting vulnerabilities before attackers do? 🎯
Launching soon 👉 DM for demo - see it break (and defend) in real-time.
Just went through OpenAI’s Oct 2025 report on “malicious use of AI”
Some takeways from that is bad actors aren’t inventing crazy new AI hacks. They’re mostly bolting models onto old playbooks (malware, scams, info ops) to move faster & make fewer mistakes.
A few bits that stood out:
-> Russian / Korean / Chinese-speaking crews using AI for debugging, translations, phishing copy, basic C2 tweaks.
-> Scam farms in Cambodia / Myanmar / Nigeria using it to churn cold DMs + fake “investment guru” personas.
Our Mandates SDK is finally out in typescript.
You can now now create mandates, sign them using EIP-191 signatures through client and server agents, and get them verified by our verification layer.
Gitbook, task primitives and integrations coming soon!
https://t.co/yEYuqdunrz
Ship a fix → rerun the adversarial sim:
-> Did the path die?
-> Did the fix open something else?
-> Is your risk score trending down?
Now you’re doing continuous red-teaming, not one-time “security theater.”
This is why we call QuillShield “The Red Team Co-pilot of Web3”
If your own AI can’t break you after thousands of attacks,
good luck to everyone else.
Most teams still treat security like a final checkbox before mainnet.
We built QuillShield so security becomes a continuous adversarial game your own AI plays against you.
Here’s how teams use QuillShield as their Red Team Co-pilot of Web3 👇
Instead of generic “High severity bug” messages, QuillShield gives you:
-> Exact attack path (sequence of calls + parameters)
-> What the attacker gains (fund drain, stuck funds, privilege escalation)
-> Why it works (state condition or missing guard they exploit)
This makes it much easier for devs to understand, reproduce, and fix the issue.
QuillAI unites adversarial agents into a continuous swarm simulating exploits, scoring risk & deploying guardrails to protect users and smart contracts.
AI agents across the on-chain economy. You agree?
Now it's time to Test & ship:
ngrok http 3000 → set NEXT_PUBLIC_URL → cast your frame (Use App).
Generate frame env: npx create-onchain --manifest. Prod: NETWORK=base, set CDP_API_KEY_ID/SECRET, prod wallet, plus rate limits, logs & server-side validation.c
For the full deep dive, hit Coinbase’s x402 Miniapps docs: https://t.co/1PD2rjiFOv
Ever heard of Miniapps?
Miniapps are lightweight apps that run inside Farcaster clients (e.g., Warpcast, TBA). Built with MiniKit, they feel native while leveraging Farcaster’s social graph and the user’s connected wallet.
Now let’s ship one with in-flow USDC via x402 in under an hour. From “hello world” to paid features before your coffee cools.
Dive in 🧵
Price per endpoint first, then graduate to unlock tiers.
1) $0.01 “action” routes
• /api/protected → micro-utilities, tipping, basic tools
2) $1.00 content gates
• /api/premium-content → longform, datasets, templates
3) $5.00 feature unlocks
• /api/exclusive-feature → pro tools, generators, bulk ops
Gate several endpoints at once or issue a “session pass” by checking a paid flag server-side for N minutes.
Glad to be the part of the Agent Consortium.
If Agents are where users meet AI, QuillAI is the crash-test + shield, adversarial swarms that harden users, contracts & agents before threats go live.
Let’s make “secure by default” the standard🔥