ScamShield is a multi-agent AI assistant built with ClawMax to help everyday people identify phishing, scam messages, and online fraud without needing technical knowledge. I created a custom ClawMax team with four specialized agents and four workflows: 1. **Scam Analysis** - Detects suspicious messages, phishing indicators, impersonation, and social engineering. 2. **Independent Verification** - Checks suspicious claims and separates verified evidence from assumptions. 3. **Safety Review** - Evaluates findings and assigns a risk level and confidence level. 4. **Final User Guidance** - Explains the results in simple language and recommends safe next steps. The demo uses a fictional PayPal phishing SMS and shows how the four workflows produce a user-friendly safety report. Alongside ScamShield, I contributed improvements directly to ClawMax during the hackathon at Qualcomm. I reported 24 GitHub issues and submitted 23 pull requests, including 8 security fixes addressing unsafe code execution, file path vulnerabilities, API key exposure, and other security risks. Additional contributions improve workflow execution, reliability, accessibility, and dashboard usability. All 23 pull requests passed GitHub Actions CI and are available for maintainer review and merge. The goal is to make AI agents both more useful for non-technical people and safer to operate.
Built at ClawMax.ai Build Night Silicon Valley
ScamShield - AI Scam Protection with ClawMax
ScamShield is a multi-agent AI assistant built with ClawMax to help everyday people identify phishing, scam messages, and online fraud without needing technical knowledge. I created a custom ClawMax team with four specialized agents and four workflows: 1. **Scam Analysis** - Detects suspicious messages, phishing indicators, impersonation, and social engineering. 2. **Independent Verification** - Checks suspicious claims and separates verified evidence from assumptions. 3. **Safety Review** - Evaluates findings and assigns a risk level and confidence level. 4. **Final User Guidance** - Explains the results in simple language and recommends safe next steps. The demo uses a fictional PayPal phishing SMS and shows how the four workflows produce a user-friendly safety report. Alongside ScamShield, I contributed improvements directly to ClawMax during the hackathon at Qualcomm. I reported 24 GitHub issues and submitted 23 pull requests, including 8 security fixes addressing unsafe code execution, file path vulnerabilities, API key exposure, and other security risks. Additional contributions improve workflow execution, reliability, accessibility, and dashboard usability. All 23 pull requests passed GitHub Actions CI and are available for maintainer review and merge. The goal is to make AI agents both more useful for non-technical people and safer to operate.
ClawMaxClawMax, OpenClaw, Multi-Agent AI, AI Workflows, TypeScript, React, Node.js, GitHub Actions, GitHubKeep exploring what builders shipped.
HackerSquad project
Open Desk
Open Desk is a four-agent team built on ClawMax. You give it a public GitHub repository. Scout reads the project and describes it in plain language. Pathfinder finds the contributing rules. Suggester writes three ways to help, each tied to a real issue or file. Evaluator checks that the ideas match the repo and those rules, then stops and asks before anything is posted. The workflow is Map the Repo, Find the Path, Suggest Contributions, then Check and Ask. In the demo, the crew reviewed Maximilien-ai/clawmax and suggested work on issues #225, #223, and #162. The evaluator passed all three. Nothing was posted upstream.
HackerSquad project
Workin with ClawMax
ClawMac
HackerSquad project
My ClawMax agents
A very descriptive description