Community-powered platform for checking suspicious job offers and malicious coding test repositories. Submit a case — get an evidence-backed risk verdict you can share.
No account needed to browse cases
Research partner
Automation handles intake, scanning, and scoring. Analysts step in for edge cases and appeals.
Clone and analyze public GitHub / Bitbucket repos for install hooks, obfuscated code, exfiltration patterns, and risky scripts.
Detect urgency, off-platform redirects, domain mismatches, and other observable red flags using transparent, rule-based scoring.
Get a plain-language explanation of findings — grounded in evidence, never hallucinated.
Three steps from suspicious message to shareable, evidence-backed case page.
Drop the full recruiting thread into the form. We auto-extract repo links, persona names, companies, and contact channels — no manual field-filling needed.
The worker clones the repo, runs static checks against 50+ malicious patterns, and applies rule-based signal scoring. Your narrative is anonymized before storage.
Get a public, evidence-backed page with the risk verdict, signal breakdown, AI summary, and a clear path to appeal if the outcome looks wrong.
A product team and academic researchers working together — defdone handles the platform, Stony Brook University brings deep expertise in fraud measurement and attacker methodology.
Product Engineer
Owns the full development process from concept through deployment — building scalable product features, Web3 integrations, and AI-powered tools. CS graduate from Poznan University of Technology (thesis on IoT in renewable energy management). Responsible for implementation, testing, and release — turning product direction into working software.
Head of Product
Leads product strategy for technology that helps prevent fraud in the interview process. Deep experience in product leadership, enterprise platforms, AI-native systems, blockchain infrastructure, and distributed technology — focused on turning complex trust problems into practical, user-centered products.
Technical Product Manager
20+ years across enterprise technology and financial services (IBM, Cognizant, Standard Chartered). 3+ years at Casper Association leading DeFi, NFT, and developer tooling projects. His firsthand experience as a target of the recruitment scam campaigns RTIdx detects informs both platform design and threat intelligence. Full-stack blockchain specialist building with Ethereum, Solidity, and Next.js.
PhD Student — Stony Brook University
PhD candidate in Computer Science at Stony Brook, working in the Ethos Lab. Research focuses on developing methodologies to detect and protect against internet scams — designing automated pipelines that leverage LLMs to improve scam classification accuracy and building crawlers to automate scam detection at scale.
Assistant Professor — Stony Brook University
Assistant Professor at Stony Brook University and director of the Ethos Security and Privacy Lab, researching the security and privacy of emerging systems including IoT, AR, and ML.
Publication
Abisheka Pitumpe, Amir Rahmati · arXiv preprint, Feb 2026
Scalable pipeline for characterizing job scams — the methodology and findings behind our threat signal design.
Community-powered platform for checking suspicious job offers and malicious coding test repositories. Submit a case — get an evidence-backed risk verdict you can share.
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