about
About
Research to detection to shipped product. That loop is the job.
I’m Daniel Alfasi, AI Security Research Lead at Reco, based in Tel Aviv.
I lead AI security research with a bias toward outcomes you can run in production: agentic red teaming, adversarial scenario generation, and detection logic that closes the loop on the attacks we find.
What I care about
- Agentic systems under attack - direct and indirect prompt injection, jailbreaks, tool misuse, memory and RAG poisoning
- Automation - scenario generation, goal optimization, quantitative methods for the harnesses red-team agents run in
- The full loop - research → detection → shipped product, not findings that die in a slide deck
Background
Before Reco I spent several years at CyberArk as a data scientist and senior software engineer - user behavior analytics, classical ML for detections, graph methods, and production security systems on AWS. Earlier work spanned trade-finance research, attack-surface management at Illusive Networks, and cloud engineering at Perfecto.
I hold an MSc in Computer Science from Reichman University (knowledge graphs and LLMs; work that led to VulnScopper at CoNEXT GNNet 2024) and a BSc in Computer Science from Ariel University.
I’ve contributed to the OWASP AI Vulnerability Scoring System (AIVSS) and the OWASP Top 10 for Agentic Skills.