---
title: About
canonical_url: https://danielalfasi.com/about/
last_updated: '2026-08-28'
description: Research to detection to shipped product. That loop is the job.
---

I'm **Daniel Alfasi**, AI Security Research Lead at [Reco](https://www.reco.ai), 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**.

### Elsewhere

- [LinkedIn](https://www.linkedin.com/in/daniel-alfasi/)
- [Google Scholar](https://scholar.google.com/citations?user=uxuvP0gAAAAJ)
- [Reco](https://www.reco.ai)

## Sitemap

See the full [sitemap](/sitemap.md) for all pages.