Lee Ennis
Sr Manager, Data Science
Lee Ennis leads the AI data science and research team at F5, where he focuses on developing advanced AI security solutions that help enterprises safely deploy and monitor large language models (LLMs) and generative AI systems. His team combines expertise in machine learning, adversarial testing, and model assurance to identify vulnerabilities and strengthen trust in AI-driven environments.

Research by Lee Ennis (12)

Article | Oct 21, 2026
Unprompted: When AI Agents Expose Data Without an Attacker
Four new incidents, and CASI/ARS Score updates
8 min read

Article | Aug 12, 2026
Capability Is Closing the Open-Closed Gap; Security Is Not
A competitive open-weight model, Claude Fable, and Jade Puffer.
7 min read

Article | Jul 14, 2026
Adversarial Tales
A competitive open-weight model, Claude Fable, and Jade Puffer
8 min read

Article | Jun 3, 2026
Topic Bridge
CASI leaderboard shifts, and two incidents where AI was handed the keys.
11 min read

Article | May 27, 2026
The Small Model Cliff
CASI Leaderboard, Bias Jailbreak, and Three Coordinated Supply Chain Incidents
7 min read

Article | Apr 9, 2026
CASI Leaderboard Shifts: Developer Role Attack, and Three Concerning Incidents
AI Security Insights – April 2026
9 min read

Article | Mar 5, 2026
CASI Leaderboard Shifts: Sugar-Coated Poison, and the Expanding AI Attack Surface
AI Security Insights – March 2026
7 min read

Article | Feb 26, 2026
AI Capabilities Are Advancing Faster Than AI Security
AI Security Insights – February 2026
7 min read

Article | Jan 13, 2026
When AI Gets Bullied: How Agentic Attacks Are Replaying Human Social Engineering
AI Security Insights – January 2026
8 min read

Article | Dec 11, 2025
Adversarial Poetry and the Efficacy of AI Guardrails
We investigate the rise of adversarial poetry in AI security. Understand how metaphor-based exploits circumvent guardrails and the defenses we need for LLMs moving forward.
4 min read
Results 1-10 of 12
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