McKinsey's Lilli Looks More Like an API Security Failure Than a Model Jailbreak
Why the reported Lilli incident looks like an application-security chain reaching an AI system, not a model jailbreak.
Michael D'Angelo - Writing
Articles on AI security, LLM red teaming, and trust & safety by Michael D'Angelo.
Latest posts
Promptfoo is joining OpenAI
Announcing that Promptfoo has agreed to be acquired by OpenAI.
Notes on the Claude Code 2.1.0 outage
A changelog formatting change took down Claude Code. Lessons about parsing human docs as machine data.
Notes on the Eurostar chatbot "vulnerability" report
Looking at what makes something a vulnerability versus a hardening opportunity in LLM applications.
What I learned shipping 1,000+ PRs with Claude Code
Notes from using Claude Code in parallel git worktrees: Plan Mode, ultrathink, verification loops, and Chrome automation.
How AI Regulation Changed in 2025
Why "AI compliance questions" appeared in security questionnaires and RFPs, and how policy becomes contract requirements.
Why Attack Success Rate (ASR) Isn't Comparable Across Jailbreak Papers
ASR isn't portable across papers because measurement choices dominate the headline number. Includes math and a checklist for reading papers.
GPT-5.2 Initial Trust and Safety Assessment
Day-zero red team of GPT-5.2 focusing on jailbreak resilience and harmful content.
Real-Time Fact Checking for LLM Outputs
Introduces search-rubric, an assertion where a search-enabled judge verifies time-sensitive claims during evals and CI.
When AI becomes the attacker: The rise of AI-orchestrated cyberattacks
Connects malware querying LLMs at runtime with "vibe hacking" case studies. Defense needs continuous testing.
Reinforcement Learning with Verifiable Rewards Makes Models Faster, Not Smarter
RLVR gains are often "search compression" rather than new reasoning ability.
Prompt Injection vs Jailbreaking: What's the Difference?
Jailbreaking targets model safety training; prompt injection targets application trust boundaries.
AI Safety vs AI Security in LLM Applications: What Teams Must Know
Safety protects people from harmful outputs; security protects systems from adversarial manipulation.
Promptfoo Raises $18.4M Series A
Announcing our Series A led by Insight Partners with participation from a16z.
Evaluating political bias in LLMs
Open methodology and dataset (2,500 political statements) to measure political leaning in models.
Celebrating 100,000 Users
Promptfoo's journey from prompt evaluation to AI red teaming, marking 100,000 users.