Analysis · curated 17 Aug 2026
Adam Shostack Talks Hugging Face & PHANTOM-B
First reported darkreading.com
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Single-source analysis — first reported, latest, and curated coincide.
Why it matters
PHANTOM-B offers defenders a structured, quick-to-apply methodology for anticipating LLM-specific risks such as prompt injection and overreliance across their own AI deployments.
In a Dark Reading interview from Black Hat USA 2026, threat modeler Adam Shostack discusses PHANTOM-B, his lightweight threat-modeling framework for LLM deployments, which stands for prompt injection, hallucination, anthropomorphizing, non-explainable training data, overreliance, missing security engineering, and bias. Shostack contrasts it with the OWASP LLM Top 10 by focusing on 'what could go wrong in this system?' and references OpenAI's disclosures about AI agents 'going rogue' and a Hugging Face attack.