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New toolkit targets overlooked AI attack surfaces in security audits

A new open-source threat modeling toolkit aims to address the significant gaps in current AI security audits, which often overlook crucial areas like training data, prompt pipelines, model weights, and agentic tool calls. The toolkit, developed by Hernan Huwyler, provides engineers and architects with practical guidance to better secure AI systems by covering a more comprehensive attack surface. AI

IMPACT Provides engineers with a more comprehensive approach to AI security, addressing overlooked vulnerabilities in training data and agentic systems.

RANK_REASON The cluster describes a new software toolkit for AI security, which falls under the 'tool' category.

Read on Mastodon — fosstodon.org →

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New toolkit targets overlooked AI attack surfaces in security audits

COVERAGE [1]

  1. Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] ·

    Most AI security audits miss 70% of the attack surface. Training data, prompt pipelines, model weights, and agentic tool calls are # AI 's real battleground. Fr

    Most AI security audits miss 70% of the attack surface. Training data, prompt pipelines, model weights, and agentic tool calls are # AI 's real battleground. Free open-source # threatmodeling toolkit for engineers and architects: https:// github.com/hwyler/ai-threat-mo deling-too…