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Parsing Agentic Offensive Security's Existential Threat

ID: 3a0d3f7b-7442-52ed-9aae-ef8b4a129eee

STIX ID: report--3a0d3f7b-7442-52ed-9aae-ef8b4a129eee

Feed Name: Dark Reading

Date Published: 2026-04-27

Date Updated: 2026-04-27

Author: Tara Seals

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Executive summary: The article reports on a Black Hat Asia keynote where RunSybil CEO Ari Herbert-Voss argues that while large language models (LLMs) are dramatically speeding up vulnerability discovery and automating parts of offensive workflows, meaningful exploitation still requires significant human validation; defenders should prioritize shifting left, investing in AI-native engineering, layered defenses, and scrutiny of vendor AI claims.

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