the-ethics-of-autonomous-ai-agents-for-offensive-s

name	the-ethics-of-autonomous-ai-agents-for-offensive-s
description	Skill generated from arXiv paper 2607.20255: The Ethics of Autonomous AI Agents for Offensive Security
metadata	{"arxiv":{"id":"2607.20255","title":"The Ethics of Autonomous AI Agents for Offensive Security","authors":["Andreas Happe","Jürgen Cito","Jasmin Wachter"],"published":"2026-07-22","categories":["cs.CR","cs.AI"],"url":"https://arxiv.org/abs/2607.20255","utility":1}}

The Ethics of Autonomous AI Agents for Offensive Security

arXiv: 2607.20255
Published: 2026-07-22
Authors: Andreas Happe, Jürgen Cito, Jasmin Wachter
Categories: cs.CR, cs.AI
Utility: 1.00

Key Innovation

LLM-driven autonomous agents are reshaping offensive security. Unlike traditional penetration-testing tooling -- deterministic, narrowly scoped, and operated by trained practitioners -- agentic security tools exhibit \textit{indeterminacy} along three independent dimensions. First, their actions are drawn from a non-deterministic policy whose outputs resist both ex-ante and ex-post explanation, frustrating incident attribution and pre-deployment safety review. Second, their impact is open-ended ...

Potential Application

This paper presents advancements that could be applied to enhance agent capabilities in the areas of cs.CR, cs.AI.

References

• arXiv: https://arxiv.org/abs/2607.20255