Evaluating Context Segmentation in Locally Deployable SLMs for Cybersecurity CTF Tasks
Published 16 Sept 2026arXiv:2609.12839
Updated 7 h ago · first seen 14 Sept 2026
paper_01M2F500SVWCPKPDVD2G7W2S2T
Abstract
-cross Abstract: The proliferation of highly capable open-weight Small Language Models (SLMs) democratizes access to advanced cybersecurity capabilities, posing a escalating risk as these models can bypass proprietary API guardrails when deployed locally. However, SLMs deployed as autonomous agents often struggle with long-horizon, exploratory tasks like cybersecurity Capture The Flag (CTF) challenges due to context bloat and cognitive degradation from accumulated tool-call outputs. To understand and mitigate this cybersecurity threat, we introduce context segmentation, a two-level agentic framework that divides complex exploitation tasks into manageable, contextually isolated sub-problems. Evaluating on the picoCTF dataset using memory-constrained gemma-4 models, we demonstrate that for the E4B model, our strategy acts as an intelligent search, achieving competitive rewards with superior token efficiency compared to brute-force retries, and successfully solving 18.52% of tasks that standard agentic execution fails to complete. Code is available at https://github.com/9xeb/context-segmentation.
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- Property changedPaperEvaluating Context Segmentation in Locally Deployable SLMs for Cybersecurity CTF Tasks
Evaluating Context Segmentation in Locally Deployable SLMs for Cybersecurity CTF Tasks: published at changed from 2026-09-15T04:00:00+00:00 to 2026-09-16T04:00:00+00:00
Published15 Sept 2026→16 Sept 2026arxiv - Property changedPaperEvaluating Context Segmentation in Locally Deployable SLMs for Cybersecurity CTF Tasks
Evaluating Context Segmentation in Locally Deployable SLMs for Cybersecurity CTF Tasks: arxiv announce type changed from cross to replace
Arxiv announce typecross→replacearxiv - Property changedPaperEvaluating Context Segmentation in Locally Deployable SLMs for Cybersecurity CTF Tasks
Evaluating Context Segmentation in Locally Deployable SLMs for Cybersecurity CTF Tasks: published at changed from 2026-09-14T04:00:00+00:00 to 2026-09-15T04:00:00+00:00
Published14 Sept 2026→15 Sept 2026arxiv - New paperPaperEvaluating Context Segmentation in Locally Deployable SLMs for Cybersecurity CTF Tasks
New paper: Evaluating Context Segmentation in Locally Deployable SLMs for Cybersecurity CTF Tasks
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