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D-CIPHER: Dynamic collaborative intel- ligent multi-agent system with planner and heterogeneous executors for offensive security.CoRR, abs/2502.10931

6 Pith papers cite this work. Polarity classification is still indexing.

6 Pith papers citing it

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cs.CR 5 cs.SE 1

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2026 6

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representative citing papers

CrackMeBench: Binary Reverse Engineering for Agents

cs.SE · 2026-05-11 · accept · novelty 7.0

CrackMeBench introduces 20 deterministic binary validation tasks and reports GPT-5.5 solving 11/12 generated ones at pass@3 while Claude and Kimi lag, especially on harder tasks.

Dynamic Cyber Ranges

cs.CR · 2026-04-27 · unverdicted · novelty 7.0

Dynamic Cyber Ranges with LLM defender agents reduce attacker success to 0-55% and preserve evaluation headroom as models advance by using comparable capabilities on both sides.

CyberCertBench: Evaluating LLMs in Cybersecurity Certification Knowledge

cs.CR · 2026-04-22 · unverdicted · novelty 7.0

CyberCertBench shows frontier LLMs reach human-expert performance on general IT and networking security but drop on vendor-specific and formal standards questions such as IEC 62443, with a new framework for producing interpretable explanations.

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Showing 4 of 4 citing papers after filters.

  • Dynamic Cyber Ranges cs.CR · 2026-04-27 · unverdicted · none · ref 51

    Dynamic Cyber Ranges with LLM defender agents reduce attacker success to 0-55% and preserve evaluation headroom as models advance by using comparable capabilities on both sides.

  • CyberCertBench: Evaluating LLMs in Cybersecurity Certification Knowledge cs.CR · 2026-04-22 · unverdicted · none · ref 24

    CyberCertBench shows frontier LLMs reach human-expert performance on general IT and networking security but drop on vendor-specific and formal standards questions such as IEC 62443, with a new framework for producing interpretable explanations.

  • uGen: An Agentic Framework for Generating Microarchitectural Attack PoCs cs.CR · 2026-05-15 · unverdicted · none · ref 48

    uGen is the first retrieval-augmented multi-agent LLM framework for generating functionally correct microarchitectural attack PoCs, reporting up to 100% success on Spectre-v1 and 80% on Prime+Probe at low cost.

  • Systematic Capability Benchmarking of Frontier Large Language Models for Offensive Cyber Tasks cs.CR · 2026-04-18 · unverdicted · none · ref 7

    Claude 4.5 Opus reaches 59% solve rate on offensive cyber CTF tasks, with a Kali Linux environment adding 9.5 percentage points over Ubuntu while prompt engineering often hurts performance in equipped setups.