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.
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.
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Pith papers citing it
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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 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 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.
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.
citing papers explorer
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CrackMeBench: Binary Reverse Engineering for Agents
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.
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Dynamic Cyber Ranges
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.
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CyberCertBench: Evaluating LLMs in Cybersecurity Certification Knowledge
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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uGen: An Agentic Framework for Generating Microarchitectural Attack PoCs
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.
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Systematic Capability Benchmarking of Frontier Large Language Models for Offensive Cyber Tasks
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.
- RAVEN: Retrieval-Augmented Vulnerability Exploration Network for Memory Corruption Analysis in User Code and Binary Programs