mlsanityData to 14 Oct 2026

Llama-3.1-FoundationAI-SecurityLLM-Reasoning-8B Technical Report

arXiv 2601.21051 ↗First posted 28 Jan 2026cs.AI cs.CR cs.LGcited by 7

On the map: LLM reasoning → Reasoning for agents, planning and code

Abstract (arXiv)

We present Foundation-Sec-8B-Reasoning, the first open-source native reasoning model for cybersecurity. Built upon our previously released Foundation-Sec-8B base model (derived from Llama-3.1-8B-Base), the model is trained through a two-stage process combining supervised fine-tuning (SFT) and reinforcement learning from verifiable rewards (RLVR). Our training leverages proprietary reasoning data spanning cybersecurity analysis, instruction-following, and mathematical reasoning. Evaluation across 10 cybersecurity benchmarks and 10 general-purpose benchmarks demonstrates performance competitive with significantly larger models on cybersecurity tasks while maintaining strong general capabilities. The model shows effective generalization on multi-hop reasoning tasks and strong safety performance when deployed with appropriate system prompts and guardrails. This work demonstrates that domain-specialized reasoning models can achieve strong performance on specialized tasks while maintaining broad general capabilities. We release the model publicly at https://huggingface.co/fdtn-ai/Foundation-Sec-8B-Reasoning.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Placed in Reasoning for agents, planning and code, one of 17 directions in LLM reasoning. Builds on 31 of its 44 references that are in the map. First posted on arXiv 28 Jan 2026.

Builds on

31 of 44 references.

Closest ancestors · 2

Same direction, newest first

  1. 2024OpenAI o1 System Card21 Dec
  2. 2024Qwen2.5-Coder Technical Report18 Sep

Other references · 29

  1. 2024The Llama 3 Herd of Modelscited by 14,715
  2. 2021Training Verifiers to Solve Math Word Problemscited by 10,109
  3. 2024DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Modelscited by 9,379
  4. 2025Qwen3 Technical Reportcited by 8,820
  5. 2021Evaluating Large Language Models Trained on Codecited by 8,320
  6. 2025DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learningcited by 6,330
  7. 2021Measuring Mathematical Problem Solving With the MATH Datasetcited by 5,371
  8. 2025Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilitiescited by 3,796
  9. 2018HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answeringcited by 3,754
  10. 2023Mistral 7Bcited by 3,164
  11. 2025DAPO: An Open-Source LLM Reinforcement Learning System at Scalecited by 2,810
  12. 2022Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Themcited by 1,807
17 more
  1. 2024HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusalcited by 1,429
  2. 2025gpt-oss-120b & gpt-oss-20b Model Cardcited by 1,386
  3. 2025Understanding R1-Zero-Like Training: A Critical Perspectivecited by 1,345
  4. 2020Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning Stepscited by 1,282
  5. 2023Instruction-Following Evaluation for Large Language Modelscited by 1,228
  6. 2023Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversationscited by 1,207
  7. 2024Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluatorscited by 897
  8. 2024Phi-4 Technical Reportcited by 711
  9. 2025From System 1 to System 2: A Survey of Reasoning Large Language Modelscited by 320
  10. 2025Llama-Nemotron: Efficient Reasoning Modelscited by 158
  11. 2025Phi-4-reasoning Technical Reportcited by 151
  12. 2025LLM Post-Training: A Deep Dive into Reasoning Large Language Modelscited by 135
  13. 2024When LLMs Meet Cybersecurity: A Systematic Literature Reviewcited by 71
  14. 2025Llama-3.1-FoundationAI-SecurityLLM-Base-8B Technical Reportcited by 31
  15. 2025Primus: A Pioneering Collection of Open-Source Datasets for Cybersecurity LLM Trainingcited by 23
  16. 2025Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Reportcited by 23
  17. 2024SecBench: A Comprehensive Multi-Dimensional Benchmarking Dataset for LLMs in Cybersecuritycited by 21

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 7.

7 papers.

  1. 2026Antares: Foundation Models for Agentic Vulnerability Localizationcited by 2
  2. 2026FAPO: Fully Automated Prompt Optimization of Multi-Step LLM Pipelinescited by 1
  3. 2026Fine-tuning RoBERTa for CVE-to-CWE Classification: A 125M Parameter Model Competitive with LLMscited by 0
  4. 2026XekRung Technical Reportcited by 0
  5. 2026Honeyquest for LLMs: Rethinking Cyber Deception for AI Attackerscited by 0
  6. 2026Automatic Hard Example Synthesis with Multi-Level Agentic Data Curationcited by 0
  7. 2026KaliBench: A Fine-Grained Benchmark for Cybersecurity Tool Use on Kali Linux with Runtime-Free Verifiable Rewardscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Guided Reasoning in LLM-Driven Penetration Testing Using Structured Attack Trees
  2. 2026Reasoning Topology Matters: A Controlled Study of LLM-Based Cybersecurity Analysis
  3. 2024Crimson: Empowering Strategic Reasoning in Cybersecurity through Large Language Models
  4. 2025Reasoning Under Threat: Symbolic and Neural Techniques for Cybersecurity Verification
  5. 2025AttackSeqBench: Benchmarking the Capabilities of LLMs for Attack Sequences Understanding
  6. 2025Toward Cybersecurity-Expert Small Language Models
  7. 2026Structured but Fragile: On the Limits of LLMs in Cybersecurity Decision-Making
  8. 2025RSafe: Incentivizing proactive reasoning to build robust and adaptive LLM safeguards