PulseAugur
EN
LIVE 23:58:02

Survey details dual-use risks of LLMs in cybersecurity and privacy

A new survey paper details the dual-use risks of large language models (LLMs) and generative AI in cybersecurity and privacy. The paper highlights how these technologies can be used for both advanced defense mechanisms, such as real-time threat detection and secure code generation, and for sophisticated attacks, including AI-generated malware. It notes a significant increase in LLM-generated malware, estimating it comprised 50% of detected threats by 2025. The research synthesizes insights from over 70 sources and offers recommendations for responsible deployment, such as model watermarking and adversarial defense. AI

IMPACT Highlights the critical need for advanced security frameworks and responsible AI deployment to counter evolving AI-driven cyber threats.

RANK_REASON The cluster contains a survey paper published on arXiv detailing research findings and recommendations.

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 3 sources. How we write summaries →

Survey details dual-use risks of LLMs in cybersecurity and privacy

How we ranked this

Signal score
0 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Research
The cluster contains a survey paper published on arXiv detailing research findings and recommendations.
Source corroboration
3 independent sources
Multiple independent publishers reporting the same story raises confidence that it's real and newsworthy.
Topics
paper, safety
Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
100 days old
Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.
Coverage growth since scoring
+1 source(s) since last score
New sources have picked up this story since our last re-score. Score will update on the next scoring pass.

Full methodology in our editorial standards.

COVERAGE [3]

  1. arXiv cs.AI TIER_1 English(EN) · Kiarash Ahi, Saeed Valizadeh ·

    Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies

    arXiv:2607.06963v1 Announce Type: cross Abstract: Large Language Models (LLMs) and generative AI (GenAI) systems, such as ChatGPT, Claude, Gemini, LLaMA, Copilot, Stable Diffusion by OpenAI, Anthropic, Google, Meta, Microsoft, Stability AI, respectively, are revolutionizing cyber…

  2. arXiv cs.CL TIER_1 English(EN) · Saeed Valizadeh ·

    Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies

    Large Language Models (LLMs) and generative AI (GenAI) systems, such as ChatGPT, Claude, Gemini, LLaMA, Copilot, Stable Diffusion by OpenAI, Anthropic, Google, Meta, Microsoft, Stability AI, respectively, are revolutionizing cybersecurity, enabling both automated defense and soph…

  3. Hugging Face Daily Papers TIER_1 English(EN) ·

    Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies

    Large Language Models (LLMs) and generative AI (GenAI) systems, such as ChatGPT, Claude, Gemini, LLaMA, Copilot, Stable Diffusion by OpenAI, Anthropic, Google, Meta, Microsoft, Stability AI, respectively, are revolutionizing cybersecurity, enabling both automated defense and soph…