agent/papers/items/2026-2606-31639-a-lifecycle-and-application-stack-survey-of-large-language-model-vulnerabilities.md

Paper: A Lifecycle and Application-Stack Survey of Large Language Model Vulnerabilities: Attacks, Risks, Defenses, and Open Problems

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type: paper title: "A Lifecycle and Application-Stack Survey of Large Language Model Vulnerabilities: Attacks, Risks, Defenses, and Open Problems" authors: Seyed Bagher Hashemi Natanzi, Bo Tang year: 2026 venue: arXiv url: https://arxiv.org/abs/2606.31639 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-06-30 updated_at: 2026-06-30 status: queued relevance: high topics:

• agent-evaluation
• agent-safety
• coding-agent
• embodied-agent
• memory
• planning
• rag
• tool-use
• workflow-agent methods:

benchmarks:

models:

datasets:

• cs.CR
• cs.AI
• cs.GT
• cs.LO related_concepts:

related_jobs:

related_experiments:

related_projects:

collection_score: 17 collection_queries: agent-evaluation, autonomous-agent-llm

One-line Takeaway

Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.

Why Collected

• matched queries: agent-evaluation, autonomous-agent-llm
• inferred topics: agent-evaluation, agent-safety, coding-agent, embodied-agent, memory, planning, rag, tool-use, workflow-agent
• arXiv categories: cs.CR, cs.AI, cs.GT, cs.LO
• collection score: 17

Review Checklist

• Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
• Does it include a benchmark, dataset, code, or reproducible experimental setup?
• Should it be promoted from queued to skimmed or summarized?

Links

• arXiv: https://arxiv.org/abs/2606.31639