AgentFlow builds a framework-agnostic Agent Dependency Graph from agent program source code to support static analyses such as BOM generation and prompt-to-tool risk detection, evaluated on 5,399 real programs across five frameworks.
Sok: Understanding vulnerabilities in the large language model supply chain,
3 Pith papers cite this work, alongside 1 external citations. Polarity classification is still indexing.
3
Pith papers citing it
1
external citations · external index
years
2026 3verdicts
UNVERDICTED 3representative citing papers
Conjunctive prompt attacks split adversarial elements across agents and routing paths in multi-agent LLM systems, evading isolated defenses and succeeding through topology-aware optimization.
LiL vulnerabilities are more severe than ecosystem and conventional bugs and drop LLM-based repair Pass@1 by ~10.8%, with three categories often at 0% success.
citing papers explorer
-
AgentFlow: Building Agent Dependency Graphs for Static Analysis of Agent Programs
AgentFlow builds a framework-agnostic Agent Dependency Graph from agent program source code to support static analyses such as BOM generation and prompt-to-tool risk detection, evaluated on 5,399 real programs across five frameworks.
-
Conjunctive Prompt Attacks in Multi-Agent LLM Systems
Conjunctive prompt attacks split adversarial elements across agents and routing paths in multi-agent LLM systems, evading isolated defenses and succeeding through topology-aware optimization.
-
Towards Demystifying and Repairing LLM-in-the-Loop Vulnerabilities
LiL vulnerabilities are more severe than ecosystem and conventional bugs and drop LLM-based repair Pass@1 by ~10.8%, with three categories often at 0% success.