Paper Suggestion: AgentLeak
Hi! I'd like to suggest adding AgentLeak to the Privacy section (under Vulnerabilities) — it benchmarks privacy leakage across the full multi-agent LLM pipeline.
📄 Paper
"AgentLeak: A Full-Stack Benchmark for Privacy Leakage in Multi-Agent LLM Systems"
🔍 Why it fits
AgentLeak directly addresses LLM privacy vulnerabilities in multi-agent settings — a growing deployment paradigm not covered by existing privacy benchmarks:
- 7 leakage channels measured simultaneously: tool calls, inter-agent messages, RAG queries, code execution, API calls, final outputs, and reasoning traces
- 68.8% of leakage occurs through inter-agent communication — undetectable by output-only auditing
- 41.7% of leakage is missed by output-only evaluation (the current standard approach)
- Covers AutoGen, LangGraph, CrewAI; evaluates GPT-4o, Claude 3.5 Sonnet, Gemini 1.5 Pro, Llama 3.1 70B
- Introduces PII propagation tracking across agent boundaries
This fills a clear gap in the Privacy section: existing entries focus on single-agent or extraction attacks; AgentLeak addresses privacy leakage in multi-agent orchestration.
Thanks for maintaining this resource!
Paper Suggestion: AgentLeak
Hi! I'd like to suggest adding AgentLeak to the Privacy section (under Vulnerabilities) — it benchmarks privacy leakage across the full multi-agent LLM pipeline.
📄 Paper
"AgentLeak: A Full-Stack Benchmark for Privacy Leakage in Multi-Agent LLM Systems"
🔍 Why it fits
AgentLeak directly addresses LLM privacy vulnerabilities in multi-agent settings — a growing deployment paradigm not covered by existing privacy benchmarks:
This fills a clear gap in the Privacy section: existing entries focus on single-agent or extraction attacks; AgentLeak addresses privacy leakage in multi-agent orchestration.
Thanks for maintaining this resource!