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版本更新 · v2arXiv:2607.17147

SlotGuard: Stop Oversharing Private Local Context in LLM Agent Transcripts

Haocheng Xia, Yongjoo Park

原文摘要

LLM agents can expose private local context (e.g., paths, emails) and credentials (e.g., API keys) as agent observations (e.g., tool outputs, shell logs, and file reads) are appended to provider-bound transcripts. Existing placeholder redaction is brittle: it can miss embedded or cross-turn references, over-redact benign lookalikes, and destroy the structure useful for reasoning. We present SlotGuard, a local transcript boundary that can hide sensitive data while retaining agents' performance. SlotGuard rewrites structural bindings as typed, suffix-aware slots, replaces secrets with format-preserving synthetic values, links cross-turn references with a lightweight session graph, and restores raw values only inside the trusted runtime. On controlled repository-oriented agent transcripts, SlotGuard removes all 20,814 annotated structurally sensitive characters across 9,229 paths and reduces credential leakage to 0.0% across 852 planted values. It remains close to raw-transcript task success across four upstream models, while generic redaction drops to 2.5%. Deterministic transcript rewriting takes a median of 14.424 microseconds per agent turn, excluding the optional semantic detector. The code is publicly accessible at https://github.com/illinoisdata/SlotGuard.

cs.CR · cs.CL

新论文 · v1arXiv:2611.01363

Eliminating Servers in State Machine Replication

Dohyun Park, Wenjie Hu, Xiangyao Yu, Mahesh Balakrishnan, Yongjoo Park

原文摘要

State Machine Replication (SMR) underpins many stateful systems, including distributed databases, coordination services, and metadata stores. Fundamentally, SMR requires state to be materialized from a durable total order of commands. Existing SMR systems rely on servers to materialize, locally store, and serve snapshots of state; while the durable total order either resides on the same servers, or on an external, disaggregated shared log. Unfortunately, servers act as brittle, expensive choke-points in such systems, causing service unavailability when they fail; incurring provisioning latency on cold starts; and red-lining when exposed to bad clients. In this paper, we propose Serverless SMR (S^2MR), where both the materialized state and the durable total order are stored on disaggregated storage; clients concurrently maintain a single copy of materialized state on external storage. Our key technical insight is that the shared log abstraction is useful not just for consistently ordering commands in SMR, but also for enabling distributed materialization, thus becoming the only interface for ac hieving SMR. We demonstrate S^2MR by developing AirDB, a transactional key-value store. In our evaluation, AirD B over S^2MR achieves higher availability than existing SMR-based systems like etcd over Raft: it is oblivious to server failures and bad client activity; and spins up 10x-45x faster from a cold start.

cs.DB · cs.DC