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SlotGuard addresses critical privacy risks in LLM agents by replacing brittle placeholder redaction with a system that preserves structural context while eliminating credential leakage. By rewriting sensitive bindings into typed slots within local transcripts, it maintains agent reasoning performance without exposing data to external providers or cross-turn references. This approach offers a robust solution for securing the growing ecosystem of autonomous AI tools against observation-based attacks.
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SlotGuard: Stop Oversharing Private Local Context in LLM Agent Transcri

arXiv2 min de cititArticolul și perspectiva sunt în engleză.

arXiv:2607.17147v1 Announce Type: cross Abstract: LLM agents can leak privacy (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\%. Transcript rewriting takes a median of 14.424~$\mu$s per agent turn. The code is publicly accessible at https://github.com/illinoisdata/SlotGuard.

Abstract:LLM agents can leak privacy (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\%. Transcript rewriting takes a median of 14.424~$\mu$s per agent turn. The code is publicly accessible at this https URL.

Cryptography and Security (cs.CR); Computation and Language (cs.CL)

arXiv:2607.17147 [cs.CR]

(or arXiv:2607.17147v1 [cs.CR] for this version)

https://doi.org/10.48550/arXiv.2607.17147 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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