Sieve uses an LLM to generate executable queries from natural language security questions grounded by auto-extracted log-format context, cutting error rates over 3x on complex temporal and cross-event tasks versus manual scripting across 133 queries and 5 log types.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CR 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Parser-Free Querying of Security Logs
Sieve uses an LLM to generate executable queries from natural language security questions grounded by auto-extracted log-format context, cutting error rates over 3x on complex temporal and cross-event tasks versus manual scripting across 133 queries and 5 log types.