Four Failure Modes, Two Fixes, and a Loop: Hebrew Name Matching in an Agent Authorization Gate

A production authorization gate for an AI agent system asks one question before any action that touches a person: did the manager name this person in the instruction? When the instruction text is Hebrew, the naive implementation — a substring check — fails open: prefix letters glue onto words, so short names are swallowed inside ordinary vocabulary, and actions execute on people the manager never mentioned. The standard fix, a regex word boundary, fails in the opposite direction: \b never matches Hebrew in engines where \w is ASCII, so every action escalates. This article walks through four failure modes and sorts them by direction (fail-open vs. fail-closed), measures the name/noun collision on a pre-registered list of 89 Israeli given names (44.9% are also common nouns), shows why a spellchecker is the wrong oracle in a script without capitalization, and reports a production finding: in a gate that logs only escalations, false positives are not merely unmeasured — they are unrecordable. Over-escalation is not a safe default either: it supplies the precondition of approval-fatigue attacks (MITRE ATT&CK T1621) for free. The conclusion is structural: anchor person-actions to entity identifiers chosen upstream, and log every gate decision, not only the escalations. Hebrew and English versions of the article are included.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-08-18
DOI
https://doi.org/10.5281/zenodo.22001956
Primary Topic
Natural Language Processing Techniques
Type
preprint
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preprint

Four Failure Modes, Two Fixes, and a Loop: Hebrew Name Matching in an Agent Authorization Gate

Ariel Levy
Zenodo (CERN European Organization for Nuclear Research)
Natural Language Processing Techniques
preprint

Four Failure Modes, Two Fixes, and a Loop: Hebrew Name Matching in an Agent Authorization Gate

Ariel Levy
preprint en

Abstract

A production authorization gate for an AI agent system asks one question before any action that touches a person: did the manager name this person in the instruction? When the instruction text is Hebrew, the naive implementation — a substring check — fails open: prefix letters glue onto words, so short names are swallowed inside ordinary vocabulary, and actions execute on people the manager never mentioned. The standard fix, a regex word boundary, fails in the opposite direction: \b never matches Hebrew in engines where \w is ASCII, so every action escalates. This article walks through four failure modes and sorts them by direction (fail-open vs. fail-closed), measures the name/noun collision on a pre-registered list of 89 Israeli given names (44.9% are also common nouns), shows why a spellchecker is the wrong oracle in a script without capitalization, and reports a production finding: in a gate that logs only escalations, false positives are not merely unmeasured — they are unrecordable. Over-escalation is not a safe default either: it supplies the precondition of approval-fatigue attacks (MITRE ATT&CK T1621) for free. The conclusion is structural: anchor person-actions to entity identifiers chosen upstream, and log every gate decision, not only the escalations. Hebrew and English versions of the article are included.

Zenodo (CERN European Organization for Nuclear Research)
Peace, Justice and strong institutions
Natural Language Processing Techniques
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