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Name-based binary search optimization for Parquet Variant's locate_object_field
#23657
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🩺 Stability & Availability | 🔴 Critical | ⚡ Quick win
Validate
field_idagainstnum_meta_entriesinname_for_id.name_for_idnever checks thatfield_idis inside the dictionary.probe_idat Line 540 comes from the object'sfield_idslist, which is untrusted data, andnarrow_castonly bounds it tosize_typemax.Two consequences follow:
meta_offsets_start + field_id * meta_offset_sizeisintarithmetic. A largeprobe_idoverflows it, which is undefined behavior in device code.field_id >= num_meta_entries, the two reads land in the string-data region instead of the offset table. The decoded "name" is then arbitrary, so the binary search can take the wrong branch or report a false match on malformed input.Add the range check and compute the entry positions in 64 bits.
Please also add a unit test with an object whose
field_idexceeds the dictionary size, to lock in the empty-span result.🛡️ Proposed fix
auto name_for_id = [&](size_type field_id) -> cuda::std::optional<cudf::string_view> { - auto const s = - read_uint64(meta, meta_offsets_start + field_id * meta_offset_size, meta_offset_size); - auto const e = - read_uint64(meta, meta_offsets_start + (field_id + 1) * meta_offset_size, meta_offset_size); + if (field_id < 0 || field_id >= num_meta_entries.value()) { return cuda::std::nullopt; } + // Positions fit in `size_type` because the offset table was bounds-checked above. + auto const entry_pos = meta_offsets_start + field_id * meta_offset_size; + auto const s = read_uint64(meta, entry_pos, meta_offset_size); + auto const e = read_uint64(meta, entry_pos + meta_offset_size, meta_offset_size); if (!s.has_value() || !e.has_value()) { return cuda::std::nullopt; }🤖 Prompt for AI Agents
Source: Coding guidelines