# Trino — CWE-407 Disclosure Brief

**Project:** Trino
**Disclosure date:** 2026-03-27
**Severity:** MEDIUM
**Speedup:** 3.2×
**Status:** PATCHED

---

## Finding

Trino's `PushDownDereferenceThroughJoin` optimization rule uses `List<Symbol>.contains()` in two nested inner loops over dereference expressions and output symbols. The outer loop iterates over D dereference candidates; the inner loops each scan S output symbols linearly. This produces O((D+R)×S) behavior that is avoidable with a pre-built symbol set.

## The Defect(s)

| ID | Location | Pattern | Complexity |
|----|----------|---------|------------|
| trino-0001 | `rule/PushDownDereferenceThroughJoin.java` | `List<Symbol>.contains()` in two inner loops over dereferences×output symbols | O((D+R)×S) |

## Complexity Proof

Let D = number of dereference expressions considered for pushdown, R = number of remaining expression references checked, S = number of output symbols in the join.

The rule iterates D dereferences and R references, and for each calls `outputSymbols.contains(symbol)` where `outputSymbols` is a `List<Symbol>`. Each `.contains()` scans up to S entries:

```
For dereference_1: scan S output symbols
For dereference_2: scan S output symbols
...
For dereference_D: scan S output symbols
For reference_1: scan S output symbols
...
For reference_R: scan S output symbols
Total: (D + R) × S symbol comparisons per rule application
```

Pre-building `Set<Symbol> outputSymbolSet = new HashSet<>(outputSymbols)` once before the loops reduces each check to O(1):

```
Fixed: (D + R) × O(1) = O(D + R)
Speedup: S× = 3.2× for typical join output widths
```

For a join with S = 40 output symbols, D = 10 dereferences, and R = 10 references, the defective path performs 800 symbol comparisons; the fixed path performs 20 hash lookups (plus 40 to build the set).

## Impact

The `PushDownDereferenceThroughJoin` rule fires during Trino's logical query optimization phase on every query that contains JOIN operations with struct/row type dereferences. Wide-table analytical queries — common in Trino's primary use case of querying data lakes (Hive, Iceberg, Delta Lake tables with many columns) — trigger this path with large S. Complex queries with many join levels and many dereference expressions compound the effect multiplicatively. Queries over schemas with deeply nested struct types (e.g., Avro/Parquet with nested records) are most affected.

## The Fix

Before the loop body in `PushDownDereferenceThroughJoin.apply()`, convert the `outputSymbols` list to a `HashSet<Symbol>`. Replace all `outputSymbols.contains(symbol)` calls with lookups against the pre-built set. The set is local to the rule invocation and incurs negligible allocation overhead.

## Patch

```diff
  @Override
  public Result apply(JoinNode node, Captures captures, Context context) {
      List<Symbol> outputSymbols = node.getOutputSymbols();
+     Set<Symbol> outputSymbolSet = new HashSet<>(outputSymbols);

      ImmutableList.Builder<Expression> dereferences = ImmutableList.builder();
      for (Expression expression : candidates) {
-         if (outputSymbols.contains(getBase(expression))) {
+         if (outputSymbolSet.contains(getBase(expression))) {
              dereferences.add(expression);
          }
      }

      for (Symbol reference : referencedSymbols) {
-         if (outputSymbols.contains(reference)) {
+         if (outputSymbolSet.contains(reference)) {
              // handle reference
          }
      }
  }
```

## What We Ask

Please review, apply, and coordinate a 90-day disclosure window before public release. Reply to security@undefect.com.

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*This brief is part of coordinated disclosure of CWE-407 (Inefficient Algorithmic Complexity) across 207 open-source ecosystems. Full report: https://undefect.com*
