GraphQL-core: Denial of service via quadratic complexity in the OverlappingFieldsCanBeMerged validation rule

Summary

The OverlappingFieldsCanBeMerged validation rule can be driven into quadratic — and in the worst case O(n²·m²) — running time by a small, highly compressible query. A single 364 KB document can occupy one CPU core for over five minutes during validation, before any resolver runs. Because the rule is part of specified_rules and therefore enabled by default, every GraphQL-core based server is affected at default settings.

Details

OverlappingFieldsCanBeMerged compares every pair of fields that share a response name and recurses into their sub-selections. The memoization added for CVE-2023-26144 (GHSA-9pv7-vfvm-6vr7) is keyed by named fragment identity, so it does not cover this path: inline fragments are flattened into the parent selection set before the cache is consulted, and therefore every pair is re-compared from scratch at every nesting level.

Repeating an inline fragment that selects the same response name at two nesting levels multiplies the two effects. There was no comparison budget and no validation timeout, so the rule ran to completion regardless of cost.

The cost is incurred in the validation phase, which is what makes this hard to defend against from outside the library: query-depth limiters, complexity analyzers and cost estimators all operate on the parsed document after validation, and the malicious document is trivially shallow (depth 3, complexity 1). The payload is also one short string repeated many times, so it compresses to a few kilobytes and slips past body-size limits and WAF inspection that only see the compressed request.

Proof of concept

import time
from graphql import build_schema, parse, validate

schema = build_schema(
    "type Query { field: Node } type Node { f: Node, g: Node, x: String }"
)

def gen(n: int, m: int) -> str:
    inner = " ".join(["... on Node { x }"] * m)
    outer = " ".join([f"... on Node {{ f {{ {inner} }} }}"] * n)
    return f"{{ field {{ {outer} }} }}"

query = gen(200, 100)          # 364 KB, gzips to a few KB
document = parse(query)
start = time.perf_counter()
validate(schema, document)      # returns no errors — it just burns CPU
print(f"{(time.perf_counter() - start):.0f}s")

Measured on GraphQL-core 3.2.8 / CPython 3.12 / Linux x86_64:

Doubling n at fixed m quadruples the time, as expected for a quadratic outer loop driving a quadratic inner walk.

Impact

Denial of service. One request pins one worker process for minutes; because CPython holds the GIL for this pure-CPU work, a handful of concurrent requests can saturate a typical multi-worker deployment. No authentication is required, and no data is disclosed or modified.

Patches

Fixed in 3.2.12 and 3.3.0rc1.

Validation now enforces a per-document comparison budget. Once MAX_FIELD_COMPARISONS (default 250_000) pairwise comparisons have been made, the rule aborts and reports a GraphQLError instead of running to completion:

Query is too complex to validate for overlapping fields: exceeded 250000 field comparisons. Validation was aborted.

The default is far above what any realistic query reaches. It is a module-level constant and can be raised or lowered:

from graphql.validation.rules import overlapping_fields_can_be_merged

overlapping_fields_can_be_merged.MAX_FIELD_COMPARISONS = 1_000_000

Note the behaviour change: a pathological query that previously validated — slowly — now produces a validation error.

Workarounds

If you cannot upgrade, reject oversized documents before they reach validate(). Note that a request body-size limit must be applied to the decompressed body to be effective here, since the payload is highly compressible. Removing OverlappingFieldsCanBeMergedRule from the rule set is not a safe workaround: it is a correctness rule required by the specification.

A body-size limit remains worthwhile after upgrading — the comparison budget bounds this specific rule, not overall request cost.

Credits

Reported by @BZHunt, who also reviewed the fixes before release. In memory of ZaX, who was the driving force behind this discovery.

Independently found and diagnosed by @bcmyguest, who also proposed a fix.