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JS-YAML: Quadratic-complexity DoS in merge key handling via repeated aliases

Moderate severity GitHub Reviewed Published May 31, 2026 in nodeca/js-yaml • Updated Jun 29, 2026

Package

npm js-yaml (npm)

Affected versions

>= 4.0.0, <= 4.1.1
< 3.15.0

Patched versions

4.2.0
3.15.0

Description

Summary

A crafted YAML document can trigger algorithmic CPU exhaustion in js-yaml merge-key processing (<<) by repeating the same alias many times in a merge sequence.
This causes quadratic parse-time behavior relative to input size and can block a Node.js worker/event loop for seconds with a relatively small payload (tens of KB), resulting in denial of service.

Details

The issue is in merge handling inside lib/loader.js:

  • storeMappingPair(...) iterates every element of a merge sequence when key tag is tag:yaml.org,2002:merge.
  • For each element, it calls mergeMappings(...).
  • mergeMappings(...) computes Object.keys(source) and performs _hasOwnProperty.call(destination, key) checks for each key.

When input is of the form:

a: &a {k0:0, k1:0, ..., kK:0}
b: {<<: [*a, *a, *a, ... repeated M times ...]}
all *a entries refer to the same anchored object. After the first merge, subsequent merges are semantically no-ops, but the parser still reprocesses all keys each time.
Resulting work is O(K * M), while input size is O(K + M), giving quadratic scaling as payload grows.
Relevant code path:
lib/loader.js in storeMappingPair(...) merge branch (keyTag === 'tag:yaml.org,2002:merge')
lib/loader.js mergeMappings(...)

Root cause

File: lib/loader.js
Function: storeMappingPair(state, _result, overridableKeys, keyTag, keyNode,
valueNode, startLine, startLineStart, startPos)
Lines: ~359-366

if (keyTag === 'tag:yaml.org,2002:merge') {
  if (Array.isArray(valueNode)) {
    for (index = 0, quantity = valueNode.length; index < quantity; index += 1) {
      mergeMappings(state, _result, valueNode[index], overridableKeys);
    }
  } else {
    mergeMappings(state, _result, valueNode, overridableKeys);
  }
}

When the merge value is a sequence (YAML 1.1 <<: [ *a, *a, ... ]), each element
is handed to mergeMappings() without deduplication. mergeMappings() then does

sourceKeys = Object.keys(source);
for (index = 0; index < sourceKeys.length; index += 1) {
  key = sourceKeys[index];
  if (!_hasOwnProperty.call(destination, key)) {
    setProperty(destination, key, source[key]);
    overridableKeys[key] = true;
  }
}

Every alias reference in the sequence resolves (by design) to the SAME object
via state.anchorMap. After the first merge, every subsequent merge of that same
reference is a pure no-op semantically, but still performs:

  • one Object.keys(source) call (O(K))
  • K _hasOwnProperty.call checks on the destination

Total: M * K hasOwnProperty checks + M Object.keys allocations, while the final
object and all observable side effects are identical to a single merge.

YAML semantics for <<: are idempotent and commutative over duplicate sources,
so collapsing duplicates preserves behavior exactly; this isn't a spec trade-off.

PoC

Environment:
js-yaml version: 4.1.1
Node.js: v24.5.0
Platform: arm64 macOS (reproduced consistently)
Reproduction script:
Create many keys in one anchored map (&a).
Merge that same alias repeatedly via <<: [*a, *a, ...].
Measure parse time and compare with control payload using single merge (<<: *a).
Observed repeated runs (same machine):
K=M=1000, input 9,909 bytes: ~33–36 ms
K=M=2000, input 20,909 bytes: ~121–123 ms
K=M=4000, input 42,909 bytes: ~524–537 ms
K=M=6000, input 64,909 bytes: ~1,608–1,829 ms
K=M=8000, input 86,909 bytes: ~3,395–3,565 ms
Control (single merge, similar key counts):
K=2000: ~1–2 ms
K=4000: ~3 ms
K=8000: ~5 ms
Also verified: repeated-merge output equals single-merge output (same key count and same JSON), confirming excess time is redundant computation.

Impact

This is a denial-of-service vulnerability (CPU exhaustion / algorithmic complexity).
Any service parsing untrusted YAML with js-yaml can be impacted, including API backends, CI tools, config processors, and automation services. An attacker can submit crafted YAML to significantly increase CPU time and reduce availability.

Suggested fix:

Dedupe the merge source list by reference before invoking mergeMappings. Any of
the following are minimal and preserve YAML 1.1 merge semantics:

dedupe in storeMappingPair:

if (keyTag === 'tag:yaml.org,2002:merge') {
  if (Array.isArray(valueNode)) {
    var seen = new Set();
    for (index = 0, quantity = valueNode.length; index < quantity; index += 1) {
      var src = valueNode[index];
      if (seen.has(src)) continue;   // idempotent; skip redundant alias
      seen.add(src);
      mergeMappings(state, _result, src, overridableKeys);
    }
  } else {
    mergeMappings(state, _result, valueNode, overridableKeys);
  }
}

References

@puzrin puzrin published to nodeca/js-yaml May 31, 2026
Published to the GitHub Advisory Database Jun 15, 2026
Reviewed Jun 15, 2026
Published by the National Vulnerability Database Jun 22, 2026
Last updated Jun 29, 2026

Severity

Moderate

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v3 base metrics

Attack vector
Network
Attack complexity
Low
Privileges required
None
User interaction
None
Scope
Unchanged
Confidentiality
None
Integrity
None
Availability
Low

CVSS v3 base metrics

Attack vector: More severe the more the remote (logically and physically) an attacker can be in order to exploit the vulnerability.
Attack complexity: More severe for the least complex attacks.
Privileges required: More severe if no privileges are required.
User interaction: More severe when no user interaction is required.
Scope: More severe when a scope change occurs, e.g. one vulnerable component impacts resources in components beyond its security scope.
Confidentiality: More severe when loss of data confidentiality is highest, measuring the level of data access available to an unauthorized user.
Integrity: More severe when loss of data integrity is the highest, measuring the consequence of data modification possible by an unauthorized user.
Availability: More severe when the loss of impacted component availability is highest.
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L

EPSS score

Exploit Prediction Scoring System (EPSS)

This score estimates the probability of this vulnerability being exploited within the next 30 days. Data provided by FIRST.
(17th percentile)

Weaknesses

Inefficient Algorithmic Complexity

An algorithm in a product has an inefficient worst-case computational complexity that may be detrimental to system performance and can be triggered by an attacker, typically using crafted manipulations that ensure that the worst case is being reached. Learn more on MITRE.

CVE ID

CVE-2026-53550

GHSA ID

GHSA-h67p-54hq-rp68

Source code

Credits

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