GHSA-5p4m-2wfm-xmqj

ADVISORY - github

Summary

Quadratic CPU consumption in !!omap resolution (js-yaml 3.x and 4.x)

Summary

resolveYamlOmap() enforces key uniqueness for !!omap sequences with a linear scan (objectKeys.indexOf(...)) inside the per-element loop, making resolution O(n²) in the number of entries. A modestly sized YAML document therefore consumes disproportionate CPU inside yaml.load(), giving a denial of service against any consumer that parses untrusted YAML.

!!omap is registered in the default schema (lib/schema/default.jsrequire('../type/omap')), so a plain yaml.load(untrustedInput) with no options is affected — no custom schema or non-default configuration is required.

This is the same weakness as CVE-2026-59870 / GHSA-724g-mxrg-4qvm, which was fixed in the 5.x line in 5.2.1. That fix was never backported: both currently maintained legacy lines still carry the original implementation.

Affected versions

Line Latest tested Status
3.x 3.15.0 Affected — objectKeys.indexOf(pairKey) at lib/type/omap.js:29
4.x 4.3.0 Affected — objectKeys.indexOf(pairKey) at lib/type/omap.js:30
5.x 5.2.2 Not affected — fixed in 5.2.1 (uses a Set)

Both figures are the newest release of each line at the time of writing, so this is not a "you are on an old version" issue.

Details

lib/type/omap.js (js-yaml 4.3.0):

if (objectKeys.indexOf(pairKey) === -1) objectKeys.push(pairKey)
else return false

objectKeys grows by one element per entry, and Array.prototype.indexOf is a linear scan, so resolving an n-entry !!omap performs roughly 1 + 2 + … + n comparisons — quadratic in n. The work happens synchronously inside yaml.load(), blocking the event loop for its whole duration.

The 5.x line already solves exactly this by tracking seen keys in a Set (src/tag/sequence/omap.ts):

if (carrier.seen.has(key)) return 'duplicate key in ordered map'
carrier.seen.add(key)

Proof of concept

// poc.js  —  node poc.js
const yaml = require('js-yaml');
const doc = n => '!!omap\n' + Array.from({length: n}, (_, i) => `- k${i}: ${i}`).join('\n') + '\n';

for (const n of [10000, 20000, 40000, 80000]) {
  const d = doc(n), t = Date.now();
  yaml.load(d);                      // default schema, no options
  console.log(`n=${n} bytes=${d.length} load=${Date.now() - t}ms`);
}

Measured (node v20.20.2, default heap, no flags)

js-yaml 4.3.0

n=10000  bytes=137787   load=54ms
n=20000  bytes=297787   load=169ms
n=40000  bytes=617787   load=646ms
n=80000  bytes=1257787  load=2607ms

js-yaml 3.15.0

n=10000  bytes=137787   load=53ms
n=20000  bytes=297787   load=166ms
n=40000  bytes=617787   load=641ms
n=80000  bytes=1257787  load=2567ms

Runtime grows by a factor of ~4 for each doubling of n, which is the signature of O(n²) (linear growth would be ~2×).

Scaling further: a 2.48 MB document with 150,000 entries blocked yaml.load() for 10.8 seconds.

Impact

Any service that parses attacker-influenced YAML with js-yaml 3.x or 4.x can be stalled with a small input. Because the loop is synchronous, a single request blocks the Node.js event loop and stalls every other request in the process — so the amplification is per-process, not just per-request.

Suggested severity: consistent with CVE-2026-59870 (the same weakness in 5.x), i.e. Availability-only impact, network attack vector, no privileges or user interaction required.

Suggested fix

Mirror the 5.x fix — replace the linear scan with a Set:

// lib/type/omap.js
const seen = new Set()
// ...
if (seen.has(pairKey)) return false
seen.add(pairKey)

This preserves the existing duplicate-key rejection semantics exactly while making resolution O(n). A maxOmapLength-style cap would also work, but the Set matches what 5.x already ships and requires no new option.

References

  • CVE-2026-59870 / GHSA-724g-mxrg-4qvm — same weakness in 5.0.0–5.2.0, fixed in 5.2.1
  • lib/type/omap.js (3.x, 4.x) — the affected resolver
  • lib/schema/default.js — registers !!omap in the default schema

Discovery

Found by an automated static-analysis and executed-proof-of-concept scanner run against js-yaml 4.2.0, then manually verified against 3.15.0 and 4.3.0 by executing the proof of concept above. All timings in this report were measured on the current releases of each line, not on the version originally scanned.

Common Weakness Enumeration (CWE)

ADVISORY - github

Inefficient Algorithmic Complexity


GitHub

CREATED

UPDATED

EXPLOITABILITY SCORE

3.9

EXPLOITS FOUND
-
COMMON WEAKNESS ENUMERATION (CWE)

CVSS SCORE

7.5high
PackageTypeOS NameOS VersionAffected RangesFix Versions
js-yamlnpm-->=3.0.0,<3.15.13.15.1
js-yamlnpm-->=4.0.0,<4.3.14.3.1

CVSS:3 Severity and metrics

The CVSS metrics represent different qualitative aspects of a vulnerability that impact the overall score, as defined by the CVSS Specification.

The vulnerable component is bound to the network stack, but the attack is limited at the protocol level to a logically adjacent topology. This can mean an attack must be launched from the same shared physical (e.g., Bluetooth or IEEE 802.11) or logical (e.g., local IP subnet) network, or from within a secure or otherwise limited administrative domain (e.g., MPLS, secure VPN to an administrative network zone). One example of an Adjacent attack would be an ARP (IPv4) or neighbor discovery (IPv6) flood leading to a denial of service on the local LAN segment (e.g., CVE-2013-6014).

Specialized access conditions or extenuating circumstances do not exist. An attacker can expect repeatable success when attacking the vulnerable component.

The attacker is unauthorized prior to attack, and therefore does not require any access to settings or files of the vulnerable system to carry out an attack.

The vulnerable system can be exploited without interaction from any user.

An exploited vulnerability can only affect resources managed by the same security authority. In this case, the vulnerable component and the impacted component are either the same, or both are managed by the same security authority.

There is no loss of confidentiality.

There is no loss of trust or accuracy within the impacted component.

There is a total loss of availability, resulting in the attacker being able to fully deny access to resources in the impacted component; this loss is either sustained (while the attacker continues to deliver the attack) or persistent (the condition persists even after the attack has completed). Alternatively, the attacker has the ability to deny some availability, but the loss of availability presents a direct, serious consequence to the impacted component.