BinaryMuse Toml-node: Allocation of Resources Without Limits or Throttling (CVE-2026-114144)
Published Last modified Sources: CVE.org, Hersteller
What is affected, what to do
Update BinaryMuse Toml-node to version 5.0.1.
- Affected
- BinaryMuse Toml-node
lt *..5.0.1
- BinaryMuse Toml-node
- Fixed in
- BinaryMuse Toml-node
5.0.1
- BinaryMuse Toml-node
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Metrics
7.5
Priority
XIEM Effective CVSS: highest available CVSS rating from NVD and vendor data.
Source: Vendor (CNA), CVSS v3
7.5
CVSS v3
Severity High on the scale from 0 to 10.
Source: CVE.org, Hersteller
—
EPSS score
No value is available for this vulnerability.
Show all metrics
- Severity
- High
Priority (0–325)
The priority score is a consolidated metric that condenses several individual signals into a single, action-guiding ranking: technical severity (CVSS), exploitation likelihood (EPSS), known-exploited status (KEV) and the context of the affected asset. The aim is to answer the only truly important question in vulnerability management: what first?
Read in glossary- 67.50 Methodology
Exploit maturity
An exploit is code or a technique that specifically uses a concrete vulnerability to force unintended behaviour — such as executing code or escalating privileges. It is the tool that turns a theoretical flaw into a practical attack.
Read in glossary- no public PoC known
XIEM Effective CVSS
XIEM® is the tiered managed-security operating model from NEOSEC and a registered trademark of NEOSEC GmbH. It extends classic SIEM — the central collection, normalisation and correlation of security-relevant events — with endpoint forensics, network visibility and deception technology, and consolidates them into three building tiers: Sentry, Orchestrate and Command.
Read in glossary- 7.5 Methodology
CVSS v3
CVSS is the globally established, open standard for assessing the technical severity of a vulnerability on a scale from 0 to 10. It describes how easily a flaw can be exploited and what damage it can cause — but not how likely its actual exploitation is. CVSS and the complementary EPSS deliberately answer different questions.
Read in glossary- 7.5
KEV status
The KEV catalogue is a list maintained by the US authority CISA of vulnerabilities for which active exploitation in the wild has been confirmed. It answers not the question „how severe?“ but „is it already being attacked?“ — thereby sharply prioritising patching.
Read in glossary- —
- Published
CWE
CWE is a catalogue of typical weakness types in software and hardware — such as flawed input validation, unsafe memory handling or poor authentication. Where a CVE names a concrete vulnerability in a concrete product, a CWE describes the underlying class of defect.
Read in glossary- CWE-400, CWE-770
Detection rules
No NEOSEC detection rule is available for this vulnerability yet.
Classification under NIS2 and CRA
Rule-based classification from exploitation status and severity. It does not replace a case-by-case assessment.
NIS2
NIS2 is EU Directive (EU) 2022/2555 to raise the level of cybersecurity across the Union. It substantially broadens obligations compared with the first NIS directive: more sectors, mandatory risk management, staged reporting duties and personal accountability of senior management.
Read in glossary- High technical severity: assess and remediate the vulnerability in vulnerability handling under Art. 21(2)(e) NIS2 and document the decision.
CRA
The CRA is EU Regulation (EU) 2024/2847 setting horizontal cybersecurity requirements for „products with digital elements“ — from industrial controllers and software to connected consumer devices. For the first time manufacturers must ensure security across the entire product lifecycle, handle vulnerabilities and provide security updates.
Read in glossary- From 11.12.2027, Annex I Part II CRA requires manufacturers of affected products with digital elements to handle vulnerabilities without delay and provide security updates.
ISO/IEC 27001
ISO/IEC 27001 is the internationally leading standard for an information security management system (ISMS). It describes a risk-based, process-oriented framework to systematically plan, implement, review and improve information security.
Read in glossary- Control A.8.8, management of technical vulnerabilities: assess relevance to your systems, plan remediation and keep evidence.
Description
Summary
toml.parse() converts integer literals (hex, octal, binary, and decimal) to BigInt without first bounding the length of the digit sequence. Since BigInt(string) construction from a very long numeric string runs in super-linear time, a single small, well-formed TOML document containing one long integer literal can pin a Node.js process's event loop at 100% CPU for several seconds — a denial of service for any application that parses attacker-supplied or third-party TOML. No authentication or complex crafting is required.
Details
In lib/parser.js, the grammar actions that build integer nodes call BigInt() directly on the matched digit text, with no upper bound on its length:
lib/parser.js:326— hex:BigInt('0x' + stripUnderscores(digits))lib/parser.js:327— octal:BigInt('0o' + stripUnderscores(digits))lib/parser.js:328— binary:BigInt('0b' + stripUnderscores(digits))lib/parser.js:329— decimal:BigInt(stripUnderscores(text))
The parser does enforce a nesting-depth limit (MAX_DEPTH, default 500, lib/parser.js:4343) to guard against stack overflow from deeply nested arrays/inline tables (per GHSA-82x6-q7mm-w9cf). However, that guard only bounds structural nesting — it does not bound the length of a single scalar token.
The subsequent 64-bit range check in lib/compiler.js (reduceInteger, lines 143–150, comparing against INT64_MIN / INT64_MAX defined at lines 3–4) happens after the expensive BigInt() conversion has already completed. It therefore provides no protection against this cost — the CPU time is already spent by the time the value is rejected as out of range.
PoC
const toml = require('toml');
const N = 5_000_000; // ~5 MB request body
const doc = 'x = 0x' + 'f'.repeat(N);
const start = Date.now();
try {
toml.parse(doc); // eventually throws "outside the 64-bit signed integer range" —
// but only after the costly conversion has run
} catch (e) {}
console.log('elapsed:', Date.now() - start, 'ms');
Measured results:
| Digits (hex) | Approx. payload size | Parse time |
|---|---|---|
| 200,000 | ~200 KB | 141 ms |
| 400,000 | ~400 KB | 276 ms |
| 800,000 | ~800 KB | 685 ms |
| 1,600,000 | ~1.6 MB | 1,761 ms |
| 5,000,000 | ~5 MB | 6,061 ms |
Growth is clearly super-linear. The same behavior reproduces for plain decimal literals (3,000,000 '9' digits → ~6.3 s).
Impact
Any application that calls toml.parse() on untrusted or third-party input — config upload endpoints, CI/CD tools ingesting user-supplied .toml files, package managers, linters, editors/language servers — is exposed.
During the conversion, the event loop is fully blocked. In a typical single-threaded Node.js server this stalls all concurrent request handling, not just the request containing the malicious payload. A single ~5 MB request is sufficient to cause several seconds of full CPU denial of service.
Suggested fix: Reject digit sequences above a reasonable length before calling BigInt(), analogous to the existing maxDepth option. A 64-bit signed integer requires at most 20 decimal digits or 16 hex digits, so any digit sequence significantly longer than that is guaranteed to fail the existing range check anyway, and can be rejected with a cheap .length comparison instead of paying for the full BigInt conversion.
Source: NVD (NIST), cvelistv5, GitHub Security Advisories
Affected products
The following versions are affected. Older releases of the same product line are also vulnerable unless stated otherwise.
| Vendor | Product | Affected versions | Fixed in |
|---|---|---|---|
| BinaryMuse | toml-node |
|
|
| npm | toml |
|
|
Weakness classes (CWE)
CWE-400Uncontrolled Resource Consumption
Class
The product does not properly control the allocation and maintenance of a limited resource.
Entry at MITRE CWE-400CWE-770Allocation of Resources Without Limits or Throttling
Base
The product allocates a reusable resource or group of resources on behalf of an actor without imposing any intended restrictions on the size or number of resources that can be allocated.
Entry at MITRE CWE-770
References & sources
- github.comBinaryMuse/toml-node/security/advisories/GHSA-9qmh-m7c6-f92px_refsource_CONFIRM
- github.comBinaryMuse/toml-node/commit/9d52e384f6030932174d1afb0d910154dd6…x_refsource_MISC
- github.comBinaryMuse/toml-node/releases/tag/v5.0.1x_refsource_MISC
Reanalysis & status changes
Chronological NVD audit events for this CVE — reanalyses, CVSS updates, CPE diffs.
New CVE Receivedsecurity-advisories@github.com
- Description: after toml-node is a TOML parser for Node.js and the browser. Prior to 5.0.1, toml.parse() passes unbounded hexadecimal, octal, binary, and decimal digit sequences from lib/parser.js to BigInt() before reduceInteger() in lib/compiler.js checks whether the resulting value fits the TOML 64-bit integer range. Converting a sufficiently long integer string consumes super-linear CPU time and synchronously blocks the Node.js event loop, allowing one attacker-supplied TOML document to deny service to concurrent work in the process. The later range check cannot prevent the conversion cost because it executes after BigInt(). This issue is fixed in version 5.0.1.
- CVSS V3.1: after AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
- CWE: after CWE-400
- CWE: after CWE-770
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