GHSA-vqpr-j7v3-hqw9 is a high-severity (CVSS 7.5) CWE-1333 vulnerability in valibot. A fix is available for valibot — see the affected versions and patch details below.
Valibot has a ReDoS vulnerability in `EMOJI_REGEX`
Exploitation Status
No confirmed exploitation observed yet
- CISA assesses this as automatable — exploitation doesn’t require manual, per-target effort, which raises the odds of mass scanning and opportunistic attacks.
- CISA’s own triage has not observed active exploitation or public proof-of-concept code for this CVE as of its last assessment.
Exploitation and automatability from CISA’s SSVC triage for GHSA-vqpr-j7v3-hqw9.
EPSS Exploitation Probability
EPSS (Exploit Prediction Scoring System) is a daily probability model maintained by FIRST.org. It estimates the likelihood a CVE will be exploited in production environments within the next 30 days, derived from real-world threat intelligence signals.
How urgent is this, really
GHSA-vqpr-j7v3-hqw9 plotted by exploitation likelihood (EPSS) against impact (CVSS). The shaded corner — EPSS 50%+ and CVSS 7.0+ — is where this CVE doesn't sit, though severity or exploitability alone can still warrant action.
Where this sits among everything scored
Of 377,333 CVEs with a current EPSS score, this one falls in the < 10% band (highlighted). Real counts from FIRST.org, not a sample — log-scaled since the landscape is heavily right-skewed.
Real-World Exposure
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.
valibotnpmDescription
Summary
The EMOJI_REGEX used in the emoji action is vulnerable to a Regular Expression Denial of Service (ReDoS) attack. A short, maliciously crafted string (e.g., <100 characters) can cause the regex engine to consume excessive CPU time (minutes), leading to a Denial of Service (DoS) for the application.
Details
The ReDoS vulnerability stems from "catastrophic backtracking" in the EMOJI_REGEX. This is caused by ambiguity in the regex pattern due to overlapping character classes.
Specifically, the class \p{Emoji_Presentation} overlaps with more specific classes used in the same alternation, such as [\u{1F1E6}-\u{1F1FF}] (regional indicator symbols used for flags) and \p{Emoji_Modifier_Base}.
When the regex engine attempts to match a string that almost matches but ultimately fails (like the one in the PoC), this ambiguity forces it to explore an exponential number of possible paths. The matching time increases exponentially with the length of the crafted input, rather than linearly.
PoC
The following code demonstrates the vulnerability.
import * as v from 'valibot';
const schema = v.object({
x: v.pipe(v.string(), v.emoji()),
});
const attackString = '\u{1F1E6}'.repeat(49) + '0';
console.log(`Input length: ${attackString.length}`);
console.log('Starting parse... (This will take a long time)');
// On my machine, a length of 99 takes approximately 2 minutes.
console.time();
try {
v.parse(schema, {x: attackString });
} catch (e) {}
console.timeEnd();
Impact
Any project using Valibot's emoji validation on user-controllable input is vulnerable to a Denial of Service attack.
An attacker can block server resources (e.g., a web server's event loop) by submitting a short string to any endpoint that uses this validation. This is particularly dangerous because the attack string is short enough to bypass typical input length restrictions (e.g., maxLength(100)).
Recommended Fix
The root cause is the overlapping character classes. This can be resolved by making the alternatives mutually exclusive, typically by using negative lookaheads ((?!...)) to subtract the specific classes from the more general one.
The following modified EMOJI_REGEX applies this principle:
export const EMOJI_REGEX: RegExp =
// eslint-disable-next-line redos-detector/no-unsafe-regex, regexp/no-dupe-disjunctions -- false positives
/^(?:[\u{1F1E6}-\u{1F1FF}]{2}|\u{1F3F4}[\u{E0061}-\u{E007A}]{2}[\u{E0030}-\u{E0039}\u{E0061}-\u{E007A}]{1,3}\u{E007F}|(?:\p{Emoji}\uFE0F\u20E3?|\p{Emoji_Modifier_Base}\p{Emoji_Modifier}?|(?![\p{Emoji_Modifier_Base}\u{1F1E6}-\u{1F1FF}])\p{Emoji_Presentation})(?:\u200D(?:\p{Emoji}\uFE0F\u20E3?|\p{Emoji_Modifier_Base}\p{Emoji_Modifier}?|(?![\p{Emoji_Modifier_Base}\u{1F1E6}-\u{1F1FF}])\p{Emoji_Presentation}))*)+$/u;
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 📦npm | valibot | ≥ 0.31.0&&< 1.2.0 | 1.2.0npm install valibot@1.2.0 |
Detection & mitigation playbook
Open-source dependencyDetect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for valibot, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.
Fix
Update valibot to 1.2.0 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-vqpr-j7v3-hqw9 is resolved across your whole dependency graph.
Workarounds
If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.
How O3 protects you
O3 Security's impact-aware SCA analyses which vulnerable code paths your application actually calls, so a match like GHSA-vqpr-j7v3-hqw9 can be triaged on real exposure rather than presence alone.
Tailored to GHSA-vqpr-j7v3-hqw9. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.
Frequently Asked Questions
Is GHSA-vqpr-j7v3-hqw9 in your dependencies?
O3 Security finds GHSA-vqpr-j7v3-hqw9 across npm dependencies, including transitive ones, and its impact-aware SCA ranks findings by whether your code actually calls the vulnerable path.