CVE-2026-76892: Malformed JSON Crashes tsParticles MCP Server, Causing Denial of Service

A high-severity vulnerability in tsParticles MCP server allows unauthenticated attackers to terminate the Node.js process with a single malformed JSON request, leaving the service unavailable until restart.

Christopher Ort
By Christopher Ort · 2 min read
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On this page
  1. Vulnerability Overview
  2. Technical Details
  3. Exploitation and Impact
  4. Affected Systems
  5. Patch and Mitigation
  6. Recommendations
  7. Sources

Vulnerability Overview

CVE-2026-76892 is a high-severity denial-of-service vulnerability in the @tsparticles/mcp-server package, a TypeScript library component for creating particle animations. The flaw allows unauthenticated remote attackers to crash the entire Node.js process by sending a single malformed JSON request to the HTTP endpoint.

The vulnerability affects versions prior to 4.3.1 and has been assigned a CVSS v4 score of 8.7.

Technical Details

The vulnerability exists in the HTTP mode POST /mcp handler located in `integrations/mcp-server/src/index.ts`. According to the security advisory, the code calls `JSON.parse()` on incoming request bodies without wrapping the operation in a request-local error boundary or try-catch block.

The vulnerable code pattern is:

“`

const body = await new Promise((resolve, reject) => {

const chunks: Buffer[] = [];

req.on(“data, (chunk) => chunks.push(Buffer.from(chunk)));

req.on(end, () => resolve(Buffer.concat(chunks).toString(utf8″)));

req.on(“error, reject);

});

const parsedBody = body ? JSON.parse(body) : undefined;

“`

When `JSON.parse()` encounters malformed JSON, it raises a `SyntaxError` that propagates up and terminates the Node.js process entirely.

Exploitation and Impact

The vulnerability was verified on version 4.3.0 at commit 0266d469aa2d719cb66a9c6bf09aded4186ec17c. Reproduction requires sending a malformed JSON request to the /mcp endpoint:

“`

POST /mcp HTTP/1.1

Content-Type: application/json

Mcp-Protocol-Version: 2025-11-25

{jsonrpc”:

“`

According to the advisory, this resulted in process termination in 3 out of 3 test runs with the error:

“`

exit_code=1

SyntaxError: Unexpected end of JSON input

at Server. (integrations/mcp-server/src/index.ts:407:38)

“`

The impact is a complete denial of service. An unauthenticated remote attacker can terminate the exposed MCP process with a single malformed request. The service remains unavailable until an external supervisor restarts it. No authentication or privileges are required to exploit this vulnerability.

Affected Systems

The vulnerability affects:

  • **Package**: @tsparticles/mcp-server (npm)
  • **Affected versions**: All versions up to and including 4.3.0
  • **Patched version**: 4.3.1

Patch and Mitigation

Version 4.3.1 fixes the vulnerability by wrapping JSON parsing in proper error handling. The patch, visible in commit 25fb70e7f527a91568adaef576570289083f243b, adds try-catch blocks around both the body reading and JSON parsing operations.

The fixed code now returns HTTP 400 responses with error messages for invalid JSON:

“`javascript

try {

parsedBody = body ? JSON.parse(body) : undefined;

} catch {

res.writeHead(400, { ‘Content-Type’: ‘application/json’ });

res.end(JSON.stringify({ error: ‘Invalid JSON’ }));

return;

}

“`

The process now remains alive after receiving malformed requests.

Recommendations

Organizations using @tsparticles/mcp-server should:

  • Upgrade immediately to version 4.3.1 or later
  • Review logs for evidence of exploitation attempts (repeated process crashes)
  • Ensure external process supervisors are configured to restart the service if crashes occurred
  • Consider implementing rate limiting or request validation at the network layer as defense-in-depth

The fix was merged via pull request #5875 on July 1, 2026.

Sources

Christopher Ort

Christopher Ort

Christopher Ort handles SEO, AI agent workflows and PR & partnerships at i10x.ai, the all-in-one AI workspace built by i10X Global Pte. Ltd. in Singapore. He is a graduate of Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU). He is the author of “The Style Penalty”, a study published on SSRN that analyses 1,576 evaluation decisions by four frontier AI models to show how AI-written CVs fare in automated hiring screens; the research has been covered by heise online and t3n.

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