CVE-2026-0621

Jan. 5, 2026, 10:15 p.m.

8.7
High

Description

Anthropic's MCP TypeScript SDK versions up to and including 1.25.1 contain a regular expression denial of service (ReDoS) vulnerability in the UriTemplate class when processing RFC 6570 exploded array patterns. The dynamically generated regular expression used during URI matching contains nested quantifiers that can trigger catastrophic backtracking on specially crafted inputs, resulting in excessive CPU consumption. An attacker can exploit this by supplying a malicious URI that causes the Node.js process to become unresponsive, leading to a denial of service.

Product(s) Impacted

Vendor Product Versions
Anthropic
  • Mcp Typescript Sdk
  • *

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-1333
Inefficient Regular Expression Complexity
The product uses a regular expression with an inefficient, possibly exponential worst-case computational complexity that consumes excessive CPU cycles.

*CPE(s)

Affected systems and software identified for this CVE.

Type Vendor Product Version Update Edition Language Software Edition Target Software Target Hardware Other Information
a anthropic mcp_typescript_sdk / / / / / / / /

CVSS Score

8.7 / 10

CVSS Data - 4.0

  • Attack Vector: NETWORK
  • Attack Complexity: LOW
  • Attack Requirements: NONE
  • Privileges Required: NONE
  • User Interaction: NONE
  • Scope:
  • Confidentiality Impact: NONE
  • Integrity Impact: NONE
  • Availability Impact: HIGH
  • Exploit Maturity: NOT_DEFINED
  • CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X

    View Vector String

Timeline

Published: Jan. 5, 2026, 9:16 p.m.
Last Modified: Jan. 5, 2026, 10:15 p.m.

Status : Received

CVE has been recently published to the CVE List and has been received by the NVD.

More info

Source

disclosure@vulncheck.com

*Disclaimer: Some vulnerabilities do not have an associated CPE. To enhance the data, we use AI to infer CPEs based on CVE details. This is an automated process and might not always be accurate.