CVE-2025-70949: @perfood/couch-auth Timing Attack Vulnerability

CVE-2025-70949 Overview

An observable timing discrepancy vulnerability has been identified in @perfood/couch-auth version 0.26.0. This timing side-channel attack allows attackers to extract sensitive information by measuring the time taken by authentication operations. By analyzing response time variations, attackers can infer details about valid usernames, password lengths, or other authentication-related data, potentially leading to credential enumeration or authentication bypass scenarios.

Critical Impact
Attackers can leverage timing discrepancies in authentication routines to enumerate valid users and extract sensitive information, potentially facilitating credential stuffing attacks or targeted brute-force campaigns.

Affected Products

@perfood/couch-auth v0.26.0

Discovery Timeline

2026-03-05 - CVE CVE-2025-70949 published to NVD
2026-03-05 - Last updated in NVD database

Technical Details for CVE-2025-70949

Vulnerability Analysis

This vulnerability falls into the category of Side Channel Attack, specifically a timing attack against authentication mechanisms. The @perfood/couch-auth library, which provides authentication functionality for CouchDB-based applications, exhibits observable timing differences in its authentication validation routines.

When processing authentication requests, the library performs string comparison operations that do not execute in constant time. This non-constant time comparison means that the time required to reject an authentication attempt varies based on how many characters match between the submitted credentials and the actual stored credentials. An attacker can statistically analyze these timing variations across multiple requests to incrementally determine valid credential values.

The impact of this vulnerability extends to information disclosure, where attackers can determine whether specific usernames exist in the system, infer password lengths, and potentially recover partial or complete credential information through iterative timing analysis.

Root Cause

The root cause of this vulnerability is the use of non-constant-time string comparison functions when validating authentication credentials. Standard string comparison operations in JavaScript (and most programming languages) terminate early upon finding the first mismatched character, creating measurable timing differences. Secure authentication implementations should use constant-time comparison functions that always perform the same number of operations regardless of input, preventing timing analysis attacks.

Attack Vector

The attack vector for this vulnerability is network-based. An attacker can remotely send authentication requests to the application using the vulnerable @perfood/couch-auth library and measure response times with high precision. By sending multiple requests with systematically varied credentials and performing statistical analysis on the response times, the attacker can extract information about valid credentials.

The attack requires network access to the authentication endpoint but does not require any prior authentication or special privileges. The attacker can perform this attack from anywhere on the network that can reach the vulnerable service.

A proof-of-concept demonstrating this timing attack methodology is available in the GitHub Gist PoC. For additional context on the affected library, see the GitHub Repository for Couch-Auth and the NPM Package for Couch-Auth.

Detection Methods for CVE-2025-70949

Indicators of Compromise

High volume of authentication attempts from single IP addresses with systematically varying credentials
Unusual patterns of failed authentication attempts that appear to be testing character-by-character variations
Network traffic analysis showing precisely timed authentication requests at regular intervals

Detection Strategies

Deploy application-layer monitoring to detect anomalous authentication request patterns
Implement rate limiting with logging to identify potential timing attack enumeration attempts
Configure SIEM rules to alert on statistical anomalies in authentication failure timing patterns
Use network intrusion detection systems to identify high-frequency authentication probing

Monitoring Recommendations

Monitor authentication endpoints for unusual request volume and timing patterns
Enable detailed logging of authentication attempts including timestamps and source IPs
Implement alerting for authentication brute-force patterns that may indicate timing analysis
Review application logs for evidence of credential enumeration activities

How to Mitigate CVE-2025-70949

Immediate Actions Required

Audit applications using @perfood/couch-auth version 0.26.0 for exposure
Implement rate limiting on authentication endpoints to slow timing attack attempts
Deploy web application firewall rules to detect and block suspicious authentication patterns
Consider implementing additional authentication factors to reduce the impact of credential disclosure

Patch Information

No official patch information is currently available for this vulnerability. Monitor the GitHub Repository for Couch-Auth and NPM Package for Couch-Auth for updates. Organizations using this library should evaluate whether to upgrade when a patched version becomes available or implement compensating controls.

Workarounds

Implement network-level rate limiting to throttle authentication requests and reduce timing attack effectiveness
Add random delays to authentication responses to obscure timing differences (jitter injection)
Deploy a reverse proxy with request timing normalization capabilities
Consider wrapping authentication functions with constant-time comparison implementations
Implement account lockout policies to limit the number of authentication attempts per account

bash

# Example: Rate limiting configuration for nginx
# Add to server or location block for authentication endpoint
limit_req_zone $binary_remote_addr zone=auth_limit:10m rate=5r/s;

location /auth {
    limit_req zone=auth_limit burst=10 nodelay;
    # Additional authentication endpoint configuration
}