Focus on perfood vulnerabilities and metrics.
Last updated: 16 Jan 2026, 23:25 UTC
This page consolidates all known Common Vulnerabilities and Exposures (CVEs) associated with perfood. We track both calendar-based metrics (using fixed periods) and rolling metrics (using gliding windows) to give you a comprehensive view of security trends and risk evolution. Use these insights to assess risk and plan your patching strategy.
For a broader perspective on cybersecurity threats, explore the comprehensive list of CVEs by vendor and product. Stay updated on critical vulnerabilities affecting major software and hardware providers.
Total perfood CVEs: 2
Earliest CVE date: 03 Jan 2024, 13:15 UTC
Latest CVE date: 20 Nov 2025, 15:17 UTC
Latest CVE reference: CVE-2025-60794
30-day Count (Rolling): 0
365-day Count (Rolling): 1
Calendar-based Variation
Calendar-based Variation compares a fixed calendar period (e.g., this month versus the same month last year), while Rolling Growth Rate uses a continuous window (e.g., last 30 days versus the previous 30 days) to capture trends independent of calendar boundaries.
Month Variation (Calendar): -100.0%
Year Variation (Calendar): 0%
Month Growth Rate (30-day Rolling): -100.0%
Year Growth Rate (365-day Rolling): 0.0%
Average CVSS: 0.0
Max CVSS: 0
Critical CVEs (≥9): 0
| Range | Count |
|---|---|
| 0.0-3.9 | 2 |
| 4.0-6.9 | 0 |
| 7.0-8.9 | 0 |
| 9.0-10.0 | 0 |
These are the five CVEs with the highest CVSS scores for perfood, sorted by severity first and recency.
Session tokens and passwords in couch-auth 0.21.2 are stored in JavaScript objects and remain in memory without explicit clearing in src/user.ts lines 700-707. This creates a window of opportunity for sensitive data extraction through memory dumps, debugging tools, or other memory access techniques, potentially leading to session hijacking.
A host header injection vulnerability exists in the NPM package @perfood/couch-auth versions <= 0.20.0. By sending a specially crafted host header in the forgot password request, it is possible to send password reset links to users which, once clicked, lead to an attacker-controlled server and thus leak the password reset token. This may allow an attacker to reset other users' passwords and take over their accounts.