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CVE-2026-33129 is a timing side-channel vulnerability in the h3 Node.js HTTP framework's requireBasicAuth function, allowing remote attackers to recover passwords character-by-character by measuring server response time differences. It affects h3 versions >= 2.0.0-beta.0 through <= 2.0.0-rc.8 (npm package). The vulnerability was reported by researcher simonkoeck, published to the GitHub Advisory Database on March 17–18, 2026, and added to the NVD on March 20, 2026. It carries a CVSS v3.1 base score of 5.9 (Medium) (GitHub Advisory, Red Hat Bugzilla).
The root cause is classified as CWE-208 (Observable Timing Discrepancy). The vulnerable code in requireBasicAuth uses a standard JavaScript strict inequality operator (!==) to compare the user-supplied password against the expected password: if (opts.password && password !== opts.password). In V8 and most JavaScript runtimes, this operator is optimized to "fail fast" — it returns false immediately upon encountering the first mismatched byte, meaning a password with a correct first character takes measurably longer to reject than one with an incorrect first character. By statistically analyzing these minute timing differences across many requests, an attacker can determine the correct password one character at a time, reducing cracking complexity from exponential to linear. The fix (PR #1283) replaced the unsafe comparison with a constant-time timingSafeEqual function and added a random jitter delay (0–99ms) on authentication failures (GitHub Advisory, Fix PR).
Successful exploitation allows an unauthenticated remote attacker to recover plaintext passwords protected by HTTP Basic Authentication in h3-based applications, resulting in a high confidentiality impact with no integrity or availability impact. The attack is most effective in low-latency environments such as local networks or co-located cloud instances where network jitter is minimal, making it practical for attackers sharing the same cloud infrastructure. Credential recovery could enable unauthorized access to protected application resources and potential lateral movement depending on how the recovered credentials are reused (GitHub Advisory, Feedly).
A proof-of-concept (PoC) methodology is publicly documented in the GitHub Security Advisory, describing a concrete, reproducible attack using concurrent packet timing measurement. There is no evidence of active in-the-wild exploitation at this time, and no threat actor attribution has been reported. The EPSS score is approximately 0.029% (0.055% per GitHub Advisory), placing it in the 17th percentile for exploitation likelihood. The vulnerability is not listed in the CISA Known Exploited Vulnerabilities (KEV) catalog (GitHub Advisory, Feedly).
AAAA...) and record the average response time (TTFB) as a baseline reference.AAAA...) and Packet B with a candidate first character (e.g., BAAA...). Measure and compare TTFB for both.Authorization header values; successful authentication following a long sequence of failures.Upgrade h3 to version 2.0.1-rc.9 or later, which replaces the unsafe !== string comparison with a constant-time timingSafeEqual function and adds a random jitter delay (0–99ms) on authentication failures (h3 Release v2.0.1-rc.9, Fix PR). For environments where immediate patching is not possible, implement network segmentation to restrict access to h3 applications from untrusted local network segments, and avoid co-locating untrusted workloads in the same cloud environment as the vulnerable application. Rate-limiting authentication endpoints can also reduce the feasibility of the statistical timing analysis required for exploitation (Feedly).
The vulnerability was published by h3 maintainer pi0 via a GitHub Security Advisory on March 17, 2026, and the fix was merged promptly via PR #1283. Red Hat tracked the issue in Bugzilla (Bug 2449583) and published a CVE entry, indicating awareness across the broader ecosystem. Social media activity was limited, with a Bluesky post noted in tracking data. No significant independent researcher commentary or major media coverage has been identified beyond standard vulnerability database aggregation (Red Hat Bugzilla, GitHub Advisory).
Source: This report was generated using AI
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