Focus on authlib vulnerabilities and metrics.
Last updated: 25 Nov 2025, 23:25 UTC
This page consolidates all known Common Vulnerabilities and Exposures (CVEs) associated with authlib. 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 authlib CVEs: 4
Earliest CVE date: 09 Jun 2024, 19:15 UTC
Latest CVE date: 22 Oct 2025, 22:15 UTC
Latest CVE reference: CVE-2025-62706
30-day Count (Rolling): 0
365-day Count (Rolling): 3
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): 200.0%
Month Growth Rate (30-day Rolling): -100.0%
Year Growth Rate (365-day Rolling): 200.0%
Average CVSS: 0.0
Max CVSS: 0
Critical CVEs (≥9): 0
| Range | Count |
|---|---|
| 0.0-3.9 | 4 |
| 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 authlib, sorted by severity first and recency.
Authlib is a Python library which builds OAuth and OpenID Connect servers. Prior to version 1.6.5, Authlib’s JWE zip=DEF path performs unbounded DEFLATE decompression. A very small ciphertext can expand into tens or hundreds of megabytes on decrypt, allowing an attacker who can supply decryptable tokens to exhaust memory and CPU and cause denial of service. This issue has been patched in version 1.6.5. Workarounds for this issue involve rejecting or stripping zip=DEF for inbound JWEs at the application boundary, forking and add a bounded decompression guard via decompressobj().decompress(data, MAX_SIZE)) and returning an error when output exceeds a safe limit, or enforcing strict maximum token sizes and fail fast on oversized inputs; combine with rate limiting.
Authlib is a Python library which builds OAuth and OpenID Connect servers. Prior to version 1.6.5, Authlib’s JOSE implementation accepts unbounded JWS/JWT header and signature segments. A remote attacker can craft a token whose base64url‑encoded header or signature spans hundreds of megabytes. During verification, Authlib decodes and parses the full input before it is rejected, driving CPU and memory consumption to hostile levels and enabling denial of service. Version 1.6.5 patches the issue. Some temporary workarounds are available. Enforce input size limits before handing tokens to Authlib and/or use application-level throttling to reduce amplification risk.
Authlib is a Python library which builds OAuth and OpenID Connect servers. Prior to version 1.6.4, Authlib’s JWS verification accepts tokens that declare unknown critical header parameters (crit), violating RFC 7515 “must‑understand” semantics. An attacker can craft a signed token with a critical header (for example, bork or cnf) that strict verifiers reject but Authlib accepts. In mixed‑language fleets, this enables split‑brain verification and can lead to policy bypass, replay, or privilege escalation. This issue has been patched in version 1.6.4.
lepture Authlib before 1.3.1 has algorithm confusion with asymmetric public keys. Unless an algorithm is specified in a jwt.decode call, HMAC verification is allowed with any asymmetric public key. (This is similar to CVE-2022-29217 and CVE-2024-33663.)