CVE-2026-23996 (GCVE-0-2026-23996)
Vulnerability from cvelistv5 – Published: 2026-01-21 22:29 – Updated: 2026-01-22 16:49
VLAI
EPSS
VEX
Title
FastAPI Api Key has a timing side-channel in verify_key that allows statistical key validity detection
Summary
FastAPI Api Key provides a backend-agnostic library that provides an API key system. Version 1.1.0 has a timing side-channel vulnerability in verify_key(). The method applied a random delay only on verification failures, allowing an attacker to statistically distinguish valid from invalid API keys by measuring response latencies. With enough repeated requests, an adversary could infer whether a key_id corresponds to a valid key, potentially accelerating brute-force or enumeration attacks. All users relying on verify_key() for API key authentication prior to the fix are affected. Users should upgrade to version 1.1.0 to receive a patch. The patch applies a uniform random delay (min_delay to max_delay) to all responses regardless of outcome, eliminating the timing correlation. Some workarounds are available. Add an application-level fixed delay or random jitter to all authentication responses (success and failure) before the fix is applied and/or use rate limiting to reduce the feasibility of statistical timing attacks.
Severity
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-01-22 15:09 UTC
CWE
- CWE-208 - Observable Timing Discrepancy
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://github.com/Athroniaeth/fastapi-api-key/se… | x_refsource_CONFIRM |
| https://github.com/Athroniaeth/fastapi-api-key/co… | x_refsource_MISC |
| https://github.com/Athroniaeth/fastapi-api-key/re… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Athroniaeth | fastapi-api-key |
Affected:
< 1.1.0
|
guessed |
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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