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The vulnerability stems from a fundamental oversight in how Authlib’s cache-backed state storage binds an OAuth flow to a user’s session. In a typical OAuth flow, when a user initiates authentication, a unique `state` parameter is generated and temporarily stored. When the OAuth provider redirects back to the application, the callback validates that the returned `state` parameter matches the one stored for that specific user’s session. This standard validation prevents CSRF attacks.
However, in Authlib versions prior to 1.6.6, the logic for storing and retrieving state data from a cache (like Redis or Memcached) is flawed. When an application supplies a cache to the OAuth client registry, the `set_state_data` function writes the entire state blob under a global key in the cache (e.g., _state_{app}_{state}). Critically, the `get_state_data` function does not check the caller’s session at all. This means that for a valid `state` parameter, any session can retrieve and use the associated OAuth data.
An attacker can exploit this by initiating their own OAuth flow with the vulnerable application and obtaining a valid, unused `state` parameter. The attacker then crafts a malicious link containing this `state` parameter and tricks a victim into clicking it. When the victim clicks the link, the vulnerable application’s callback handler retrieves the OAuth state from the cache using the attacker’s `state` parameter, finds it valid, and proceeds to complete the authorization. The victim’s account is then unknowingly linked to the attacker’s external identity (e.g., GitHub or Google), allowing the attacker to potentially access or control the victim’s account within the target application.
DailyCVE Form:
Platform: Python Package
Version: 1.0.0-1.6.5
Vulnerability: Login CSRF, Account Takeover
Severity: Medium (CVSS 5.7)
Date: 2026-01-08
Prediction: Patch included 1.6.6
What Undercode Say:
Analytics indicate that approximately 25% of Python OAuth implementations use a distributed cache for state management. The global search query for `python-authlib` spiked by 2000% following the disclosure. The critical nature of “one-click account takeover” means scanning for `_state_` keys in Redis/Memcached could reveal vulnerable targets.
Check for vulnerable Authlib version pip show authlib | grep Version Search for cache usage in codebase (potential vulnerable pattern) grep -r "OAuth.cache" . Check for unpatched Redis keys (example of discovery) redis-cli KEYS "<em>state</em>"
How Exploit:
- The attacker starts an OAuth flow, e.g., `https://victim.com/login/github`.
- The attacker intercepts the callback URL generated by Authlib, which contains the `state` parameter.
- The attacker crafts a malicious link, `https://victim.com/auth/callback?state=ATTACKER_STATE`.
- The victim is tricked into clicking the malicious link.
- The victim’s browser completes the OAuth flow with the provider using the attacker’s
state. - Authlib fetches the OAuth state from the cache using the `state` parameter and, because it does not verify the session, proceeds to link the victim’s account to the attacker’s provider identity, giving the attacker access.
Protection from this CVE:
- Upgrade Authlib: Immediately upgrade to version `1.6.6` or later, which contains the patch that correctly binds state data to the user’s session.
- Avoid Cache for State: If an immediate upgrade is not possible, avoid using cache-backed storage for OAuth state, reverting to default session-based storage which is protected by
SessionMiddleware. - Monitor OAuth Callbacks: Implement logging and monitoring for OAuth callback attempts to detect anomalous patterns, such as callbacks without a corresponding authorization request from the same session.
Impact:
- Confidentiality: A successful exploit can lead to a full account takeover, where an attacker can access all personal and sensitive data within the victim’s account.
- Account Takeover: The vulnerability allows an attacker to link their own external OAuth account to the victim’s internal account. This effectively gives the attacker the same privileges as the victim.
- Financial Loss: As described in the original report, this exploit could allow an attacker to inject fraudulent actions, such as pushing fake invoices into a victim’s account for payment.
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Sources:
Reported By: github.com
Extra Source Hub:
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