GHSA-fg6f-75jq-6523
MEDIUMAuthlib has 1-click Account Takeover vulnerability
EPSS Exploitation Probability
EPSS (Exploit Prediction Scoring System) is a daily probability model maintained by FIRST.org. It estimates the likelihood a CVE will be exploited in production environments within the next 30 days, derived from real-world threat intelligence signals.
Blast Radius
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Description
Security Advisory: Cache-Backed State Storage CSRF in Authlib
The Security Labs team at Snyk has reported a security issue affecting Authlib, identified during a recent research project.
The Snyk Security Labs team has identified a vulnerability that can result in a one-click account takeover in applications that utilize the Authlib library.
Description
Cache-backed state/request-token storage is not tied to the initiating user session, making CSRF possible for any attacker that possesses a valid state value (easily obtainable via an attacker-initiated authentication flow). When a cache is supplied to the OAuth client registry, FrameworkIntegration.set_state_data writes the entire state blob under _state_{app}_{state}, and get_state_data disregards the caller's session entirely. [1][2]
def _get_cache_data(self, key):
value = self.cache.get(key)
if not value:
return None
try:
return json.loads(value)
except (TypeError, ValueError):
return None
[snip]
def get_state_data(self, session, state):
key = f"_state_{self.name}_{state}"
if self.cache:
value = self._get_cache_data(key)
else:
value = session.get(key)
if value:
return value.get("data")
return None
authlib/integrations/base_client/framework_integration.py:12-41
Retrieval in authorize_access_token therefore succeeds for whichever browser presents that opaque value, and the token exchange proceeds with the attacker's authorization code. [3]
def authorize_access_token(self, **kwargs):
"""Fetch access token in one step.
:return: A token dict.
"""
params = request.args.to_dict(flat=True)
state = params.get("oauth_token")
if not state:
raise OAuthError(description='Missing "oauth_token" parameter')
data = self.framework.get_state_data(session, state)
if not data:
raise OAuthError(description='Missing "request_token" in temporary data')
params["request_token"] = data["request_token"]
params.update(kwargs)
self.framework.clear_state_data(session, state)
token = self.fetch_access_token(**params)
self.token = token
return token
authlib/integrations/flask_client/apps.py:57-76
This opens up an avenue for Login CSRF in applications that use cache-backed storage. Depending on the dependent application's implementation (e.g., whether it links accounts in the event of a login CSRF), this could lead to account takeover.
Proof of Concept
Consider a hypothetical application — AwesomeAuthlibApp. Assume that AwesomeAuthlibApp contains internal logic such that, when an already authenticated user performs a callback request, the application links the newly provided SSO identity to the existing user account associated with that request.
Under these conditions, an attacker can achieve account takeover within the application by performing the following actions:
- The attacker initiates an SSO OAuth flow but halts the process immediately before the callback request is made to AwesomeAuthlibApp.
- The attacker then induces a logged-in user (via phishing, a drive-by attack, or similar means) to perform a GET request containing the attacker's state value and authorization code to the AwesomeAuthlibApp callback endpoint. Because Authlib does not verify whether the state token is bound to the session performing the callback, the callback is processed, the authorization code is sent to the provider, and the account linking proceeds.
Once the GET request is executed, the attacker's SSO account becomes permanently linked to the victim's AwesomeAuthlibApp account.
Suggested Fix
Per the OAuth RFC [4], the state parameter should be tied to the user's session to prevent exactly such scenarios. One straightforward method of mitigating this issue is to continue storing the state in the session even when caching is enabled.
An alternative approach would be to hash the session ID (or another per-user secret derived from the session) into the cache key. This ensures the state remains stored in the cache while still being bound to the session of the user that initiated the OAuth flow.
Resources
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | authlib | ≥ 1.0.0&&< 1.6.6 | 1.6.6 |
Detection & mitigation playbook
Open-source dependencyDetect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for authlib. O3's reachability analysis confirms whether the vulnerable code path is actually invoked in your application, so you act on real exposure instead of every transitive match.
Fix
Update authlib to 1.6.6 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-fg6f-75jq-6523 is resolved across your whole dependency graph.
Workarounds
If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.
How O3 protects you
O3 pinpoints whether GHSA-fg6f-75jq-6523 is reachable in your code and exactly where to fix it, then blocks exploitation in production at runtime until the patched version is deployed.
Tailored to GHSA-fg6f-75jq-6523. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.
Frequently Asked Questions
Is GHSA-fg6f-75jq-6523 in your dependencies?
O3 detects GHSA-fg6f-75jq-6523 across PyPI dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.