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Security Advisories: MDE2OlNlY3VyaXR5QWR2aXNvcnlHSFNBLXY3bTktOTQ5Ny1wOWdy
Possible pod name collisions in jupyterhub-kubespawner
Impact
What kind of vulnerability is it? Who is impacted?
JupyterHub deployments using:
- KubeSpawner <= 0.11.1 (e.g. zero-to-jupyterhub 0.9.0) and
- enabled named_servers (not default), and
- an Authenticator that allows:
- usernames with hyphens or other characters that require escape (e.g.
user-hyphen
oruser@email
), and - usernames which may match other usernames up to but not including the escaped character (e.g.
user
in the above cases)
- usernames with hyphens or other characters that require escape (e.g.
In this circumstance, certain usernames will be able to craft particular server names which will grant them access to the default server of other users who have matching usernames.
Patches
Has the problem been patched? What versions should users upgrade to?
Patch will be released in kubespawner 0.12 and zero-to-jupyterhub 0.9.1
Workarounds
Is there a way for users to fix or remediate the vulnerability without upgrading?
KubeSpawner
Specify configuration:
for KubeSpawner
from traitlets import default
from kubespawner import KubeSpawner
class PatchedKubeSpawner(KubeSpawner):
@default("pod_name_template")
def _default_pod_name_template(self):
if self.name:
return "jupyter-{username}-{servername}"
else:
return "jupyter-{username}"
@default("pvc_name_template")
def _default_pvc_name_template(self):
if self.name:
return "claim-{username}-{servername}"
else:
return "claim-{username}"
c.JupyterHub.spawner_class = PatchedKubeSpawner
Note for KubeSpawner: this configuration will behave differently before and after the upgrade, so will need to be removed when upgrading. Only apply this configuration while still using KubeSpawner ≤ 0.11.1 and remove it after upgrade to ensure consistent pod and pvc naming.
Changing the name template means pvcs for named servers will have different names. This will result in orphaned PVCs for named servers across Hub upgrade! This may appear as data loss for users, depending on configuration, but the orphaned PVCs will still be around and data can be migrated manually (or new PVCs created manually to reference existing PVs) before deleting the old PVCs and/or PVs.
References
Are there any links users can visit to find out more?
For more information
If you have any questions or comments about this advisory:
- Open an issue in kubespawner
- Email us at [email protected]
Credit: Jining Huang
Permalink: https://github.com/advisories/GHSA-v7m9-9497-p9grJSON: https://advisories.ecosyste.ms/api/v1/advisories/MDE2OlNlY3VyaXR5QWR2aXNvcnlHSFNBLXY3bTktOTQ5Ny1wOWdy
Source: GitHub Advisory Database
Origin: Unspecified
Severity: High
Classification: General
Published: over 4 years ago
Updated: 4 months ago
CVSS Score: 6.8
CVSS vector: CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:H/I:H/A:N
EPSS Percentage: 0.00153
EPSS Percentile: 0.51947
Identifiers: GHSA-v7m9-9497-p9gr, CVE-2020-15110
References:
- https://github.com/jupyterhub/kubespawner/security/advisories/GHSA-v7m9-9497-p9gr
- https://github.com/jupyterhub/kubespawner/commit/3dfe870a7f5e98e2e398b01996ca6b8eff4bb1d0
- https://nvd.nist.gov/vuln/detail/CVE-2020-15110
- https://github.com/pypa/advisory-database/tree/main/vulns/jupyterhub-kubespawner/PYSEC-2020-51.yaml
- https://github.com/advisories/GHSA-v7m9-9497-p9gr
Blast Radius: 11.9
Affected Packages
pypi:jupyterhub-kubespawner
Dependent packages: 2Dependent repositories: 57
Downloads: 13,202 last month
Affected Version Ranges: <= 0.11.1
Fixed in: 0.12.0
All affected versions: 0.5.1, 0.6.0, 0.7.1, 0.8.1, 0.9.0, 0.10.0, 0.10.1, 0.11.0, 0.11.1
All unaffected versions: 0.12.0, 0.13.0, 0.14.0, 0.14.1, 0.15.0, 0.16.0, 0.16.1, 1.0.0, 1.1.0, 1.1.1, 1.1.2, 2.0.0, 2.0.1, 3.0.0, 3.0.1, 3.0.2, 4.0.0, 4.1.0, 4.2.0, 4.3.0, 5.0.0, 6.0.0, 6.1.0, 6.2.0, 7.0.0