Home/CVE/Jupyter Server Proxy is a Jupyter notebook server extension to proxy web services. Versions of Jupyter Server Proxy prio
CVE
CVE-2022-21697
Jupyter Server Proxy is a Jupyter notebook server extension to proxy web services. Versions of Jupyter Server Proxy prio
Jupyter Server Proxy is a Jupyter notebook server extension to proxy web services. Versions of Jupyter Server Proxy prior to 3.2.1 are vulnerable to Server-Side Request Forgery (SSRF). Any user deploying Jupyter Server or Notebook with jupyter-proxy-server extension enabled is affected.
A lack of input validation allows authenticated clients to proxy requests to other hosts, bypassing the allowed_hosts check. Because authentication is required, which already grants permissions to make the same requests via kernel or terminal execution, this is considered low to moderate severity. Users may upgrade to version 3.2.1 to receive a patch or, as a workaround, install the patch manually.
MEDIUM · CVSS 6.3
EPSS 0.00365
Monitor
- No active-exploitation, high-EPSS, or public-exploit signals - routine patching cadence
Sigma rules0
YARA rules0
Look this up elsewhere - one-click external pivots
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How to read a CVE - triage first, then detect and patch
This page is every public fact about CVE-2022-21697, cross-linked. Its job is to answer one question fast - does this need my attention now? - and then hand you the two things you do about it. Here is how an analyst reads it.
Triage: should I act now? Four signals, and they are not interchangeable:
CVSSseverity - how bad it is IF exploited, 0-10. A high CVSS alone is not urgency; a flaw can be a perfect 10 and never actually be attacked.
EPSSprobability - a model’s estimate of the chance it is exploited in the next 30 days, 0-1. This is the “will it actually happen” signal.
CISA KEVconfirmed - it is being exploited in the wild right now. The strongest signal on the page; KEV beats any score.
Weaponisedavailability - public exploits / PoCs, and especially Metasploit modules rated Excellent / Great. Reliable, packaged exploit code means low-skill attackers can use it today.
How they combine: KEV, or a dependable Metasploit module, means patch now regardless of CVSS. High CVSS + low EPSS + no exploit is real but not an emergency - schedule it. Low CVSS but KEV-listed still gets patched now. The verdict above already weighed these for you; this is how it got there.
Then what - two workflows:
Detectwhen you cannot patch today, follow this CVE to the ATT&CK techniques it enables, then Build a SIEM detection (the green button) - author a rule, test it in Atomic, deploy it. That buys visibility while the patch waits.
PatchAffected products / packages tell you if you are exposed; Fixed versions by distribution and Vendor advisories give the exact version that closes it.
Reading order for the panels below: verdict + badges, then Public exploits / Metasploit (is it weaponised), then ATT&CK techniques + Sigma / IDS rules (can I detect it), then Affected products / packages + Fixed versions (am I exposed, what patches it), then Threat actors / IOCs (who uses it), then Scoring & timeline / references (the evidence).
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ATT&CK techniques
1Techniques this CVE enables - linked via CWECAPECATT&CK. High◆ = named directly in ATT&CK or Nuclei templates.
▤ Build a SIEM detection for these techniques▤
CAPEC attack patterns
1Attack patterns this CVE enables - the bridge from weakness to ATT&CK technique.
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Weakness Classification
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Affected Products & Versions
1jupyter server proxy< 3.2.1
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Affected Packages
1Language-ecosystem packages (from OSV) tied to this CVE, with the version that fixes it - the dependency-level detail NVD doesn’t carry.
PyPI
jupyter-server-proxy
MODERATE
fixed in 3.2.1
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Scoring & Timeline
6.3
MEDIUM · CVSS v3.1 · [email protected]
Attack Vector
Network
Adjacent
Local
Physical
Attack Complexity
Low
High
Privileges Required
None
Low
High
User Interaction
None
Required
Scope
Unchanged
Changed
Confidentiality
None
Low
High
Integrity
None
Low
High
Availability
None
Low
High
SSVC triage · cisa-vulnrichment
Exploitation
none
Automatable
no
Technical impact
partial
SSVC asks the questions that actually drive patch urgency: is it being exploited, can attacks be automated, and how total is the impact.
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References & Sources
3Source URLs (vendor pages, mailing lists, write-ups). Exploit/PoC links are in their own section above to avoid duplication.
https://github.com/jupyterhub/jupyter-server-proxy/commit/fd31930bacd12188c448c886e0783529436b99ebPatchThird Party Advisory
https://github.com/jupyterhub/jupyter-server-proxy/compare/v3.2.0...v3.2.1.patchPatchThird Party Advisory