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Open redirection vulnerability in `next` query parameter

Moderate
Yann-P published GHSA-qh7q-6qm3-653w May 5, 2026

Package

pip jupyter_server (pip)

Affected versions

<=2.17.0

Patched versions

2.18.0

Description

Summary

The ?next=... URL query parameter has an open redirection vulnerability. In jupyter_server<=2.17.0, this URL query parameter allows redirection to arbitrary external domains, which can be exploited to facilitate phishing attacks on server users.

Details

The vulnerability is caused by insufficient validation in the LoginFormHandler._redirect_safe() method.

  • Source code reference:

    jupyter_server/jupyter_server/auth/login.py

    Lines 33 to 76 in 987ebdd

    def _redirect_safe(self, url, default=None):
    """Redirect if url is on our PATH
    Full-domain redirects are allowed if they pass our CORS origin checks.
    Otherwise use default (self.base_url if unspecified).
    """
    if default is None:
    default = self.base_url
    # protect chrome users from mishandling unescaped backslashes.
    # \ is not valid in urls, but some browsers treat it as /
    # instead of %5C, causing `\\` to behave as `//`
    url = url.replace("\\", "%5C")
    # urllib and browsers interpret extra '/' in the scheme separator (`scheme:///host/path`)
    # differently.
    # urllib gives scheme=scheme, netloc='', path='/host/path', while
    # browsers get scheme=scheme, netloc='host', path='/path'
    # so make sure ':///*' collapses to '://' by splitting and stripping any additional leading slash
    # don't allow any kind of `:/` shenanigans by splitting on ':' only
    # and replacing `:/*` with exactly `://`
    if ":" in url:
    scheme, _, rest = url.partition(":")
    url = f"{scheme}://{rest.lstrip('/')}"
    parsed = urlparse(url)
    # full url may be `//host/path` (empty scheme == same scheme as request)
    # or `https://host/path`
    # or even `https:///host/path` (invalid, but accepted and ambiguously interpreted)
    if (parsed.scheme or parsed.netloc) or not (parsed.path + "/").startswith(self.base_url):
    # require that next_url be absolute path within our path
    allow = False
    # OR pass our cross-origin check
    if parsed.scheme or parsed.netloc:
    # if full URL, run our cross-origin check:
    origin = f"{parsed.scheme}://{parsed.netloc}"
    origin = origin.lower()
    if self.allow_origin:
    allow = self.allow_origin == origin
    elif self.allow_origin_pat:
    allow = bool(re.match(self.allow_origin_pat, origin))
    if not allow:
    # not allowed, use default
    self.log.warning("Not allowing login redirect to %r" % url)
    url = default
    self.redirect(url)

This vulnerability was originally reported by Noriaki Iwasaki. All discovery credit goes to them.

PoC

  1. Navigate to http://localhost:8888/login?next=///google.com
  2. Observe that the user is redirected to google.com despite it being an external domain.

The external domain passed in the ?next parameter may be replaced with a malicious lookalike to facilitate phishing attacks. Jupyter Server deployments served on a public domain are especially vulnerable, as prod.company.com may be redirected to a look-alike URL such as prod.company.dev.

Impact

This vulnerability affects all users, especially enterprise users who work with sensitive/confidential data.

Patches

Jupyter Server 2.18+

Workaround

None.

Severity

Moderate

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v4 base metrics

Exploitability Metrics
Attack Vector Local
Attack Complexity Low
Attack Requirements None
Privileges Required None
User interaction Passive
Vulnerable System Impact Metrics
Confidentiality None
Integrity None
Availability None
Subsequent System Impact Metrics
Confidentiality High
Integrity None
Availability None

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
User interaction: This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:L/AC:L/AT:N/PR:N/UI:P/VC:N/VI:N/VA:N/SC:H/SI:N/SA:N

CVE ID

CVE-2025-61669

Weaknesses

URL Redirection to Untrusted Site ('Open Redirect')

The web application accepts a user-controlled input that specifies a link to an external site, and uses that link in a redirect. Learn more on MITRE.

Credits