JupyterLab Desktop: TCC Bypass via Insecure Entitlements (macOS)
Severity and exploitation
KEV coverage does not rule out exploitation.
Assessment vector
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:NSeverity
medium5.5CVSS measures technical severity, not the likelihood of an attack.
Known exploitation
Not listed in the checked CISA KEV catalog
Absence from CISA KEV does not rule out attacks.
Public exploit
Not established by this record
Missing evidence does not mean no public exploit exists.
Remediation
Fix status not established
No structured fix or guidance is available here. Check the latest publisher advisory.
What this means
JupyterLab Desktop for macOS, prior to 4.6.2-1, has insecure entitlements, allowing an attacker with local code execution to load arbitrary dynamic libraries and inherit TCC permissions. The attacker must already have code execution and prior TCC grants. This affects JupyterLab Desktop versions less than 4.6.2-1.
Summarized by @cf/meta/llama-3.3-70b-instruct-fp8-fast. Verify details against the original sources.Attack conditions
Exploitation requires existing local code execution and prior TCC grants; it does not provide initial or remote code execution.
Excerpt from the original source description below.
Review supporting sources →Affected versions
Check the exact model, release, and any platform requirements against your installation.
jupyterlab · GitHub_M
jupyterlab-desktop
1 range
jupyterlab · GitHub_M
jupyterlab-desktop
Compare with this publisher’s ranges. This does not inspect your installation.
affected
< 4.6.2-1
Other versions: unknown
What to do
Compare your installed product and version with the affected versions above. A matching product name alone does not confirm exposure.
No structured fix or remediation guidance is available here. Check the full source description and vendor’s latest advisory for a patch or workaround; do not assume another version is safe.
cve.new guidance unless attributed to a publisher. This page does not inspect your installation.
Public exploit evidence
No public exploit reference is identified in the imported evidence. This is not a claim that no exploit exists.
Original source description
Read the full publisher description
JupyterLab Desktop is the cross-platform desktop application for JupyterLab. Prior to 4.6.2-1, JupyterLab Desktop for macOS declared the com.apple.security.cs.allow-dyld-environment-variables entitlement, allowing the dynamic linker to honor DYLD_INSERT_LIBRARIES despite the hardened runtime. An attacker who can already execute code as the current user can load an arbitrary dynamic library into the JupyterLab Desktop process and inherit TCC permissions previously granted to the application, including access to protected Documents, Desktop, or Downloads folders without another macOS prompt. Exploitation requires existing local code execution and prior TCC grants; it does not provide initial or remote code execution. Windows and Linux are not affected. This vulnerability is fixed in 4.6.2-1.
References
3 sourcesInside the record
Evidence available
Describes the evidence in this view, not whether the product is safe.
Original records
CVE-2025-54991View the latest unmodified CVE JSON from the official source. It may be newer than this imported page.
cve.new JSON →Underlying weaknesses
The source’s classification of what caused the vulnerability.
Contributing organizations · 2
Assigning organization
Additional data publisher
Timeline
All times UTCAdvisory published
Publication date supplied by the source.
Source updated
Latest modification date supplied by the source.
Last imported by cve.new
Latest catalog import, not the date we first saw this advisory.
What changed
Follow changes- CVE · CVE-2025-54991
Observed 2026-11-09T13:36:05.355Z · upstream updated 2026-11-09T13:22:31.447Z
Prioritization updated
before
[]
after
[ { "source": "CISA-ADP", "type": "SSVC", "role": "CISA Coordinator", "timestamp": "2026-11-09T13:22:20.769074Z", "decisions": [ { "name": "Exploitation", "value": "none" }, { "name": "Automatable", "value": "no" }, { "name": "Technical Impact", "value": "partial" } ] } ]
Large field values are marked as truncated previews. Original source snapshots remain retained.
Showing up to 50 most recent observed changes.