sagemathinc cocalc Markdown Parser cross site scripting
| CVSS Meta Temp Score | Current Exploit Price (≈) | CTI Interest Score |
|---|---|---|
| 5.5 | $0-$5k | 0.00 |
Summary
A vulnerability marked as problematic has been reported in sagemathinc cocalc. The affected element is an unknown function of the component Markdown Parser. The manipulation leads to cross site scripting. This vulnerability is traded as CVE-2024-36109. It is possible to initiate the attack remotely. There is no exploit available. To fix this issue, it is recommended to deploy a patch.
Details
A vulnerability was found in sagemathinc cocalc (the affected version is unknown) and classified as problematic. This issue affects an unknown code of the component Markdown Parser. The manipulation with an unknown input leads to a cross site scripting vulnerability. Using CWE to declare the problem leads to CWE-79. The product does not neutralize or incorrectly neutralizes user-controllable input before it is placed in output that is used as a web page that is served to other users. Impacted is integrity. The summary by CVE is:
CoCalc is web-based software that enables collaboration in research, teaching, and scientific publishing. In affected versions the markdown parser allows `` tags to be included which execute when published. This issue has been addressed in commit `419862a9c9879c`. Users are advised to upgrade. There are no known workarounds for this vulnerability.
It is possible to read the advisory at github.com. The identification of this vulnerability is CVE-2024-36109 since 05/20/2024. The exploitation is known to be easy. The attack may be initiated remotely. It demands that the victim is doing some kind of user interaction. The technical details are unknown and an exploit is not publicly available. The attack technique deployed by this issue is T1059.007 according to MITRE ATT&CK.
Applying a patch is able to eliminate this problem. The bugfix is ready for download at github.com.
Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.
Product
Vendor
Name
License
Website
CPE 2.3
CPE 2.2
CVSSv4
VulDB Vector: 🔍VulDB Reliability: 🔍
CVSSv3
VulDB Meta Base Score: 5.5VulDB Meta Temp Score: 5.5
VulDB Base Score: 3.5
VulDB Temp Score: 3.4
VulDB Vector: 🔍
VulDB Reliability: 🔍
CNA Base Score: 7.6
CNA Vector (GitHub, Inc.): 🔍
CVSSv2
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VulDB Base Score: 🔍
VulDB Temp Score: 🔍
VulDB Reliability: 🔍
Exploiting
Class: Cross site scriptingCWE: CWE-79 / CWE-94 / CWE-74
CAPEC: 🔍
ATT&CK: 🔍
Physical: No
Local: No
Remote: Yes
Availability: 🔍
Status: Not defined
EPSS Score: 🔍
EPSS Percentile: 🔍
Price Prediction: 🔍
Current Price Estimation: 🔍
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Threat Intelligence
Interest: 🔍Active Actors: 🔍
Active APT Groups: 🔍
Countermeasures
Recommended: PatchStatus: 🔍
0-Day Time: 🔍
Patch: github.com
Timeline
05/20/2024 🔍05/28/2024 🔍
05/28/2024 🔍
03/27/2025 🔍
Sources
Product: github.comAdvisory: GHSA-8w44-hggw-p5rf
Status: Confirmed
CVE: CVE-2024-36109 (🔍)
GCVE (CVE): GCVE-0-2024-36109
GCVE (VulDB): GCVE-100-266459
Entry
Created: 05/28/2024 21:48Updated: 03/27/2025 15:04
Changes: 05/28/2024 21:48 (64), 03/27/2025 15:04 (4)
Complete: 🔍
Cache ID: 216::103
Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.
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