CVE-2026-10595
Path Traversal Vulnerability in parisneo/lollms
Description
A path traversal vulnerability exists in parisneo/lollms version 2.1.0, specifically in the SPA catch-all route implemented in `backend/routers/ui.py`. The vulnerability arises from the improper handling of user-controlled path input, which is directly joined into a filesystem path without sanitization or containment checks. URL-encoded dot-dot sequences (`%2e%2e`) bypass Starlette's built-in path normalization and are resolved by Python's `pathlib`, allowing an unauthenticated attacker to read arbitrary files on the server. This issue has been resolved in version 3.
INFO
Published Date :
Aug. 9, 2026, 4:17 a.m.
Last Modified :
Aug. 9, 2026, 4:17 a.m.
Remotely Exploit :
Yes !
Source :
[email protected]
Affected Products
The following products are affected by CVE-2026-10595
vulnerability.
Even if cvefeed.io is aware of the exact versions of the
products
that
are
affected, the information is not represented in the table below.
No affected product recoded yet
CVSS Scores
| Score | Version | Severity | Vector | Exploitability Score | Impact Score | Source |
|---|---|---|---|---|---|---|
| CVSS 3.0 | HIGH | [email protected] |
Solution
- Update parisneo/lollms to version 3 or later.
- Apply vendor-provided patches for the UI route handler.
- Sanitize user-controlled path input before use.
- Implement containment checks for filesystem paths.
References to Advisories, Solutions, and Tools
Here, you will find a curated list of external links that provide in-depth
information, practical solutions, and valuable tools related to
CVE-2026-10595.
| URL | Resource |
|---|---|
| https://github.com/parisneo/lollms/commit/9bc6431ae7b708da76d51e7626a7cf48ff2b1d24 | |
| https://huntr.com/bounties/af3f40a3-38a1-49d8-a5ae-3d72b9b05b98 |
CWE - Common Weakness Enumeration
While CVE identifies
specific instances of vulnerabilities, CWE categorizes the common flaws or
weaknesses that can lead to vulnerabilities. CVE-2026-10595 is
associated with the following CWEs:
Common Attack Pattern Enumeration and Classification (CAPEC)
Common Attack Pattern Enumeration and Classification
(CAPEC)
stores attack patterns, which are descriptions of the common attributes and
approaches employed by adversaries to exploit the CVE-2026-10595
weaknesses.
We scan GitHub repositories to detect new proof-of-concept exploits. Following list is a collection of public exploits and proof-of-concepts, which have been published on GitHub (sorted by the most recently updated).
Results are limited to the first 15 repositories due to potential performance issues.
The following list is the news that have been mention
CVE-2026-10595 vulnerability anywhere in the article.
The following table lists the changes that have been made to the
CVE-2026-10595 vulnerability over time.
Vulnerability history details can be useful for understanding the evolution of a vulnerability, and for identifying the most recent changes that may impact the vulnerability's severity, exploitability, or other characteristics.
-
New CVE Received by [email protected]
Aug. 09, 2026
Action Type Old Value New Value Added Affected [{'vendor': 'parisneo', 'product': 'parisneo/lollms', 'versions': [{'status': 'affected', 'version': 'unspecified', 'lessThan': '3', 'versionType': 'custom'}]}] Added Description A path traversal vulnerability exists in parisneo/lollms version 2.1.0, specifically in the SPA catch-all route implemented in `backend/routers/ui.py`. The vulnerability arises from the improper handling of user-controlled path input, which is directly joined into a filesystem path without sanitization or containment checks. URL-encoded dot-dot sequences (`%2e%2e`) bypass Starlette's built-in path normalization and are resolved by Python's `pathlib`, allowing an unauthenticated attacker to read arbitrary files on the server. This issue has been resolved in version 3. Added CVSS V3 AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N Added CWE CWE-23 Added Reference https://github.com/parisneo/lollms/commit/9bc6431ae7b708da76d51e7626a7cf48ff2b1d24 Added Reference https://huntr.com/bounties/af3f40a3-38a1-49d8-a5ae-3d72b9b05b98