GHSA-j5pr-vrjj-9v4h

Suggest an improvement
Source
https://github.com/advisories/GHSA-j5pr-vrjj-9v4h
Import Source
https://github.com/github/advisory-database/blob/main/advisories/github-reviewed/2025/07/GHSA-j5pr-vrjj-9v4h/GHSA-j5pr-vrjj-9v4h.json
JSON Data
https://api.test.osv.dev/v1/vulns/GHSA-j5pr-vrjj-9v4h
Aliases
Published
2025-07-07T12:30:23Z
Modified
2025-07-08T19:27:19.772095Z
Severity
  • 7.5 (High) CVSS_V3 - CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N CVSS Calculator
Summary
Lord of Large Language Models vulnerable to Observable Discrepancy attack via authenticate_user function
Details

The parisneo/lollms repository is affected by a timing attack vulnerability in the authenticate_user function within the lollms_authentication.py file. This vulnerability allows attackers to enumerate valid usernames and guess passwords incrementally by analyzing response time differences. The affected version is the latest, and the issue is resolved in commit f78437f. The vulnerability arises from the use of Python's default string equality operator for password comparison, which compares characters sequentially and exits on the first mismatch, leading to variable response times based on the number of matching initial characters.

Database specific
{
    "github_reviewed": true,
    "github_reviewed_at": "2025-07-08T18:44:08Z",
    "cwe_ids": [
        "CWE-203"
    ],
    "nvd_published_at": "2025-07-07T10:15:29Z",
    "severity": "HIGH"
}
References

Affected packages

PyPI / lollms

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
0Unknown introduced version / All previous versions are affected
Last affected
11.0.0

Affected versions

1.*

1.1.3
1.1.5
1.1.6
1.1.7
1.1.9
1.1.10
1.1.11
1.1.12
1.1.13
1.1.14
1.1.15
1.1.16
1.1.17
1.1.18
1.1.19
1.1.20
1.1.21
1.1.22
1.1.25
1.1.26
1.1.27
1.1.28
1.1.29
1.1.30
1.1.31
1.1.32
1.1.33
1.1.34
1.1.35
1.1.36
1.1.37
1.1.38
1.1.45
1.1.46
1.1.47
1.1.48
1.1.49
1.1.50
1.1.51
1.1.52
1.1.53
1.1.55
1.1.56
1.1.57
1.1.58
1.1.59
1.1.60
1.1.61
1.1.62
1.1.63
1.1.64
1.1.65
1.1.66
1.1.67
1.1.68
1.1.69
1.1.70
1.1.71
1.1.73
1.1.74
1.1.75
1.1.76
1.1.77
1.1.78
1.1.79
1.1.80
1.1.82
1.1.83
1.1.84
1.1.85
1.1.86
1.1.90
1.1.91
1.1.92
1.2.0
1.2.1
1.2.3
1.2.4
1.2.6
1.2.7
1.2.8
1.2.9
1.2.10
1.2.11
1.2.12
1.2.14

2.*

2.0.0
2.0.1
2.0.2
2.0.3
2.0.4
2.0.5
2.0.6
2.0.8
2.0.9
2.0.10
2.0.11
2.0.12
2.0.13
2.0.14
2.0.15
2.0.16
2.0.17
2.0.18
2.0.19
2.0.20
2.0.21
2.0.22
2.0.23
2.0.24
2.0.25
2.0.26
2.0.27
2.0.28
2.0.30
2.0.31
2.0.32
2.1.0
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5
2.1.6
2.1.7
2.1.8
2.1.9
2.1.10
2.1.11
2.1.12
2.1.13
2.1.14
2.1.15
2.1.16
2.1.17
2.1.18
2.1.19
2.1.20
2.1.21
2.1.22
2.1.23
2.1.24
2.1.25
2.1.26
2.1.27
2.1.28
2.1.29
2.1.30
2.1.31
2.1.32
2.1.34
2.1.35
2.1.36
2.1.37
2.1.38
2.1.39
2.1.40
2.1.42
2.1.43
2.1.44
2.1.45
2.1.46
2.1.47
2.1.48
2.1.49
2.1.50
2.1.51
2.1.53
2.1.54
2.1.55
2.1.56
2.1.59
2.1.60
2.2.0
2.2.1
2.2.2
2.2.3
2.2.4
2.2.5
2.2.6
2.2.7
2.2.8
2.3.0
2.3.1
2.3.3
2.3.4

3.*

3.0.0
3.1.0
3.1.5
3.2.0

4.*

4.0.0
4.0.1
4.0.2
4.1.0
4.1.5
4.1.6
4.2.0
4.2.1
4.2.2
4.5.0
4.5.1
4.5.2
4.5.3

5.*

5.0.0
5.0.1
5.0.2
5.1.0
5.1.1
5.2.0
5.2.1
5.3.0
5.3.1
5.5.0
5.5.1
5.5.2
5.5.3
5.5.4
5.5.5
5.5.6
5.6.0
5.6.2
5.7.0
5.7.1
5.7.2
5.7.3
5.7.5
5.7.6
5.7.7
5.7.8
5.7.9
5.8.1
5.8.2
5.8.3
5.8.5
5.8.6
5.8.7
5.8.8
5.9.0
5.9.1
5.9.2
5.9.3
5.9.4
5.9.5

6.*

6.0.0
6.0.1
6.0.2
6.0.3
6.0.5
6.0.6
6.0.7
6.0.8
6.0.9
6.1.1
6.2.0
6.4.0
6.5.0
6.5.1
6.5.2
6.6.0
6.7.0
6.9.0

7.*

7.2.0

9.*

9.3.0
9.5.0
9.5.1

11.*

11.0.0