GHSA-r4xg-4wrv-w72h: Duplicate Advisory Lemur Subject To Insecure Random Vulnerability

HIGH
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CVSS 7.5
CWE-330
Published
Advisory Summary

GHSA-r4xg-4wrv-w72h is a HIGH (CVSS 7.5) lemur subject to insecure random vulnerability (CWE-330: Use of Insufficiently Random Values) affecting Duplicate Advisory libraries in the PyPI ecosystem. The issue involves lemur subject to insecure random generation. Remediation is available by upgrading affected packages to version 1.3.2.

GHSA-r4xg-4wrv-w72h at a Glance

CVE Identifier N/A
GHSA Identifier GHSA-r4xg-4wrv-w72h
Severity HIGH
CVSS v3.1 Base Score 7.5
CWE Classification CWE-330: Use of Insufficiently Random Values
Affected Product Duplicate Advisory
Package Ecosystem PyPI
Published Date
Last Updated

Security Impact

CVSS: 7.5

The security impact metrics below are parsed directly from the CVSS v3.1 vector string (CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N).

Attack Vector Network (AV:N)
Attack Complexity Low (AC:L)
Privileges Required None (PR:N)
User Interaction None (UI:N)
Scope Unchanged (S:U)
Confidentiality High (C:H)
Integrity None (I:N)
Availability None (A:N)

How to Fix GHSA-r4xg-4wrv-w72h

To remediate this vulnerability, upgrade all affected Duplicate Advisory dependencies to a patched release. Both direct and transitive dependencies should be checked, as frameworks or security libraries may pull in vulnerable versions transitively.

lemur fixed: 1.3.2 
pip install lemur>=1.3.2
Verify Direct and Transitive Dependencies

Run the following command in your project directory to verify that all resolved dependencies use the patched release: 

pip show lemur

How to Check if You Are Affected

To determine whether your Python environment is affected by GHSA-r4xg-4wrv-w72h, inspect your installed packages using pip:

pip show lemur

Analyze the terminal output to locate any version of Duplicate Advisory in your dependency tree. If any resolved version matches the vulnerable ranges listed in the table below (for example, versions earlier than 1.3.2), your application is affected.

Note: The pip show lemur command checks currently installed packages in your active Python environment.

Technical Details

Vulnerability Mechanism & Technical Analysis

This vulnerability is classified under CWE-330: Use of Insufficiently Random Values, where the product uses insufficiently random numbers or values in a security context that depends on unpredictable numbers. In Duplicate Advisory, software state validation or input boundaries are circumvented during processing. Review the official source advisory statement below for specific affected components, classes, and reproduction details.

Source Advisory Statement

## Duplicate Advisory This advisory has been withdrawn because it is a duplicate of GHSA-5fqv-mpj8-h7gm. This link is maintained to preserve external references. ## Original Description Netflix Lemur before version 1.3.2 used insufficiently random values when generating default credentials. The insufficiently random values may allow an attacker to guess the credentials and gain access to resources managed by Lemur.

GHSA-r4xg-4wrv-w72h Affected Duplicate Advisory Versions

1 component(s)
Fixed Versions:
1.3.2
Product / Package Ecosystem Affected Versions Fixed Version
lemur
pypi/lemur
PyPI
< 1.3.2
1.3.2

References

GitHub Advisory / Wiki ADVISORY
https://github.com/Netflix/lemur/security/advisories/GHSA-5fqv-mpj8-h7gm
NVD — GHSA-r4xg-4wrv-w72h NVD
https://nvd.nist.gov/vuln/detail/CVE-2023-30797
Security Fix Commit FIX COMMIT
https://github.com/Netflix/lemur/commit/666d853212174ee7f4e6f8b3b4b389ede1872238
GitHub Advisory / Wiki ADVISORY
https://github.com/Netflix/security-bulletins/blob/master/advisories/nflx-2023-001.md
vulncheck.com/advisories/netflix-... WEB
https://vulncheck.com/advisories/netflix-lemur-weak-rng

Frequently Asked Questions

What is GHSA-r4xg-4wrv-w72h?
GHSA-r4xg-4wrv-w72h is a security vulnerability in Duplicate Advisory involving Lemur subject to insecure random generation under CWE-330: Use of Insufficiently Random Values.
Which Duplicate Advisory versions are affected?
Affected versions include releases prior to 1.3.2 across affected packages: lemur.
What version fixes GHSA-r4xg-4wrv-w72h?
Upgrading to 1.3.2 (or the latest patched release for your respective branch) resolves the vulnerability.
Is lemur affected?
Yes, lemur is affected in releases prior to 1.3.2. Upgrade your dependency to 1.3.2 or later.
What is the CVSS score of GHSA-r4xg-4wrv-w72h?
GHSA-r4xg-4wrv-w72h has a CVSS v3.1 base score of 7.5 (HIGH) with vector string CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N.
What CWE is associated with GHSA-r4xg-4wrv-w72h?
GHSA-r4xg-4wrv-w72h is classified under CWE-330: Use of Insufficiently Random Values (The product uses insufficiently random numbers or values in a security context that depends on unpredictable numbers.).
How can I check PyPI dependencies for GHSA-r4xg-4wrv-w72h?
Run the dependency tree command: 'pip show lemur'. This command lists direct and transitive dependencies in your build configuration so you can verify if a vulnerable version is resolved.
Machine-readable OSV JSON OSV v1.5 Schema
Normalized schema output
View Raw JSON 
{
  "schema_version" : "1.4.0",
  "id" : "GHSA-r4xg-4wrv-w72h",
  "modified" : "2024-09-30T18:51:02Z",
  "published" : "2023-04-19T21:30:27Z",
  "withdrawn" : "2024-09-30T18:51:02Z",
  "aliases" : [ ],
  "summary" : "Duplicate Advisory: Lemur subject to insecure random generation",
  "details" : "## Duplicate Advisory\nThis advisory has been withdrawn because it is a duplicate of GHSA-5fqv-mpj8-h7gm. This link is maintained to preserve external references.\n\n## Original Description\nNetflix Lemur before version 1.3.2 used insufficiently random values when generating default credentials. The insufficiently random values may allow an attacker to guess the credentials and gain access to resources managed by Lemur.\n\n\n",
  "severity" : [ {
    "type" : "CVSS_V3",
    "score" : "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N"
  } ],
  "affected" : [ {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "lemur"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "0"
      }, {
        "fixed" : "1.3.2"
      } ]
    } ]
  } ],
  "references" : [ {
    "type" : "WEB",
    "url" : "https://github.com/Netflix/lemur/security/advisories/GHSA-5fqv-mpj8-h7gm"
  }, {
    "type" : "ADVISORY",
    "url" : "https://nvd.nist.gov/vuln/detail/CVE-2023-30797"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/Netflix/lemur/commit/666d853212174ee7f4e6f8b3b4b389ede1872238"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/Netflix/security-bulletins/blob/master/advisories/nflx-2023-001.md"
  }, {
    "type" : "WEB",
    "url" : "https://vulncheck.com/advisories/netflix-lemur-weak-rng"
  } ],
  "database_specific" : {
    "cwe_ids" : [ "CWE-330" ],
    "severity" : "HIGH",
    "github_reviewed" : true,
    "github_reviewed_at" : "2024-09-30T18:51:02Z",
    "nvd_published_at" : "2023-04-19T20:15:12Z"
  }
}