Lemur: Use of Insufficiently Random Values
CVE-2023-30797 is a high-severity use of insufficiently random values vulnerability in Lemur from Netflix, with a CVSS 3.1 base score of 7.5 out of 10. It can be exploited remotely over the network by an unauthenticated attacker, without any action from a user. The record lists version 1.3.2 as the first without the flaw, so updating Lemur to that release or later removes the exposure. There is no confirmed exploitation so far. EPSS estimates a 0.79% chance of exploitation within 30 days, higher than 57% of scored CVEs.
High severity with no evidence of exploitation so far.
What to do
- Update Lemur to 1.3.2 or a later version.
- Read the advisory on github.com for workarounds and exact fixed builds.
- Until you can update, restrict network access to the affected service so it is not reachable from untrusted networks.
Affected products and versions
Version data comes from the organisation that assigned the CVE. Confirm against the vendor advisory before deciding you are unaffected.
How the severity score breaks down
- Attack vector
- NetworkCan be exploited remotely over a network, including the internet.
- Attack complexity
- LowNo special conditions are needed; the attack works reliably.
- Privileges required
- NoneNo account or login is needed.
- User interaction
- NoneNo action by a victim is required.
- Scope
- UnchangedImpact stays within the vulnerable component.
- Confidentiality
- HighAll data handled by the component can be read.
- Integrity
- NoneNothing can be modified.
- Availability
- NoneAvailability is not affected.
Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N. Scored by NVD.
| Scoring system | Score | Severity | Scored by |
|---|---|---|---|
| CVSS 3.1 | 7.5 | High | CNA (vulncheck.com) |
| CVSS 3.1 | 7.5 | High | NVD |
| CVSS 3.1 | 7.5 | High | CISA (ADP) |
Official 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.
Source: the CVE record as published by its numbering authority, via NVD and CVE.org.
The underlying weakness: Use of Insufficiently Random Values
The product uses insufficiently random numbers or values in a security context that depends on unpredictable numbers.
How developers prevent this class of flaw
- Use a well-vetted algorithm that is currently considered to be strong by experts in the field, and select well-tested implementations with adequate length seeds. In general, if a pseudo-random number generator is not advertised as being cryptographically secure, then it is probably a statistical PRNG and should not be used in security-sensitive contexts. Pseudo-random number generators can produce predictable numbers if the generator is known and the seed can be guessed. A 256-bit seed is a good starting point for producing a random enough number.
- Consider a PRNG that re-seeds itself as needed from high quality pseudo-random output sources, such as hardware devices.
- Use products or modules that conform to FIPS 140-2 to avoid obvious entropy problems. Consult FIPS 140-2 Annex C (Approved Random Number Generators).
More Use of Insufficiently Random Values vulnerabilities (CWE-330)
Timeline
- CVE record published.
- CISA published its SSVC assessment (exploitation: none, automatable: yes, technical impact: partial).
- Record last changed materially (score, affected products, status or references).
References
Advisories
Patches and release notes
Third-party and government advisories
- vulncheck.com/advisories/netflix-lemur-weak-rngThird Party Advisory
Other vulnerabilities in Lemur
- 7.3 High severity
- 8.1 High severity
- 7.7 High severity
- 7.7 High severity
- 7.4 High severity
- 9.9 Critical severity
Recent Use of Insufficiently Random Values vulnerabilities
- 7.5 High severity
- 7.5 High severity
- 8.8 High severity
- 9.8 Critical severity
- 9.1 Critical severity
- 7.5 High severity
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