lunary-ai/lunary: Insufficient Granularity of Access Control
CVE-2024-5389 is a high-severity insufficient granularity of access control vulnerability in lunary-ai/lunary from Lunary-ai, with a CVSS 3.1 base score of 8.1 out of 10. It can be exploited remotely over the network by an attacker with a low-privileged account, without any action from a user. Affected lunary-ai/lunary versions: latest and earlier. The record does not name a fixed version, so check the vendor advisory. There is no confirmed exploitation so far. EPSS estimates a 0.43% chance of exploitation within 30 days, which is low compared with other CVEs.
High severity with no evidence of exploitation so far.
What to do
- Check which version of lunary-ai/lunary you run against the affected versions below, and install the vendor's latest release.
Affected products and versions
| Vendor | Product | Affected versions | Fixed in |
|---|---|---|---|
| Lunary-ai | lunary-ai/lunary | latest and earlier | Not stated |
| Lunary-ai | lunary | 1.2.13 | Not stated |
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
- LowA basic user account is enough.
- 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
- HighData or code can be modified at will.
- Availability
- NoneAvailability is not affected.
Vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:N. Scored by NVD.
| Scoring system | Score | Severity | Scored by |
|---|---|---|---|
| CVSS 3.1 | 8.1 | High | NVD |
| CVSS 3.0 | 5.7 | Medium | CNA (huntr.dev) |
Official description
In lunary-ai/lunary version 1.2.13, an insufficient granularity of access control vulnerability allows users to create, update, get, and delete prompt variations for datasets not owned by their organization. This issue arises due to the application not properly validating the ownership of dataset prompts and their variations against the organization or project of the requesting user. As a result, unauthorized modifications to dataset prompts can occur, leading to altered or removed dataset prompts without proper authorization. This vulnerability impacts the integrity and consistency of dataset information, potentially affecting the results of experiments.
Source: the CVE record as published by its numbering authority, via NVD and CVE.org.
The underlying weakness: Insufficient Granularity of Access Control
The product implements access controls via a policy or other feature with the intention to disable or restrict accesses (reads and/or writes) to assets in a system from untrusted agents. However, implemented access controls lack the required granularity
How developers prevent this class of flaw
- Access-control-policy protections must be reviewed for design inconsistency and common weaknesses. Access-control-policy definition and programming flow must be tested in pre-silicon, post-silicon testing.
More Insufficient Granularity of Access Control vulnerabilities (CWE-1220)
Timeline
- CVE record published.
- CISA published its SSVC assessment (exploitation: poc, automatable: no, technical impact: partial).
- Record last changed materially (score, affected products, status or references).
References
Technical write-ups (may include proof of concept)
- huntr.com/bounties/3ca5309f-5615-4d5b-8043-968af220d7a2Exploit, Third Party Advisory
Other vulnerabilities in lunary-ai/lunary
- 8.8 High severity
- 8.8 High severity
- 9.6 Critical severity
- 7.7 High severity
- 8.1 High severity
- 7.1 High severity
Recent Insufficient Granularity of Access Control vulnerabilities
- 9.8 Critical severity
- 7.8 High severity
- 7.7 High severity
- 7.7 High severity
- 8.8 High severity
Spotted an error? Tell us.