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VulnerabilityPublished Updated

CVE-2024-8999: lunary-ai/lunary · Missing Authorization

Affects lunary-ai/lunarySource CVE Database V5

0

Not known to be exploited · CVSS 9.8 Critical · fixed in 1.4.26 : patch lunary-ai/lunary as a priority.

Data as of 26 Oct 2026, 10:12 UTC

CVSS 3.0 base score
9.8Critical
How severe the flaw is on the 0–10 CVSS scale.
EPSS
0.8% chance of exploitation in 30 days – higher than 56% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
Patch
Available – fixed in 1.4.26
CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 20 Mar 2025

  2. Detectable: no evidence on record.

    No public nuclei template indexed

  3. Weaponised: no evidence on record.

    No public exploit code indexed in Metasploit or Exploit-DB

  4. Exploited in the wild: no evidence on record.

    Not in CISA KEV and no source reports exploitation

  5. Observed by OffSeq Mirage: no evidence on record.

    No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 26 Oct 2026.

What to do

Affected software

ProductAffectedFixed in
GitHublunary-ai/lunarypkg:github/lunary-ai/lunaryOther threatsAffected
  • <=1.4.25
Fixed in–

Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.

AI-suggested

  1. Immediately upgrade all lunary-ai/lunary deployments to version 1.4.26 or later, where the vulnerability is fixed.
  2. Restrict network access to the /api/v1/data-warehouse/bigquery endpoint using firewalls or API gateways to allow only trusted internal systems.
  3. Implement strong authentication and authorization controls on all API endpoints, especially those handling sensitive data exports.
  4. Monitor logs and network traffic for unusual or unauthorized BigQuery export attempts.
  5. Conduct a thorough audit of data access and export activities to detect any prior exploitation.
  6. Employ data loss prevention (DLP) solutions to detect and block unauthorized data exfiltration.
  7. Educate development and operations teams about secure API design and the importance of access control.
  8. If immediate patching is not possible, consider temporarily disabling the vulnerable endpoint or isolating the affected systems from untrusted networks.

Description

lunary-ai/lunary version v1.4.25 contains an improper access control vulnerability in the POST /api/v1/data-warehouse/bigquery endpoint. This vulnerability allows any user to export the entire database data by creating a stream to Google BigQuery without proper authentication or authorization. The issue is fixed in version 1.4.26.

References

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