yeti: Improper Neutralization of Special Elements in Data Query Logic
CVE-2026-63489 is a high-severity improper neutralization of special elements in data query logic vulnerability in yeti from Yeti-platform, with a CVSS 3.1 base score of 7.6 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 yeti versions: <= 2.5.0. The record does not name a fixed version, so check the vendor advisory. There is no confirmed exploitation so far. EPSS estimates a 0.26% 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 yeti you run against the affected versions below, and install the vendor's latest release.
- Read the advisory on github.com for workarounds and exact fixed builds.
Affected products and versions
| Vendor | Product | Affected versions | Fixed in |
|---|---|---|---|
| Yeti-platform | yeti | <= 2.5.0 | 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
- LowLimited modification of data is possible.
- Availability
- LowPerformance or availability is reduced.
Vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:L. Scored by CNA (github.com).
Official description
Yeti bridges the gap between CTI and DFIR practitioners by providing a Forensics Intelligence platform and pipeline. In version 2.5.0 and earlier, YETI directly interpolates user-controlled sorting fields and filter_aliases attribute paths into ArangoDB AQL identifier and expression positions in core/database_arango.py. A low-privileged authenticated user can send crafted values to POST /api/v2/observables/search, POST /api/v2/entities/search, POST /api/v2/indicators/search, POST /api/v2/dfiq/search, POST /api/v2/search/, or POST /api/v2/graph/search, causing attacker-controlled AQL subexpressions to be parsed and evaluated. This can provide an error oracle, evaluate expressions against internal collections such as users, alter intended search logic, enumerate schema information, and consume excessive database resources. The verified injection points are read and search contexts, so arbitrary database writes are not established. No fixed version is available as of this review.
Source: the CVE record as published by its numbering authority, via NVD and CVE.org.
The underlying weakness: Improper Neutralization of Special Elements in Data Query Logic
The product generates a query intended to access or manipulate data in a data store such as a database, but it does not neutralize or incorrectly neutralizes special elements that can modify the intended logic of the query.
More Improper Neutralization of Special Elements in Data Query Logic vulnerabilities (CWE-943)
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
Patches and release notes
Other vulnerabilities in yeti
- 8.3 High severity
- 7.1 High severity
- 7.5 High severity
- 8.1 High severity
- 7.5 High severity
- 7.3 High severity
Recent Improper Neutralization of Special Elements in Data Query Logic vulnerabilities
- 9.8 Critical severity
- 8.7 High severity
- 7.5 High severity
- 7.6 High severity
- 7.1 High severity
- 7.1 High severity
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