CVE-2026-100631 (GCVE-0-2026-100631)
Vulnerability from cvelistv5 – Published: 2026-09-26 13:23 – Updated: 2026-09-28 18:55
VLAI
EPSS
VEX
Title
Parse Server 9.0.0 Unauthenticated Installation Deletion via Operator Injection
Summary
Parse Server is an open source backend server. In versions prior to 8.6.90 and in versions from 9.0.0 prior to 9.10.1-alpha.9, the device token deduplication logic for installation records does not validate the type of client-supplied installation fields before using them to build database queries. An unauthenticated remote attacker who knows only the public application ID can submit non-string values in these fields to inject query operators, causing the deduplication cleanup — which runs with elevated privileges before class-level permissions are evaluated — to delete every device registration in the application or an attacker-chosen subset of them. No account, session token, master key, or user interaction is required. Deleted registrations cannot be recovered on the server, so push notifications cannot be delivered until every client re-registers. Any deployment that exposes the REST API to clients and uses push notifications is affected in its default configuration. Versions 8.6.90 and 9.10.1-alpha.9 fix the issue by rejecting non-string values with a client error and by scoping the deduplication cleanup to the calling application. No workaround other than upgrading is available.
Severity
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-09-28 18:55 UTC
CWE
- CWE-943 - Improper Neutralization of Special Elements in Data Query Logic
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://github.com/parse-community/parse-server/s… | vendor-advisory |
| https://www.vulncheck.com/advisories/parse-server… | third-party-advisory |
Impacted products
2 products
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| parse-community | parse-server |
Affected:
9.0.0 , < 9.10.1-alpha.9
(semver)
Unaffected: 9.10.1-alpha.9 (semver) |
guessed | |
| parse-community | parse-server |
Affected:
0 , < 8.6.90
(semver)
Unaffected: 8.6.90 (semver) |
guessed |
Date Public
2026-09-09 00:00
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.
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