CVE-2026-78230 (GCVE-0-2026-78230)
Vulnerability from cvelistv5 – Published: 2026-09-08 16:41 – Updated: 2026-09-08 17:33
VLAI
EPSS
VEX
Title
AshAi aggregate tool can read field-policy-protected fields
Summary
AshAi exposes Ash read actions to language-model tool calls. The read tool accepts an aggregate result type (min, max, sum, avg) that builds an ad-hoc Ash.Query.Aggregate over a named field and returns its raw value.
Ash field policies redact forbidden fields on returned records (replacing them with %Ash.ForbiddenField{}), but that redaction does not apply to aggregate values. A tool caller could therefore read a field the calling actor's field policies forbid by requesting it as an aggregate; min/max in particular return an actual field value. This includes fields that are public? true but restricted per-actor by a field policy, such as sensitive PII. The tool's existing check only required the field to be public, which is a separate axis from per-actor field-policy authorization.
The fix authorizes the aggregated field against the resource's field policies, so aggregating over a field the actor may not see is refused or scoped to the rows where it is visible.
This issue affects ash_ai: from 0.1.0 before 1.0.3.
Severity
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-09-08 17:33 UTC
CWE
- CWE-1220 - Insufficient Granularity of Access Control
Assigner
References
5 references
Impacted products
2 products
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| ash-project | ash_ai |
Affected:
0.1.0 , < 1.0.3
(semver)
cpe:2.3:a:ash-project:ash_ai:*:*:*:*:*:*:*:* |
||
| ash-project | ash_ai |
Affected:
2ba234b50946a3b8116190c8467f9f4dfa5edce7 , < 9c02de581625c342c9870a672830bff28c1d701e
(git)
cpe:2.3:a:ash-project:ash_ai:*:*:*:*:*:*:*:* |
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"cveMetadata": "{\"cveId\": \"CVE-2026-78230\", \"state\": \"PUBLISHED\", \"dateUpdated\": \"2026-09-08T17:33:57.604Z\", \"dateReserved\": \"2026-08-31T00:45:02.439Z\", \"assignerOrgId\": \"6b3ad84c-e1a6-4bf7-a703-f496b71e49db\", \"datePublished\": \"2026-09-08T16:41:45.975Z\", \"assignerShortName\": \"EEF\"}",
"dataType": "CVE_RECORD",
"dataVersion": "5.2"
}
}
}
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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.
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.
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