FKIE_CVE-2026-75760
Vulnerability from fkie_nvd - Published: 2026-08-31 02:17 - Updated: 2026-08-31 16:19
Severity
Summary
Generation of Error Message Containing Sensitive Information vulnerability in ash-project ash_ai discloses provider request state and credentials in a user-facing validation error.
In AshAi.Changes.Vectorize, when the embedding provider call fails the change added a changeset error whose message inspected the raw error term (An error occurred while generating embeddings: #{inspect(error)}). A plain-string add_error produces an Ash.Error.Changes.InvalidChanges in the :invalid class, which AshJsonApi and AshGraphql render back to the caller. The embedding client's error term is not sanitized, so it can carry the request URL, the provider response body, and, for HTTP clients that keep the request in the error struct, the outbound Authorization header with the provider API key. Failures are attacker-reachable via oversized or malformed vectorized content. The fix logs the raw error and returns a generic message.
This issue affects ash_ai: from 0.1.0 before 1.0.0.
References
Impacted products
| Vendor | Product | Version |
|---|
{
"affected": [
{
"affectedData": [
{
"collectionURL": "https://repo.hex.pm",
"cpes": [
"cpe:2.3:a:ash-project:ash_ai:*:*:*:*:*:*:*:*"
],
"defaultStatus": "unaffected",
"modules": [
"\u0027Elixir.AshAi.Changes.Vectorize\u0027"
],
"packageName": "ash_ai",
"packageURL": "pkg:hex/ash_ai",
"product": "ash_ai",
"programFiles": [
"lib/ash_ai/changes/vectorize.ex"
],
"programRoutines": [
{
"name": "\u0027Elixir.AshAi.Changes.Vectorize\u0027:change/3"
}
],
"repo": "https://github.com/ash-project/ash_ai",
"vendor": "ash-project",
"versions": [
{
"lessThan": "1.0.0",
"status": "affected",
"version": "0.1.0",
"versionType": "semver"
}
]
},
{
"collectionURL": "https://github.com",
"cpes": [
"cpe:2.3:a:ash-project:ash_ai:*:*:*:*:*:*:*:*"
],
"defaultStatus": "unaffected",
"modules": [
"\u0027Elixir.AshAi.Changes.Vectorize\u0027"
],
"packageName": "ash-project/ash_ai",
"packageURL": "pkg:github/ash-project/ash_ai",
"product": "ash_ai",
"programFiles": [
"lib/ash_ai/changes/vectorize.ex"
],
"programRoutines": [
{
"name": "\u0027Elixir.AshAi.Changes.Vectorize\u0027:change/3"
}
],
"repo": "https://github.com/ash-project/ash_ai",
"vendor": "ash-project",
"versions": [
{
"lessThan": "088a2562e16d65f36cec178070de683636479f58",
"status": "affected",
"version": "5334edc73a007f0629661761d6a75796f2fc0004",
"versionType": "git"
}
]
}
],
"source": "6b3ad84c-e1a6-4bf7-a703-f496b71e49db"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "Generation of Error Message Containing Sensitive Information vulnerability in ash-project ash_ai discloses provider request state and credentials in a user-facing validation error.\n\nIn AshAi.Changes.Vectorize, when the embedding provider call fails the change added a changeset error whose message inspected the raw error term (An error occurred while generating embeddings: #{inspect(error)}). A plain-string add_error produces an Ash.Error.Changes.InvalidChanges in the :invalid class, which AshJsonApi and AshGraphql render back to the caller. The embedding client\u0027s error term is not sanitized, so it can carry the request URL, the provider response body, and, for HTTP clients that keep the request in the error struct, the outbound Authorization header with the provider API key. Failures are attacker-reachable via oversized or malformed vectorized content. The fix logs the raw error and returns a generic message.\n\nThis issue affects ash_ai: from 0.1.0 before 1.0.0."
}
],
"id": "CVE-2026-75760",
"lastModified": "2026-08-31T16:19:11.957",
"metrics": {
"cvssMetricV40": [
{
"cvssData": {
"Automatable": "NOT_DEFINED",
"Recovery": "NOT_DEFINED",
"Safety": "NOT_DEFINED",
"attackComplexity": "LOW",
"attackRequirements": "NONE",
"attackVector": "NETWORK",
"availabilityRequirement": "NOT_DEFINED",
"baseScore": 7.1,
"baseSeverity": "HIGH",
"confidentialityRequirement": "NOT_DEFINED",
"exploitMaturity": "NOT_DEFINED",
"integrityRequirement": "NOT_DEFINED",
"modifiedAttackComplexity": "NOT_DEFINED",
"modifiedAttackRequirements": "NOT_DEFINED",
"modifiedAttackVector": "NOT_DEFINED",
"modifiedPrivilegesRequired": "NOT_DEFINED",
"modifiedSubAvailabilityImpact": "NOT_DEFINED",
"modifiedSubConfidentialityImpact": "NOT_DEFINED",
"modifiedSubIntegrityImpact": "NOT_DEFINED",
"modifiedUserInteraction": "NOT_DEFINED",
"modifiedVulnAvailabilityImpact": "NOT_DEFINED",
"modifiedVulnConfidentialityImpact": "NOT_DEFINED",
"modifiedVulnIntegrityImpact": "NOT_DEFINED",
"privilegesRequired": "LOW",
"providerUrgency": "NOT_DEFINED",
"subAvailabilityImpact": "NONE",
"subConfidentialityImpact": "NONE",
"subIntegrityImpact": "NONE",
"userInteraction": "NONE",
"valueDensity": "NOT_DEFINED",
"vectorString": "CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:N/VA:N/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X",
"version": "4.0",
"vulnAvailabilityImpact": "NONE",
"vulnConfidentialityImpact": "HIGH",
"vulnIntegrityImpact": "NONE",
"vulnerabilityResponseEffort": "NOT_DEFINED"
},
"source": "6b3ad84c-e1a6-4bf7-a703-f496b71e49db",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2026-75760",
"options": [
{
"exploitation": "poc"
},
{
"automatable": "no"
},
{
"technicalImpact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2026-08-31T16:07:03.271063Z",
"version": "2.0.3"
}
}
]
},
"published": "2026-08-31T02:17:01.313",
"references": [
{
"source": "6b3ad84c-e1a6-4bf7-a703-f496b71e49db",
"url": "https://cna.erlef.org/cves/CVE-2026-75760.html"
},
{
"source": "6b3ad84c-e1a6-4bf7-a703-f496b71e49db",
"url": "https://github.com/ash-project/ash_ai/commit/088a2562e16d65f36cec178070de683636479f58"
},
{
"source": "6b3ad84c-e1a6-4bf7-a703-f496b71e49db",
"url": "https://github.com/ash-project/ash_ai/security/advisories/GHSA-p5cr-mmmf-6w39"
},
{
"source": "6b3ad84c-e1a6-4bf7-a703-f496b71e49db",
"url": "https://osv.dev/vulnerability/EEF-CVE-2026-75760"
},
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"url": "https://github.com/ash-project/ash_ai/security/advisories/GHSA-p5cr-mmmf-6w39"
}
],
"sourceIdentifier": "6b3ad84c-e1a6-4bf7-a703-f496b71e49db",
"vulnStatus": "Received",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-209"
}
],
"source": "6b3ad84c-e1a6-4bf7-a703-f496b71e49db",
"type": "Secondary"
}
]
}
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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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