FKIE_CVE-2026-82723
Vulnerability from fkie_nvd - Published: 2026-09-17 14:17 - Updated: 2026-09-17 19:17
Severity
Summary
Insertion of Sensitive Information into Log File vulnerability in team-alembic AshAuthentication allows disclosure of user password digests to readers of the audit store.
The audit_log add-on builds each entry's extra_data in AshAuthentication.AddOn.AuditLog.Auditor.build_extra_data/4, which takes :actor from the action callback context verbatim. Any audited action invoked with actor: set to a user record therefore deposits that record, including its hashed_password attribute, into the audit entry. The same module already collapses the audited identity to an opaque string via AshAuthentication.user_to_subject/1 and filters params against the strategy's configured allow-list, so the actor is the only stored value that reaches the audit store unfiltered. Marking the attribute sensitive?: true does not help, because that redacts inspect/1 output rather than JSON encoding or raw-term storage.
There is no attacker-controlled trigger and no network disclosure path: entries accumulate from ordinary authenticated activity, and an attacker's own requests deposit only their own digest. Exploitation requires independent read access to the audit store, such as database credentials, an audit role, a backup, or a log shipper, at which point the digests support offline password attack against every active account. Whether the material persists depends on the data layer, since raw-term stores keep it verbatim while a SQL store raises Protocol.UndefinedError and drops the entry unless the user resource derives Jason.Encoder.
This issue affects ash_authentication: from 4.12.0 before 4.15.0 and from 5.0.0-rc.0 before 5.0.0-rc.2.
References
Impacted products
| Vendor | Product | Version |
|---|
{
"affected": [
{
"affectedData": [
{
"collectionURL": "https://repo.hex.pm",
"cpes": [
"cpe:2.3:a:team-alembic:ash_authentication:*:*:*:*:*:*:*:*"
],
"defaultStatus": "unaffected",
"modules": [
"\u0027Elixir.AshAuthentication.AddOn.AuditLog.Auditor\u0027"
],
"packageName": "ash_authentication",
"packageURL": "pkg:hex/ash_authentication",
"product": "ash_authentication",
"programFiles": [
"lib/ash_authentication/add_ons/audit_log/auditor.ex"
],
"programRoutines": [
{
"name": "\u0027Elixir.AshAuthentication.AddOn.AuditLog.Auditor\u0027:build_extra_data/4"
}
],
"repo": "https://github.com/team-alembic/ash_authentication",
"vendor": "team-alembic",
"versions": [
{
"lessThan": "4.15.0",
"status": "affected",
"version": "4.12.0",
"versionType": "semver"
},
{
"lessThan": "5.0.0-rc.2",
"status": "affected",
"version": "5.0.0-rc.0",
"versionType": "semver"
}
]
},
{
"collectionURL": "https://github.com",
"cpes": [
"cpe:2.3:a:team-alembic:ash_authentication:*:*:*:*:*:*:*:*"
],
"defaultStatus": "unaffected",
"modules": [
"\u0027Elixir.AshAuthentication.AddOn.AuditLog.Auditor\u0027"
],
"packageName": "team-alembic/ash_authentication",
"packageURL": "pkg:github/team-alembic/ash_authentication",
"product": "ash_authentication",
"programFiles": [
"lib/ash_authentication/add_ons/audit_log/auditor.ex"
],
"programRoutines": [
{
"name": "\u0027Elixir.AshAuthentication.AddOn.AuditLog.Auditor\u0027:build_extra_data/4"
}
],
"repo": "https://github.com/team-alembic/ash_authentication",
"vendor": "team-alembic",
"versions": [
{
"changes": [
{
"at": "17ea0dff3bad56a7e915e050c43ab7160b37901f",
"status": "unaffected"
},
{
"at": "f6b49cc98b9ff7c16a1aeb12e35633a8d93a211f",
"status": "unaffected"
}
],
"lessThan": "*",
"status": "affected",
"version": "255cfc9c0e511b7e0de39f8b3d676ae994fae06c",
"versionType": "git"
}
]
}
],
"source": "6b3ad84c-e1a6-4bf7-a703-f496b71e49db"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "Insertion of Sensitive Information into Log File vulnerability in team-alembic AshAuthentication allows disclosure of user password digests to readers of the audit store.\n\nThe audit_log add-on builds each entry\u0027s extra_data in AshAuthentication.AddOn.AuditLog.Auditor.build_extra_data/4, which takes :actor from the action callback context verbatim. Any audited action invoked with actor: set to a user record therefore deposits that record, including its hashed_password attribute, into the audit entry. The same module already collapses the audited identity to an opaque string via AshAuthentication.user_to_subject/1 and filters params against the strategy\u0027s configured allow-list, so the actor is the only stored value that reaches the audit store unfiltered. Marking the attribute sensitive?: true does not help, because that redacts inspect/1 output rather than JSON encoding or raw-term storage.\n\nThere is no attacker-controlled trigger and no network disclosure path: entries accumulate from ordinary authenticated activity, and an attacker\u0027s own requests deposit only their own digest. Exploitation requires independent read access to the audit store, such as database credentials, an audit role, a backup, or a log shipper, at which point the digests support offline password attack against every active account. Whether the material persists depends on the data layer, since raw-term stores keep it verbatim while a SQL store raises Protocol.UndefinedError and drops the entry unless the user resource derives Jason.Encoder.\n\nThis issue affects ash_authentication: from 4.12.0 before 4.15.0 and from 5.0.0-rc.0 before 5.0.0-rc.2."
}
],
"id": "CVE-2026-82723",
"lastModified": "2026-09-17T19:17:04.150",
"metrics": {
"cvssMetricV40": [
{
"cvssData": {
"Automatable": "NOT_DEFINED",
"Recovery": "NOT_DEFINED",
"Safety": "NOT_DEFINED",
"attackComplexity": "HIGH",
"attackRequirements": "PRESENT",
"attackVector": "LOCAL",
"availabilityRequirement": "NOT_DEFINED",
"baseScore": 1.8,
"baseSeverity": "LOW",
"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": "HIGH",
"providerUrgency": "NOT_DEFINED",
"subAvailabilityImpact": "NONE",
"subConfidentialityImpact": "NONE",
"subIntegrityImpact": "NONE",
"userInteraction": "NONE",
"valueDensity": "NOT_DEFINED",
"vectorString": "CVSS:4.0/AV:L/AC:H/AT:P/PR:H/UI:N/VC:L/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": "LOW",
"vulnIntegrityImpact": "NONE",
"vulnerabilityResponseEffort": "NOT_DEFINED"
},
"source": "6b3ad84c-e1a6-4bf7-a703-f496b71e49db",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2026-82723",
"options": [
{
"exploitation": "none"
},
{
"automatable": "no"
},
{
"technicalImpact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2026-09-17T18:18:14.370339Z",
"version": "2.0.3"
}
}
]
},
"published": "2026-09-17T14:17:32.863",
"references": [
{
"source": "6b3ad84c-e1a6-4bf7-a703-f496b71e49db",
"url": "https://cna.erlef.org/cves/CVE-2026-82723.html"
},
{
"source": "6b3ad84c-e1a6-4bf7-a703-f496b71e49db",
"url": "https://github.com/team-alembic/ash_authentication/commit/17ea0dff3bad56a7e915e050c43ab7160b37901f"
},
{
"source": "6b3ad84c-e1a6-4bf7-a703-f496b71e49db",
"url": "https://github.com/team-alembic/ash_authentication/commit/255cfc9c0e511b7e0de39f8b3d676ae994fae06c"
},
{
"source": "6b3ad84c-e1a6-4bf7-a703-f496b71e49db",
"url": "https://github.com/team-alembic/ash_authentication/commit/f6b49cc98b9ff7c16a1aeb12e35633a8d93a211f"
},
{
"source": "6b3ad84c-e1a6-4bf7-a703-f496b71e49db",
"url": "https://github.com/team-alembic/ash_authentication/security/advisories/GHSA-59wx-q3r8-ghv4"
},
{
"source": "6b3ad84c-e1a6-4bf7-a703-f496b71e49db",
"url": "https://osv.dev/vulnerability/EEF-CVE-2026-82723"
}
],
"sourceIdentifier": "6b3ad84c-e1a6-4bf7-a703-f496b71e49db",
"vulnStatus": "Received",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-532"
}
],
"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.
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- 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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