PatchSiren cyber security CVE debrief
CVE-2026-75760 ash-project CVE debrief
AI-assisted PatchSiren debrief based on the supplied source corpus. The CVE record was published on 2026-08-31T02:17:01.313Z and has not been modified since then. The ash_ai product is vulnerable to Generation of Error Message Containing Sensitive Information. When the embedding provider call fails, the error message could potentially disclose sensitive information such as the request URL, provider response body, and outbound Authorization header with the provider API key. This issue is reachable via oversized or malformed vectorized content. The fix involves logging the raw error and returning a generic message. Organizations and developers should review the official advisory and CVE record to understand the affected scope, severity, and vendor guidance. They should plan for vendor-supported updates or mitigations through normal change control where exposure is confirmed. Additionally, they should review compensating controls for exposed systems while remediation is scheduled and verified.
- Vendor
- ash-project
- Product
- ash_ai
- CVSS
- HIGH 7.1
- CISA KEV
- Not listed in stored evidence
- Original CVE published
- 2026-08-31
- Original CVE updated
- 2026-08-31
- Advisory published
- 2026-08-31
- Advisory updated
- 2026-08-31
Who should care
Organizations and developers using ash_ai versions between 0.1.0 and before 1.0.0 should be aware of this vulnerability and take steps to mitigate it. They should confirm whether affected product deployments exist in managed environments and assign an owner for follow-up. Affected operators, platforms, vulnerability-management, and security teams should prioritize patching to prevent potential sensitive information disclosure. They should also conduct inventory checks to identify and update vulnerable ash_ai installations, monitor for suspicious activity related to oversized or malformed vectorized content, and consider exception tracking for unusual error patterns.
Technical summary
The ash_ai product is vulnerable to Generation of Error Message Containing Sensitive Information. When the embedding provider call fails, the error message could potentially disclose sensitive information such as the request URL, provider response body, and outbound Authorization header with the provider API key. This issue is reachable via oversized or malformed vectorized content. The fix involves logging the raw error and returning a generic message.
Defensive priority
Organizations using ash_ai should prioritize patching to prevent potential sensitive information disclosure.
Recommended defensive actions
- Review and apply the patch for ash_ai version 1.0.0 or later.
- Implement compensating controls to monitor and limit sensitive information disclosure.
- Conduct inventory checks to identify and update vulnerable ash_ai installations.
- Monitor for suspicious activity related to oversized or malformed vectorized content.
- Consider exception tracking for unusual error patterns.
Evidence notes
The CVE-2026-75760 issue arises from the ash_ai product's handling of embedding provider errors. When the embedding provider call fails, the change adds a changeset error whose message inspects the raw error term. This could potentially disclose sensitive information such as the request URL, provider response body, and outbound Authorization header with the provider API key. The issue is reachable via oversized or malformed vectorized content. The fix involves logging the raw error and returning a generic message.
Sources and references
Verified primary and authoritative sources
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CVE-2026-75760 CVE Program record
Publisher, destination, and source semantics verified
URL: https://www.cve.org/CVERecord?id=CVE-2026-75760
CVE Program - Official CVE Program record with source-provided CVE metadata.
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CVE-2026-75760 NVD vulnerability detail
Publisher, destination, and source semantics verified
URL: https://nvd.nist.gov/vuln/detail/CVE-2026-75760
NIST National Vulnerability Database - Official NIST NVD detail page and source-specific vulnerability assessment.
Supplemental references
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Source reference
Unverified legacy reference
URL: https://cna.erlef.org/cves/CVE-2026-75760.html
6b3ad84c-e1a6-4bf7-a703-f496b71e49db
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Source reference
Unverified legacy reference
URL: https://github.com/ash-project/ash_ai/commit/088a2562e16d65f36cec178070de683636479f58
6b3ad84c-e1a6-4bf7-a703-f496b71e49db
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Source reference
Unverified legacy reference
URL: https://github.com/ash-project/ash_ai/security/advisories/GHSA-p5cr-mmmf-6w39
6b3ad84c-e1a6-4bf7-a703-f496b71e49db
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Source reference
Unverified legacy reference
URL: https://osv.dev/vulnerability/EEF-CVE-2026-75760
6b3ad84c-e1a6-4bf7-a703-f496b71e49db
Methodology and review provenance
AI-assisted synthesis based on stored public vulnerability evidence. System validation, approval state, and publication status do not by themselves establish human review of this revision. PatchSiren helps prioritize defensive review and does not prove exposure or remediation on any system.