ash-project ash_ai 1.5.0 Error AshAi.Tool.Errors.format information exposure
| CVSS Meta Temp Score | Current Exploit Price (≈) | CTI Interest Score |
|---|---|---|
| 4.1 | $0-$5k | 0.00+ |
Summary
A vulnerability described as problematic has been identified in ash-project ash_ai 1.5.0. This affects the function AshAi.Tool.Errors.format of the component Error Handler. Executing a manipulation can lead to information exposure.
The identification of this vulnerability is CVE-2026-119613. The attack may be launched remotely. There is no exploit available.
Upgrading the affected component is recommended.
Details
A vulnerability classified as problematic was found in ash-project ash_ai 1.5.0. This vulnerability affects the function AshAi.Tool.Errors.format of the component Error Handler. The manipulation with an unknown input leads to a information exposure vulnerability. The CWE definition for the vulnerability is CWE-209. The product generates an error message that includes sensitive information about its environment, users, or associated data. As an impact it is known to affect confidentiality. CVE summarizes:
Generation of Error Message Containing Sensitive Information vulnerability in ash-project ash_ai allows a caller of an AshAi tool to read internal error details, including module names and data values, by making a tool call fail. AshAi.ToToolError gained an implementation for Ash.Error.Unknown.UnknownError that returns the error's error field as is, and AshAi.Tool.Errors.format/1 sends that text to MCP clients (tool calls and resource reads in AshAi.Mcp.Server) and to the model in AshAi.ToolLoop. Ash stores the full Exception.format/2 output of a raised exception, or inspect/1 of a bare {:error, term} return, in that field. A tool result that cannot be JSON-encoded raises a Protocol.UndefinedError whose text includes the inspected value, which can be a whole record with fields the tool never returns. None of these errors were logged. The fix logs them under an error id and returns only that id to the caller. This issue affects ash_ai: from 1.5.0 before 1.5.1.
The advisory is shared for download at github.com. This vulnerability was named CVE-2026-119613 since 10/31/2026. The exploitation appears to be easy. The attack can be initiated remotely. There are known technical details, but no exploit is available. The MITRE ATT&CK project declares the attack technique as T1592.
Upgrading to version 1.5.1 eliminates this vulnerability.
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Product
Type
Vendor
Name
Version
Website
CPE 2.3
CPE 2.2
CVSSv4
VulDB Vector: 🔒VulDB Reliability: 🔍
CNA CVSS-B Score: 🔒
CNA CVSS-BT Score: 🔒
CNA Vector: 🔒
CVSSv3
VulDB Meta Base Score: 4.3VulDB Meta Temp Score: 4.1
VulDB Base Score: 4.3
VulDB Temp Score: 4.1
VulDB Vector: 🔒
VulDB Reliability: 🔍
CVSSv2
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VulDB Base Score: 🔒
VulDB Temp Score: 🔒
VulDB Reliability: 🔍
Exploiting
Class: Information exposureCWE: CWE-209 / CWE-200 / CWE-284
CAPEC: 🔒
ATT&CK: 🔒
Physical: No
Local: No
Remote: Yes
Availability: 🔒
Status: Not defined
Price Prediction: 🔍
Current Price Estimation: 🔒
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Threat Intelligence
Interest: 🔍Active Actors: 🔍
Active APT Groups: 🔍
Countermeasures
Recommended: UpgradeStatus: 🔍
0-Day Time: 🔒
Upgrade: ash_ai 1.5.1
Timeline
10/31/2026 CVE reserved11/09/2026 Advisory disclosed
11/09/2026 VulDB entry created
11/09/2026 VulDB entry last update
Sources
Product: github.comAdvisory: github.com
Status: Confirmed
CNA: EEF
CVE: CVE-2026-119613 (🔒)
GCVE (CVE): GCVE-0-2026-119613
GCVE (VulDB): GCVE-100-433144
Entry
Created: 11/09/2026 14:33Changes: 11/09/2026 14:33 (69)
Complete: 🔍
Cache ID: 216::103
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