Description
LangAlpha through 2026.09.07 contains an indirect prompt injection vulnerability that allows remote attackers to execute shell commands or Python by planting instructions in web content retrieved by the agent. Because Bash and ExecuteCode lack an allow-list and human-in-the-loop approval, attackers can run code in the workspace sandbox and exfiltrate vault secrets from _internal/.vault_secrets.json.
Published: 2026-10-20
Score: 8.6 High
EPSS: n/a
KEV: No
Impact: Remote Code Execution
Action: Immediate Patch
AI Analysis

Impact

The vulnerability in LangAlpha prior to 2026.09.07 is an indirect prompt injection flaw that permits an attacker to cause the agent to execute arbitrary shell or Python code. Because the Bash and ExecuteCode functions lack an allow‑list and do not require human approval, embedded instructions in fetched web content are executed in the workspace sandbox. An attacker who can inject such content can run any command and exfiltrate sensitive vault secrets from the internal .vault_secrets.json file. This flaw represents a remote code execution issue capable of compromising confidentiality, integrity, and availability of the affected system.

Affected Systems

LangAlpha, distributed by ginlix‑ai, version 2026.09.07 and earlier contains this issue. The affected component is the agent module that reads external web content and forwards it to the Bash and ExecuteCode execution back‑ends.

Risk and Exploitability

With a CVSS score of 8.6 the flaw is considered high severity. No EPSS score is available, and the vulnerability is not listed in the CISA KEV catalog, but the lack of an allow‑list and the lack of any user confirmation make exploitation straightforward for anyone able to supply crafted web content. The attack vector is inferred to be remote, originating from the agent's ability to download and execute web content. Once a payload is embedded, the agent will run it in the sandbox, allowing exfiltration of secrets and full system compromise.

Generated by OpenCVE AI on October 20, 2026 at 06:02 UTC.

Remediation

No solution or workaround provided in the CVE record.

OpenCVE Recommended Actions

  • Update LangAlpha to a patched release (2026.09.08 or later) that addresses the prompt injection flaw.
  • Reconfigure the agent to disable or restrict the Bash and ExecuteCode commands for content coming from untrusted sources.
  • Move or encrypt internal vault secrets and enforce strict access controls so that even if code runs it cannot read _internal/.vault_secrets.json.
  • Monitor execution logs for unexpected shell activity and restrict network access to the agent, limiting its ability to contact external content sources.

Generated by OpenCVE AI on October 20, 2026 at 06:02 UTC.

Tracking

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Advisories

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History

Tue, 20 Oct 2026 01:15:00 +0000

Type Values Removed Values Added
Description LangAlpha through 2026.09.07 contains an indirect prompt injection vulnerability that allows remote attackers to execute shell commands or Python by planting instructions in web content retrieved by the agent. Because Bash and ExecuteCode lack an allow-list and human-in-the-loop approval, attackers can run code in the workspace sandbox and exfiltrate vault secrets from _internal/.vault_secrets.json.
Title LangAlpha through 2026.09.07 Indirect Prompt Injection RCE via Bash and ExecuteCode
Weaknesses CWE-1427
References
Metrics cvssV3_1

{'score': 8.1, 'vector': 'CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:N'}

cvssV4_0

{'score': 8.6, 'vector': 'CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:H/VI:H/VA:N/SC:N/SI:N/SA:N'}


Subscriptions

No data.

cve-icon MITRE

Status: PUBLISHED

Assigner: VulnCheck

Published:

Updated: 2026-10-20T00:46:05.334Z

Reserved: 2026-10-12T15:52:36.683Z

Link: CVE-2026-109440

cve-icon Vulnrichment

No data.

cve-icon NVD

Status : Received

Published: 2026-10-20T01:17:10.103

Modified: 2026-10-20T01:17:10.103

Link: CVE-2026-109440

cve-icon Redhat

No data.

cve-icon OpenCVE Enrichment

Updated: 2026-10-20T06:15:10Z

Weaknesses
  • CWE-1427

    Improper Neutralization of Input Used for LLM Prompting