Vibe trading ai: Vibe-Trading LLM-callable tools permit command execution, code injection, and SSRF
Vibe trading AI contains multiple critical vulnerabilities that allow unauthenticated remote attackers to execute arbitrary shell commands as root via LLM-callable tools. The BashTool, BackgroundRunTool, and other components execute commands without filtering or validation, enabling command injection, code injection, and SSRF. These vulnerabilities are reachable from any anonymous TCP client due to an unauthenticated API endpoint and lack of operator opt-in gating. Prompt injection attacks can also trigger arbitrary command execution by embedding malicious instructions in documents processed by the LLM agent. The vulnerabilities affect versions from 0.1.0 up to but not including 0.1.7. A patch is available to remediate these issues.
AI Analysis
Technical Summary
The Vibe trading AI platform includes five critical security flaws in its LLM-callable tools, notably the BashTool which passes LLM-generated commands directly to subprocess.run with shell=True and no filtering, enabling remote code execution as root. Other tools exhibit similar unsafe command execution or SSRF due to lack of input validation. These tools are automatically registered and callable by the LLM agent without operator consent. Combined with an unauthenticated POST API endpoint, these flaws allow any anonymous TCP client to achieve root-level RCE. Additionally, prompt injection attacks can cause the LLM to execute attacker-controlled shell commands embedded in documents it processes. The vulnerabilities affect versions >=0.1.0 and <0.1.7. The CVSS v3.1 score is 9.0 (critical). A patch is available.
Potential Impact
Successful exploitation allows unauthenticated remote attackers to execute arbitrary shell commands as root on the host running the Vibe trading AI container. This includes full system compromise, data access, and potential lateral movement. The vulnerabilities also enable server-side request forgery (SSRF) and code injection via Jinja2 templates with disabled autoescape. The lack of filtering or validation means attackers can bypass intended usage restrictions and leverage prompt injection to escalate privileges even from authenticated users. The combined effect is a critical security risk with complete system control.
Mitigation Recommendations
A patch is available to address these vulnerabilities. Operators should apply the official fix promptly. The vendor advisory confirms patch availability. Until patched, restrict network access to port 8899 to trusted clients only and disable or restrict LLM tool registration if possible. Avoid processing untrusted documents that could contain prompt injection payloads. Do not rely on the LLM's internal judgment to filter commands. Follow the vendor advisory for detailed remediation steps.
Vibe trading ai: Vibe-Trading LLM-callable tools permit command execution, code injection, and SSRF
Description
Vibe trading AI contains multiple critical vulnerabilities that allow unauthenticated remote attackers to execute arbitrary shell commands as root via LLM-callable tools. The BashTool, BackgroundRunTool, and other components execute commands without filtering or validation, enabling command injection, code injection, and SSRF. These vulnerabilities are reachable from any anonymous TCP client due to an unauthenticated API endpoint and lack of operator opt-in gating. Prompt injection attacks can also trigger arbitrary command execution by embedding malicious instructions in documents processed by the LLM agent. The vulnerabilities affect versions from 0.1.0 up to but not including 0.1.7. A patch is available to remediate these issues.
CVSS v3.1
Score 10.0critical
Affected software
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AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
The Vibe trading AI platform includes five critical security flaws in its LLM-callable tools, notably the BashTool which passes LLM-generated commands directly to subprocess.run with shell=True and no filtering, enabling remote code execution as root. Other tools exhibit similar unsafe command execution or SSRF due to lack of input validation. These tools are automatically registered and callable by the LLM agent without operator consent. Combined with an unauthenticated POST API endpoint, these flaws allow any anonymous TCP client to achieve root-level RCE. Additionally, prompt injection attacks can cause the LLM to execute attacker-controlled shell commands embedded in documents it processes. The vulnerabilities affect versions >=0.1.0 and <0.1.7. The CVSS v3.1 score is 9.0 (critical). A patch is available.
Potential Impact
Successful exploitation allows unauthenticated remote attackers to execute arbitrary shell commands as root on the host running the Vibe trading AI container. This includes full system compromise, data access, and potential lateral movement. The vulnerabilities also enable server-side request forgery (SSRF) and code injection via Jinja2 templates with disabled autoescape. The lack of filtering or validation means attackers can bypass intended usage restrictions and leverage prompt injection to escalate privileges even from authenticated users. The combined effect is a critical security risk with complete system control.
Mitigation Recommendations
A patch is available to address these vulnerabilities. Operators should apply the official fix promptly. The vendor advisory confirms patch availability. Until patched, restrict network access to port 8899 to trusted clients only and disable or restrict LLM tool registration if possible. Avoid processing untrusted documents that could contain prompt injection payloads. Do not rely on the LLM's internal judgment to filter commands. Follow the vendor advisory for detailed remediation steps.
Technical Details
- Gcve Source
- db.gcve.eu
- Osv Id
- GHSA-jqmf-mx4f-hfr6
- Osv Schema Version
- 1.4.0
- Ecosystems
- ["PyPI"]
- Database Specific Severity
- CRITICAL
- Cvss Version
- 3.1
Threat ID: 6ac139b2a43b0b3b89d69af1
Added to database: 10/03/2026, 17:21:54 UTC
Last enriched: 10/03/2026, 17:40:19 UTC
Last updated: 10/03/2026, 20:27:37 UTC
Views: 4
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