CVE-2025-49131 Overview
CVE-2025-49131 is a critical sandbox escape vulnerability affecting FastGPT, an open-source platform for building, deploying, and operating AI-driven workflows and conversational agents. The vulnerability exists in the fastgpt-sandbox container, a specialized isolated environment designed to safely execute user-submitted or dynamically generated code. Due to insufficient isolation and inadequate restrictions on code execution through overly permissive syscalls, attackers can escape the intended sandbox boundaries.
Critical Impact
Attackers exploiting this vulnerability can read and overwrite arbitrary files on the host system and bypass Python module import restrictions, potentially leading to complete system compromise.
Affected Products
- FastGPT versions prior to 4.9.11
- fastgpt-sandbox container (all versions before the security patch)
- FastGPT deployments utilizing the sandbox for code execution
Discovery Timeline
- June 9, 2025 - CVE-2025-49131 published to NVD
- December 29, 2025 - Last updated in NVD database
Technical Details for CVE-2025-49131
Vulnerability Analysis
This vulnerability stems from CWE-732 (Incorrect Permission Assignment for Critical Resource). The fastgpt-sandbox container was designed to provide isolation for executing untrusted code within FastGPT workflows. However, the sandbox implementation permitted an excessive number of system calls that an attacker could leverage to break out of the containerized environment.
The sandbox allowed syscalls such as SYS_EXECVE, SYS_OPEN, SYS_READLINK, and filesystem manipulation calls like SYS_MKDIRAT and SYS_MKDIR, which provided attackers with the primitives necessary to interact with the underlying filesystem beyond the intended sandbox scope. By chaining these syscalls, an attacker could achieve arbitrary file read and write capabilities, effectively nullifying the sandbox's security guarantees.
Root Cause
The root cause lies in the overly permissive syscall whitelist configuration within the sandbox environment. The original implementation allowed approximately 50+ syscalls including dangerous filesystem and process management calls. This excessive permission set violated the principle of least privilege, enabling attackers to perform operations that should have been blocked by a properly configured sandbox.
Attack Vector
The attack vector is network-based and requires low privileges to exploit. An authenticated attacker can submit malicious code through FastGPT's workflow system, which gets executed within the sandbox container. By leveraging the permitted syscalls, the attacker can:
- Escape the sandbox isolation boundary
- Read sensitive files from the host filesystem
- Overwrite arbitrary files, potentially achieving persistence or further compromise
- Bypass Python module import restrictions to load malicious libraries
// Security patch comparison - Syscall whitelist reduction
// Source: https://github.com/labring/FastGPT/commit/bb810a43a1c70683fab7f5fe993771e930a94426
// BEFORE (Vulnerable): Overly permissive syscall list
allowed_syscalls = [
"syscall.SYS_ARCH_PRCTL", "syscall.SYS_BRK", "syscall.SYS_CLONE",
"syscall.SYS_CLOSE", "syscall.SYS_EPOLL_CREATE1", "syscall.SYS_EXECVE",
"syscall.SYS_EXIT", "syscall.SYS_EXIT_GROUP", "syscall.SYS_FCNTL",
"syscall.SYS_FSTAT", "syscall.SYS_FUTEX", "syscall.SYS_GETDENTS64",
"syscall.SYS_OPEN", "syscall.SYS_MKDIRAT", "syscall.SYS_MKDIR"
// ... 50+ total syscalls allowed
]
// AFTER (Patched): Restricted to safer subset
allowed_syscalls = [
"syscall.SYS_NEWFSTATAT",
"syscall.SYS_LSEEK",
"syscall.SYS_GETDENTS64",
"syscall.SYS_CLOSE",
"syscall.SYS_FUTEX",
"syscall.SYS_MMAP",
"syscall.SYS_BRK",
// Significantly reduced syscall surface
]
Source: GitHub Commit Changes
Detection Methods for CVE-2025-49131
Indicators of Compromise
- Unexpected file access or modification patterns originating from fastgpt-sandbox container processes
- Anomalous syscall patterns including attempts to use SYS_EXECVE, SYS_OPEN, or SYS_MKDIR from sandbox processes
- Python module import attempts for restricted or unexpected libraries within sandbox execution contexts
- Log entries indicating sandbox boundary violations or permission denied errors followed by successful operations
Detection Strategies
- Implement container runtime security monitoring with syscall auditing to detect unauthorized syscall usage from sandbox containers
- Deploy file integrity monitoring (FIM) on host systems to detect unauthorized file modifications originating from container breakouts
- Configure application-level logging to track code execution requests and correlate with container activity
- Use behavioral analysis tools to identify anomalous sandbox escape patterns
Monitoring Recommendations
- Enable audit logging for all syscall activity within containerized FastGPT sandbox environments
- Monitor for outbound network connections or filesystem access patterns that deviate from expected sandbox behavior
- Configure alerting on any EPERM or EACCES errors followed by successful syscall completion in sandbox logs
- Review FastGPT workflow execution logs for suspicious code submissions or unusual execution patterns
How to Mitigate CVE-2025-49131
Immediate Actions Required
- Upgrade FastGPT to version 4.9.11 or later immediately, as this version contains the security patch
- Pull the latest fastgpt-sandbox container image from the official container registry
- Audit existing FastGPT deployments for any signs of exploitation or unauthorized file access
- Review workflow configurations and restrict code execution capabilities to trusted users only
Patch Information
The vulnerability has been addressed in FastGPT version 4.9.11. The fix significantly reduces the allowed syscall list from approximately 50+ calls to a minimal safe subset, removing dangerous filesystem and process management syscalls. Additionally, the patch includes improved error messaging to provide better visibility into blocked operations.
For detailed patch changes, refer to:
Workarounds
- If immediate patching is not possible, disable the sandbox code execution feature until the update can be applied
- Implement network segmentation to isolate FastGPT sandbox containers from sensitive systems
- Apply additional container runtime security policies (such as seccomp profiles or AppArmor) to restrict syscall access at the infrastructure level
- Limit sandbox access to trusted users and implement strict input validation on code submissions
# Configuration example - Updating FastGPT sandbox container
# Pull the patched sandbox container image
docker pull ghcr.io/labring/fastgpt-sandbox:v4.9.11
# Verify the container version
docker inspect ghcr.io/labring/fastgpt-sandbox:v4.9.11 | grep -i version
# Restart FastGPT services with the updated sandbox
docker-compose down && docker-compose up -d
Disclaimer: This content was generated using AI. While we strive for accuracy, please verify critical information with official sources.
