10.0 CRITICAL
- CVSS version (CVSS): 3.1
- Attack Vector (AV): Network (N)
- Attack Complexity (AC): Low (L)
- Privileges Required (PR): None (N)
- User Interaction (UI): None (N)
- Scope (S): Changed (C)
- Confidentiality (C): High (H)
- Integrity (I): High (H)
- Availability (A): High (H)
- Modified Attack Vector (MAV): Network (N)
- Modified Attack Complexity (MAC): Low (L)
- Modified Privileges Required (MPR): None (N)
- Modified User Interaction (MUI): None (N)
- Modified Confidentiality (MC): High (H)
- Modified Scope (MS): Changed (C)
- Modified Integrity (MI): High (H)
- Modified Availability (MA): High (H)
Activity log
- Created & dismissed (no matching packages found) suggestion
Langroid: Sandbox Escape to Remote Code Execution via Incomplete `eval()` Mitigation in TableChatAgent
Langroid is a framework for building large-language-model-powered applications. Versions prior to 0.65.2 are vulnerable to a critical Sandbox Escape leading to Remote Code Execution (RCE) in its `TableChatAgent` and `VectorStore` capabilities. When these agents evaluate LLM-generated tool messages with `full_eval=True`, they attempt to sandbox the execution by explicitly setting `locals` to an empty dictionary `{}` inside Python's `eval()` function. However, this relies on an incomplete understanding of Python's execution model. Because `__builtins__` is not explicitly scrubbed from the `globals` dictionary mapping, Python implicitly injects all built-ins during execution, granting full access to functions like `__import__('os').system()`. Since `TableChatAgent.pandas_eval()` executes external LLM outputs natively, this bypass permits any attacker providing prompt payload to achieve unauthenticated RCE on the host system. Version 0.65.2 patches the issue.
References
-
https://github.com/langroid/langroid/security/advisories/GHSA-q9p7-wqxg-mrhc x_refsource_CONFIRMexploit
Affected products
- ==< 0.65.2