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Vulnerability Database/CVE-2024-50050

CVE-2024-50050: Llama Stack RCE Vulnerability

CVE-2024-50050 is a remote code execution flaw in Llama Stack caused by unsafe pickle serialization in socket communication. This post covers the technical details, affected versions, security impact, and mitigation.

Updated:

CVE-2024-50050 Overview

CVE-2024-50050 is an insecure deserialization vulnerability in Meta's Llama Stack that could allow remote code execution. The vulnerability exists because Llama Stack prior to revision 7a8aa775e5a267cf8660d83140011a0b7f91e005 used Python's pickle module as a serialization format for socket communication. The pickle module is well-documented as unsafe when processing untrusted data, as it can execute arbitrary code during the deserialization process.

Critical Impact

Attackers with low privileges could potentially achieve remote code execution by sending maliciously crafted pickle-serialized data through socket communications to vulnerable Llama Stack deployments.

Affected Products

  • Llama Stack prior to revision 7a8aa775e5a267cf8660d83140011a0b7f91e005

Discovery Timeline

  • 2024-10-23 - CVE-2024-50050 published to NVD
  • 2024-10-24 - Last updated in NVD database

Technical Details for CVE-2024-50050

Vulnerability Analysis

This vulnerability is classified as an insecure deserialization flaw. Python's pickle module is designed to serialize and deserialize Python object structures. However, it has a fundamental security limitation: during deserialization, pickle can instantiate arbitrary objects and call arbitrary functions. This means that a malicious actor can craft a pickle payload that, when deserialized, executes arbitrary Python code on the target system.

In the context of Llama Stack, the socket communication mechanism accepted pickle-serialized data, creating an attack surface where an authenticated attacker with network access could send malicious payloads to achieve code execution on systems running vulnerable versions of the software.

Root Cause

The root cause of this vulnerability is the use of Python's pickle module for deserializing data received over network sockets. The pickle module explicitly warns in its documentation that it should never be used to deserialize untrusted data due to its ability to execute arbitrary code during the unpickling process. The design decision to use pickle for inter-process or network communication introduced an inherent security risk.

Attack Vector

The attack vector is network-based and requires low privileges to exploit. An attacker would need to:

  1. Establish a socket connection to a vulnerable Llama Stack instance
  2. Craft a malicious pickle payload containing code to be executed
  3. Send the serialized payload through the socket communication channel
  4. The vulnerable application deserializes the payload, triggering code execution

The vulnerability mechanism relies on Python pickle's ability to execute arbitrary code during deserialization. When pickle.loads() processes a crafted payload, it can instantiate objects with malicious __reduce__ methods that execute system commands or arbitrary Python code. The fix involved replacing pickle serialization with JSON, which only supports basic data types and cannot execute code during parsing. For more technical details, see the Facebook Security Advisory.

Detection Methods for CVE-2024-50050

Indicators of Compromise

  • Unusual socket connections to Llama Stack services from unexpected sources
  • Anomalous process spawning or system command execution originating from Llama Stack processes
  • Network traffic containing binary pickle serialization signatures (typically starting with bytes \\x80\\x04 or similar pickle opcodes)

Detection Strategies

  • Monitor for unexpected child processes spawned by Llama Stack application processes
  • Implement network traffic analysis to detect pickle protocol signatures in socket communications
  • Review application logs for deserialization errors or unexpected object instantiations
  • Deploy endpoint detection to identify suspicious code execution patterns

Monitoring Recommendations

  • Enable verbose logging on Llama Stack deployments to capture socket communication metadata
  • Implement network segmentation to restrict access to Llama Stack socket interfaces
  • Set up alerting for any new outbound connections or command execution from Llama Stack processes
  • Monitor for signs of reconnaissance or exploitation attempts against AI/ML infrastructure

How to Mitigate CVE-2024-50050

Immediate Actions Required

  • Update Llama Stack to revision 7a8aa775e5a267cf8660d83140011a0b7f91e005 or later which uses JSON serialization instead of pickle
  • Restrict network access to Llama Stack socket interfaces to trusted hosts only
  • Implement network segmentation to isolate Llama Stack deployments from untrusted networks
  • Review application logs for any suspicious activity that may indicate prior exploitation attempts

Patch Information

Meta has addressed this vulnerability by changing the socket communication serialization format from pickle to JSON. The fix is available in Llama Stack revision 7a8aa775e5a267cf8660d83140011a0b7f91e005 and subsequent versions. JSON serialization only supports basic data types and cannot execute arbitrary code during parsing, effectively eliminating the deserialization attack vector.

For detailed patch information, refer to the Facebook Security Advisory.

Workarounds

  • If immediate patching is not possible, restrict network access to Llama Stack socket interfaces using firewall rules
  • Implement network-level authentication or VPN requirements for accessing Llama Stack services
  • Consider running Llama Stack in isolated container environments with restricted system call capabilities
  • Deploy application-level monitoring to detect and block suspicious deserialization attempts
bash
# Example: Restrict network access to Llama Stack socket interface
# Using iptables to limit access to trusted hosts only
iptables -A INPUT -p tcp --dport <llama_stack_port> -s <trusted_ip> -j ACCEPT
iptables -A INPUT -p tcp --dport <llama_stack_port> -j DROP

Disclaimer: This content was generated using AI. While we strive for accuracy, please verify critical information with official sources.

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