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CVE Vulnerability Database

CVE-2026-7183: UERANSIM RCE Vulnerability

CVE-2026-7183 is a remote code execution vulnerability in UERANSIM up to version 3.2.7 caused by an uncaught exception in the Radio Link Simulation Layer. This article covers technical details, affected versions, and mitigation.

Published:

CVE-2026-7183 Overview

A vulnerability has been discovered in aligungr UERANSIM, an open-source 5G UE and RAN (gNodeB) simulator commonly used for 5G network research and development. The affected element is the function rls::DecodeRlsMessage in the library src/lib/rls/rls_pdu.cpp of the Radio Link Simulation Layer. Manipulation of the pduLength argument leads to an uncaught exception, allowing remote attackers to cause a denial of service condition. This vulnerability is related to CVE-2024-37877.

Critical Impact

Remote attackers can exploit this uncaught exception vulnerability to disrupt 5G network simulation environments by sending crafted network packets targeting the Radio Link Simulation Layer, potentially halting research and development activities.

Affected Products

  • UERANSIM versions up to 3.2.7
  • Radio Link Simulation Layer component (src/lib/rls/rls_pdu.cpp)
  • 5G UE and RAN simulation environments using vulnerable UERANSIM versions

Discovery Timeline

  • 2026-04-27 - CVE-2026-7183 published to NVD
  • 2026-04-28 - Last updated in NVD database

Technical Details for CVE-2026-7183

Vulnerability Analysis

This vulnerability stems from improper exception handling (CWE-248: Uncaught Exception) in the UERANSIM Radio Link Simulation Layer. The rls::DecodeRlsMessage function fails to properly validate and handle the pduLength argument when processing incoming Protocol Data Units (PDUs). When a malformed PDU with an invalid length value is received, the function throws an exception that is not caught by any error handler, causing the application to terminate unexpectedly.

The Radio Link Simulation Layer is responsible for simulating radio link communication between User Equipment (UE) and the gNodeB in 5G network simulations. This makes the vulnerability particularly impactful for organizations using UERANSIM for 5G network research, testing, and development purposes.

Root Cause

The root cause is insufficient input validation and missing exception handling in the PDU decoding logic. The pduLength argument is not properly validated before being used in memory operations, and any resulting exceptions are not caught within the function or its callers. This allows a carefully crafted PDU with an invalid length to trigger an unhandled exception that propagates up the call stack and terminates the simulation process.

Attack Vector

The vulnerability can be exploited remotely over the network. An attacker can send specially crafted network packets containing malformed PDUs with manipulated pduLength values to a target UERANSIM instance. When the Radio Link Simulation Layer attempts to decode these malformed PDUs, the uncaught exception causes the simulation to crash, resulting in a denial of service.

The attack does not require authentication or user interaction, making it relatively straightforward to exploit. However, the impact is limited to availability; there is no evidence that this vulnerability allows for code execution or data compromise.

Detection Methods for CVE-2026-7183

Indicators of Compromise

  • Unexpected termination or crashes of UERANSIM processes without clear operational cause
  • Error logs showing uncaught exceptions originating from rls::DecodeRlsMessage or rls_pdu.cpp
  • Repeated crash/restart cycles of the Radio Link Simulation Layer component
  • Network traffic containing malformed PDUs with abnormal length values targeting UERANSIM instances

Detection Strategies

  • Monitor UERANSIM process stability and implement alerting for unexpected terminations
  • Implement network traffic analysis to identify packets with anomalous PDU length fields
  • Review application logs for exception messages related to PDU decoding operations
  • Deploy network intrusion detection rules to flag malformed RLS protocol traffic

Monitoring Recommendations

  • Enable verbose logging in UERANSIM to capture detailed error information before crashes
  • Implement process monitoring and automatic restart mechanisms to maintain service availability
  • Monitor network interfaces for unusual traffic patterns targeting simulation endpoints
  • Establish baseline metrics for normal UERANSIM operation to detect anomalous behavior

How to Mitigate CVE-2026-7183

Immediate Actions Required

  • Upgrade UERANSIM to version 3.2.8 or later immediately
  • Review network access controls to limit exposure of UERANSIM instances to trusted sources
  • Implement network segmentation to isolate 5G simulation environments from untrusted networks
  • Enable process monitoring to detect and alert on unexpected simulation crashes

Patch Information

The vulnerability has been addressed in UERANSIM version 3.2.8. The fix is available in commit ca1a66fffe282767bb08618af9f848e3b68ea47b. Organizations should upgrade to version 3.2.8 or later to remediate this vulnerability. The vendor responded professionally and released the fix promptly after being notified.

For detailed patch information, refer to:

Workarounds

  • Restrict network access to UERANSIM instances using firewall rules to allow only trusted IP addresses
  • Deploy UERANSIM behind a network gateway that can filter malformed packets
  • Implement network-level rate limiting to reduce the impact of potential denial of service attacks
  • Run UERANSIM instances in containerized environments with automatic restart policies to minimize downtime
bash
# Example: Restrict network access to UERANSIM using iptables
# Allow only trusted network (replace with your trusted IP range)
iptables -A INPUT -p udp --dport 38412 -s 10.0.0.0/24 -j ACCEPT
iptables -A INPUT -p udp --dport 38412 -j DROP

# Alternative: Use systemd to enable automatic restart on crash
# Add to /etc/systemd/system/ueransim.service
# [Service]
# Restart=always
# RestartSec=5

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

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