Skip to main content
Vulnerability Database/CVE-2024-26581

CVE-2024-26581: Linux Kernel Netfilter GC Vulnerability

CVE-2024-26581 is a netfilter garbage collection flaw in the Linux kernel that affects rbtree interval handling. This article covers the technical details, affected Debian Linux versions, and mitigation steps.

Published:

CVE-2024-26581 Overview

CVE-2024-26581 is a vulnerability in the Linux kernel's netfilter subsystem, specifically within the nft_set_rbtree component. The flaw occurs during the lazy garbage collection (GC) process on insert operations, where an end interval element that has been added in the current transaction may be incorrectly collected before it becomes active. This race condition in the rbtree set implementation can lead to memory corruption and potential privilege escalation.

Critical Impact

Local attackers with low privileges can potentially exploit this kernel vulnerability to achieve high impact on system confidentiality, integrity, and availability, potentially leading to privilege escalation or system compromise.

Affected Products

  • Linux Kernel (multiple versions)
  • Debian Linux 10.0

Discovery Timeline

  • February 20, 2024 - CVE-2024-26581 published to NVD
  • October 1, 2025 - Last updated in NVD database

Technical Details for CVE-2024-26581

Vulnerability Analysis

The vulnerability resides in the nft_set_rbtree module of the Linux kernel's netfilter framework. The netfilter subsystem uses red-black trees (rbtree) to manage sets of network filtering rules, which can include interval-based matching. The nft_set_rbtree implementation includes a lazy garbage collection mechanism that runs during element insertion to clean up expired or invalidated entries.

The core issue is a synchronization problem where the garbage collection routine fails to properly check whether an end interval element is currently active before attempting to collect it. When a new interval is being added to the set during a transaction, the end element marker may be temporarily in a pending state. If the GC runs at this moment during an insert operation, it can mistakenly identify this pending end interval element as garbage and remove it.

This premature removal corrupts the interval representation in the rbtree, potentially causing subsequent netfilter operations to access freed memory or operate on an inconsistent data structure.

Root Cause

The root cause is insufficient validation in the garbage collection code path. The lazy GC mechanism on insert was not checking whether end interval elements were in an active state before collecting them. Elements added within an ongoing transaction are not yet active (they become active upon transaction commit), but the GC did not account for this transactional state when determining collectability.

The fix introduces a check to skip end interval elements that are not yet active, ensuring that newly added elements within a transaction are protected from premature garbage collection.

Attack Vector

This vulnerability requires local access to the system. An attacker with low-level privileges can potentially trigger the race condition by:

  1. Manipulating netfilter set operations through the nftables interface
  2. Creating conditions where garbage collection runs during interval insertions
  3. Exploiting the resulting memory corruption for privilege escalation

The attack does not require user interaction and can be performed by a local unprivileged user who has the ability to configure netfilter rules or interact with the nftables subsystem.

The vulnerability manifests in the nft_set_rbtree garbage collection path during insert operations. The fix adds a check to skip end interval elements that are not yet active, preventing premature collection. See the kernel commit c60d2529 for the patch implementation details.

Detection Methods for CVE-2024-26581

Indicators of Compromise

  • Unexpected kernel panics or crashes related to netfilter or nftables operations
  • Memory corruption errors in kernel logs referencing nft_set_rbtree or netfilter components
  • System instability when performing nftables rule modifications with interval sets

Detection Strategies

  • Monitor kernel logs for oops messages or warnings from the netfilter subsystem
  • Implement kernel crash dump analysis to identify exploitation attempts targeting nft_set_rbtree
  • Use kernel debugging tools to trace nftables operations for anomalous garbage collection behavior

Monitoring Recommendations

  • Enable audit logging for nftables configuration changes
  • Monitor for unusual privilege escalation attempts following netfilter operations
  • Deploy endpoint detection solutions capable of monitoring kernel-level activity

How to Mitigate CVE-2024-26581

Immediate Actions Required

  • Update the Linux kernel to a patched version immediately on all affected systems
  • Review systems for signs of compromise if exploitation is suspected
  • Restrict access to nftables configuration to trusted administrators only

Patch Information

Multiple kernel patches have been released to address this vulnerability across different kernel branches. The fix ensures that the garbage collection routine skips end interval elements that are not yet active within a transaction.

Official patches are available through:

Debian users should refer to the Debian LTS Announcement for distribution-specific updates.

Workarounds

  • Limit access to nftables/netfilter configuration to root or trusted users only
  • Consider disabling interval sets in nftables if not required for your use case
  • Apply kernel live patching solutions if available for your distribution until a full reboot with patched kernel is possible
bash
# Check current kernel version
uname -r

# Update kernel on Debian-based systems
sudo apt update && sudo apt upgrade linux-image-$(uname -r)

# Verify nftables module status
lsmod | grep nft

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

Experience the Most Advanced Cybersecurity Platform

See how the world’s most intelligent, autonomous cybersecurity platform can protect your organization today and into the future.