The SentinelOne Annual Threat Report - A Defenders Guide from the FrontlinesThe SentinelOne Annual Threat ReportGet the Report
Experiencing a Breach?Blog
Get StartedContact Us
SentinelOne
  • Platform
    Platform Overview
    • Singularity Platform
      Welcome to Integrated Enterprise Security
    • AI for Security
      Leading the Way in AI-Powered Security Solutions
    • Securing AI
      Accelerate AI Adoption with Secure AI Tools, Apps, and Agents.
    • How It Works
      The Singularity XDR Difference
    • Singularity Marketplace
      One-Click Integrations to Unlock the Power of XDR
    • Pricing & Packaging
      Comparisons and Guidance at a Glance
    Data & AI
    • Purple AI
      Accelerate SecOps with Generative AI
    • Singularity Hyperautomation
      Easily Automate Security Processes
    • AI-SIEM
      The AI SIEM for the Autonomous SOC
    • Singularity Data Lake
      AI-Powered, Unified Data Lake
    • Singularity Data Lake for Log Analytics
      Seamlessly Ingest Data from On-Prem, Cloud or Hybrid Environments
    Endpoint Security
    • Singularity Endpoint
      Autonomous Prevention, Detection, and Response
    • Singularity XDR
      Native & Open Protection, Detection, and Response
    • Singularity RemoteOps Forensics
      Orchestrate Forensics at Scale
    • Singularity Threat Intelligence
      Comprehensive Adversary Intelligence
    • Singularity Vulnerability Management
      Application & OS Vulnerability Management
    • Singularity Identity
      Identity Threat Detection and Response
    Cloud Security
    • Singularity Cloud Security
      Block Attacks with an AI-Powered CNAPP
    • Singularity Cloud Native Security
      Secure Cloud and Development Resources
    • Singularity Cloud Workload Security
      Real-Time Cloud Workload Protection Platform
    • Singularity Cloud Data Security
      AI-Powered Threat Detection for Cloud Storage
    • Singularity Cloud Security Posture Management
      Detect and Remediate Cloud Misconfigurations
    Securing AI
    • Prompt Security
      Secure AI Tools Across Your Enterprise
  • Why SentinelOne?
    Why SentinelOne?
    • Why SentinelOne?
      Cybersecurity Built for What’s Next
    • Our Customers
      Trusted by the World’s Leading Enterprises
    • Industry Recognition
      Tested and Proven by the Experts
    • About Us
      The Industry Leader in Autonomous Cybersecurity
    Compare SentinelOne
    • Arctic Wolf
    • Broadcom
    • CrowdStrike
    • Cybereason
    • Microsoft
    • Palo Alto Networks
    • Sophos
    • Splunk
    • Trellix
    • Trend Micro
    • Wiz
    Verticals
    • Energy
    • Federal Government
    • Finance
    • Healthcare
    • Higher Education
    • K-12 Education
    • Manufacturing
    • Retail
    • State and Local Government
  • Services
    Managed Services
    • Managed Services Overview
      Wayfinder Threat Detection & Response
    • Threat Hunting
      World-Class Expertise and Threat Intelligence
    • Managed Detection & Response
      24/7/365 Expert MDR Across Your Entire Environment
    • Incident Readiness & Response
      DFIR, Breach Readiness, & Compromise Assessments
    Support, Deployment, & Health
    • Technical Account Management
      Customer Success with Personalized Service
    • SentinelOne GO
      Guided Onboarding & Deployment Advisory
    • SentinelOne University
      Live and On-Demand Training
    • Services Overview
      Comprehensive Solutions for Seamless Security Operations
    • SentinelOne Community
      Community Login
  • Partners
    Our Network
    • MSSP Partners
      Succeed Faster with SentinelOne
    • Singularity Marketplace
      Extend the Power of S1 Technology
    • Cyber Risk Partners
      Enlist Pro Response and Advisory Teams
    • Technology Alliances
      Integrated, Enterprise-Scale Solutions
    • SentinelOne for AWS
      Hosted in AWS Regions Around the World
    • Channel Partners
      Deliver the Right Solutions, Together
    • SentinelOne for Google Cloud
      Unified, Autonomous Security Giving Defenders the Advantage at Global Scale
    • Partner Locator
      Your Go-to Source for Our Top Partners in Your Region
    Partner Portal→
  • Resources
    Resource Center
    • Case Studies
    • Data Sheets
    • eBooks
    • Reports
    • Videos
    • Webinars
    • Whitepapers
    • Events
    View All Resources→
    Blog
    • Feature Spotlight
    • For CISO/CIO
    • From the Front Lines
    • Identity
    • Cloud
    • macOS
    • SentinelOne Blog
    Blog→
    Tech Resources
    • SentinelLABS
    • Ransomware Anthology
    • Cybersecurity 101
  • About
    About SentinelOne
    • About SentinelOne
      The Industry Leader in Cybersecurity
    • Investor Relations
      Financial Information & Events
    • SentinelLABS
      Threat Research for the Modern Threat Hunter
    • Careers
      The Latest Job Opportunities
    • Press & News
      Company Announcements
    • Cybersecurity Blog
      The Latest Cybersecurity Threats, News, & More
    • FAQ
      Get Answers to Our Most Frequently Asked Questions
    • DataSet
      The Live Data Platform
    • S Foundation
      Securing a Safer Future for All
    • S Ventures
      Investing in the Next Generation of Security, Data and AI
  • Pricing
Get StartedContact Us
CVE Vulnerability Database
Vulnerability Database/CVE-2026-23243

CVE-2026-23243: Linux Kernel Buffer Overflow Vulnerability

CVE-2026-23243 is a buffer overflow vulnerability in the Linux kernel RDMA/umad component that can trigger out-of-bounds memory access. This post explains its technical details, affected versions, and mitigation steps.

Published: March 20, 2026

CVE-2026-23243 Overview

A vulnerability has been identified in the Linux kernel's RDMA/umad subsystem where the ib_umad_write function fails to properly validate user-controlled input, allowing negative data_len values to propagate through to ib_create_send_mad(). This flaw can be exploited when there is a mismatch between the user MAD (Management Datagram) header size and the RMPP (Reliable Multi-Packet Transaction Protocol) header length, causing the padding calculation to exceed the segment size and trigger an out-of-bounds memory write in alloc_send_rmpp_list().

Critical Impact

Attackers with local access can trigger an out-of-bounds memory write in the kernel's RDMA subsystem, potentially leading to system crashes, denial of service, or arbitrary code execution in kernel context.

Affected Products

  • Linux Kernel (multiple versions with RDMA/umad support)
  • Systems with InfiniBand/RDMA hardware and drivers enabled
  • Linux distributions using vulnerable kernel versions

Discovery Timeline

  • 2026-03-18 - CVE CVE-2026-23243 published to NVD
  • 2026-03-18 - Last updated in NVD database

Technical Details for CVE-2026-23243

Vulnerability Analysis

The vulnerability resides in the ib_umad_write function within the Linux kernel's RDMA user MAD (Management Datagram) interface. This function is responsible for handling write operations to the /dev/infiniband/umad* device files, which provide userspace applications with access to InfiniBand management interfaces.

The core issue is an integer underflow vulnerability that occurs during the calculation of data_len. This value is computed by subtracting header sizes from a user-controlled count parameter. When a specially crafted request provides a mismatched combination of user MAD header size and RMPP header length, the arithmetic can result in a negative data_len value.

Since C handles signed integers, this negative value is passed to ib_create_send_mad() where it is used in subsequent memory operations. The KASAN (Kernel Address Sanitizer) output confirms that this leads to an out-of-bounds write of 220 bytes in the alloc_send_rmpp_list() function, where the padding calculation exceeds valid segment boundaries.

The vulnerability was detected via KASAN instrumentation, which reported a slab-out-of-bounds write condition triggered by user threads interacting with the vulnerable code path.

Root Cause

The root cause is improper input validation in the ib_umad_write function. The code computes data_len from user-provided values without checking whether the result becomes negative before using it in memory allocation and copy operations. The signed integer representation allows negative values to pass through unchecked, eventually corrupting adjacent memory regions when used as a size parameter in memory operations.

Attack Vector

An attacker with local access to a system with InfiniBand/RDMA hardware enabled can exploit this vulnerability by:

  1. Opening the /dev/infiniband/umad* device file (requires appropriate permissions)
  2. Crafting a write request with carefully chosen MAD header size and RMPP header length values
  3. Triggering the integer underflow condition that produces a negative data_len
  4. Causing an out-of-bounds write in kernel memory via ib_create_send_mad()

The attack requires local access to a system with RDMA capabilities enabled. The KASAN stack trace shows the exploitation path through ib_umad_write → ib_create_send_mad, confirming the vulnerability mechanism.

Detection Methods for CVE-2026-23243

Indicators of Compromise

  • KASAN kernel log messages reporting "slab-out-of-bounds" writes in ib_create_send_mad or alloc_send_rmpp_list
  • Kernel panic or oops messages originating from RDMA/umad code paths
  • Unexpected system crashes on systems with active InfiniBand/RDMA workloads
  • Unusual access patterns to /dev/infiniband/umad* device files

Detection Strategies

  • Enable KASAN (Kernel Address Sanitizer) on development and testing systems to detect memory corruption attempts
  • Monitor kernel logs for RDMA-related error messages and stack traces
  • Implement audit rules for access to /dev/infiniband/umad* device files
  • Deploy kernel live patching solutions to detect and block exploitation attempts

Monitoring Recommendations

  • Configure syslog forwarding for kernel messages containing "KASAN", "slab-out-of-bounds", or "ib_umad" keywords
  • Implement file access monitoring on InfiniBand management interfaces
  • Deploy endpoint detection solutions capable of identifying kernel memory corruption patterns
  • Review audit logs for suspicious RDMA-related system calls

How to Mitigate CVE-2026-23243

Immediate Actions Required

  • Apply the kernel security patches available from the official Linux kernel Git repository
  • Restrict access to /dev/infiniband/umad* device files to only necessary users and applications
  • Consider disabling RDMA/umad kernel module on systems where InfiniBand functionality is not required
  • Enable KASAN on non-production systems to detect exploitation attempts

Patch Information

The Linux kernel maintainers have released patches to address this vulnerability. The fix adds an explicit check to reject negative data_len values before creating the send buffer in ib_umad_write. Multiple commits have been backported to stable kernel branches:

  • Kernel Git Commit 1371ef6
  • Kernel Git Commit 205955f
  • Kernel Git Commit 362e45f
  • Kernel Git Commit 52ab82c
  • Kernel Git Commit 5551b02
  • Kernel Git Commit 6eb2919
  • Kernel Git Commit 9c80d68
  • Kernel Git Commit a6a3e4a

Workarounds

  • Unload the ib_umad kernel module if InfiniBand user-space management is not required: modprobe -r ib_umad
  • Blacklist the module to prevent automatic loading by adding blacklist ib_umad to /etc/modprobe.d/blacklist.conf
  • Restrict device file permissions to root-only access: chmod 600 /dev/infiniband/umad*
  • Use SELinux or AppArmor policies to limit which processes can access RDMA device files
bash
# Configuration example
# Disable ib_umad module loading
echo "blacklist ib_umad" >> /etc/modprobe.d/blacklist-rdma.conf

# Remove module if currently loaded
modprobe -r ib_umad

# Restrict device file permissions (if module must remain loaded)
chmod 600 /dev/infiniband/umad*

# Update module dependencies
depmod -a

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

  • Vulnerability Details
  • TypeBuffer Overflow

  • Vendor/TechLinux Kernel

  • SeverityNONE

  • CVSS ScoreN/A

  • EPSS Probability0.03%

  • Known ExploitedNo
  • Impact Assessment
  • ConfidentialityNone
  • IntegrityNone
  • AvailabilityNone
  • Technical References
  • Kernel Git Commit 1371ef6

  • Kernel Git Commit 205955f

  • Kernel Git Commit 362e45f

  • Kernel Git Commit 52ab82c

  • Kernel Git Commit 5551b02

  • Kernel Git Commit 6eb2919

  • Kernel Git Commit 9c80d68

  • Kernel Git Commit a6a3e4a
  • Related CVEs
  • CVE-2026-23448: Linux Kernel Buffer Overflow Vulnerability

  • CVE-2026-23447: Linux Kernel Buffer Overflow Vulnerability

  • CVE-2026-31395: Linux Kernel Buffer Overflow Vulnerability

  • CVE-2026-31402: Linux Kernel Buffer Overflow Vulnerability
Default Legacy - Prefooter | Experience the World’s Most Advanced Cybersecurity Platform

Experience the World’s Most Advanced Cybersecurity Platform

See how our intelligent, autonomous cybersecurity platform can protect your organization now and into the future.

Try SentinelOne
  • Get Started
  • Get a Demo
  • Product Tour
  • Why SentinelOne
  • Pricing & Packaging
  • FAQ
  • Contact
  • Contact Us
  • Customer Support
  • SentinelOne Status
  • Language
  • Platform
  • Singularity Platform
  • Singularity Endpoint
  • Singularity Cloud
  • Singularity AI-SIEM
  • Singularity Identity
  • Singularity Marketplace
  • Purple AI
  • Services
  • Wayfinder TDR
  • SentinelOne GO
  • Technical Account Management
  • Support Services
  • Verticals
  • Energy
  • Federal Government
  • Finance
  • Healthcare
  • Higher Education
  • K-12 Education
  • Manufacturing
  • Retail
  • State and Local Government
  • Cybersecurity for SMB
  • Resources
  • Blog
  • Labs
  • Case Studies
  • Videos
  • Product Tours
  • Events
  • Cybersecurity 101
  • eBooks
  • Webinars
  • Whitepapers
  • Press
  • News
  • Ransomware Anthology
  • Company
  • About Us
  • Our Customers
  • Careers
  • Partners
  • Legal & Compliance
  • Security & Compliance
  • Investor Relations
  • S Foundation
  • S Ventures

©2026 SentinelOne, All Rights Reserved.

Privacy Notice Terms of Use

English