CVE-2024-41874 Overview
CVE-2024-41874 is a critical Insecure Deserialization vulnerability affecting Adobe ColdFusion versions 2023.9, 2021.15 and earlier. This vulnerability allows remote attackers to execute arbitrary code in the context of the current user by providing crafted input to the application. When the malicious input is deserialized by the ColdFusion server, it leads to the execution of attacker-controlled code. Notably, exploitation of this vulnerability does not require any user interaction, making it particularly dangerous for exposed ColdFusion installations.
Critical Impact
Remote attackers can achieve arbitrary code execution on vulnerable ColdFusion servers without authentication or user interaction, potentially leading to complete system compromise.
Affected Products
- Adobe ColdFusion 2023 (all versions through Update 9)
- Adobe ColdFusion 2021 (all versions through Update 15)
- Earlier unsupported versions of Adobe ColdFusion
Discovery Timeline
- September 13, 2024 - CVE-2024-41874 published to NVD
- September 13, 2024 - Last updated in NVD database
Technical Details for CVE-2024-41874
Vulnerability Analysis
This vulnerability stems from the improper handling of serialized data within Adobe ColdFusion. When the application receives serialized objects from untrusted sources, it fails to adequately validate or sanitize the data before deserializing it. This allows an attacker to craft a malicious serialized object that, when processed by the ColdFusion server, triggers the execution of arbitrary code.
The attack can be performed remotely over the network without requiring any privileges or user interaction. Successful exploitation grants the attacker the ability to execute commands with the same privileges as the ColdFusion service, which typically runs with elevated system permissions. This could result in complete compromise of confidentiality, integrity, and availability of the affected system and any data it processes.
Root Cause
The root cause of CVE-2024-41874 is classified as CWE-502: Deserialization of Untrusted Data. ColdFusion's handling of serialized Java objects does not properly validate the class types and object graphs being deserialized. This allows attackers to inject malicious object chains (commonly known as "gadget chains") that leverage existing classes in the application's classpath to achieve code execution during the deserialization process.
Attack Vector
The attack vector for this vulnerability is network-based, requiring no authentication or user interaction. An attacker can exploit this vulnerability by sending specially crafted HTTP requests containing malicious serialized data to endpoints that process serialized objects. The ColdFusion server's deserialization routines will process the malicious payload, instantiating attacker-controlled object graphs that execute arbitrary commands upon reconstruction.
Common attack scenarios include targeting ColdFusion's built-in administrative interfaces, custom application endpoints that accept serialized data, or any component that processes user-controllable serialized input. The lack of authentication requirements means any network-accessible ColdFusion installation is at risk.
Detection Methods for CVE-2024-41874
Indicators of Compromise
- Unusual outbound network connections from ColdFusion server processes
- Unexpected process spawning by coldfusion.exe or ColdFusion Java processes
- Presence of unfamiliar serialized data patterns in HTTP request logs, particularly containing known Java gadget chain class names
- Suspicious file creation or modification in ColdFusion installation directories
- Anomalous system commands executed under the ColdFusion service account context
Detection Strategies
- Monitor HTTP traffic for requests containing serialized Java object signatures (0xaced0005 magic bytes or base64-encoded equivalents)
- Implement web application firewall (WAF) rules to detect and block known Java deserialization attack patterns
- Enable verbose logging on ColdFusion servers and analyze logs for deserialization-related exceptions or errors
- Deploy endpoint detection solutions to monitor for suspicious child process creation by ColdFusion services
Monitoring Recommendations
- Configure SIEM rules to alert on ColdFusion processes initiating network connections to unexpected external hosts
- Establish baseline behavior for ColdFusion servers and alert on deviations in process execution patterns
- Monitor for modifications to critical ColdFusion configuration files and directories
- Implement network segmentation and monitor traffic between ColdFusion servers and internal resources
How to Mitigate CVE-2024-41874
Immediate Actions Required
- Update Adobe ColdFusion 2023 to Update 10 or later immediately
- Update Adobe ColdFusion 2021 to Update 16 or later immediately
- If immediate patching is not possible, restrict network access to ColdFusion servers to trusted IP ranges only
- Review and disable any unnecessary ColdFusion services or endpoints that may accept serialized data
Patch Information
Adobe has released security updates to address this vulnerability as documented in security bulletin APSB24-71. Organizations should apply the appropriate update for their ColdFusion version:
- ColdFusion 2023: Apply Update 10 or later
- ColdFusion 2021: Apply Update 16 or later
Patches should be applied through Adobe's standard update mechanism or downloaded directly from the Adobe ColdFusion Security Advisory.
Workarounds
- Implement strict network access controls to limit connectivity to ColdFusion servers from untrusted networks
- Deploy a web application firewall (WAF) with rules to block serialized Java object payloads in HTTP requests
- Consider placing ColdFusion servers behind a reverse proxy that can inspect and filter incoming requests
- Disable or restrict access to administrative interfaces and any endpoints known to process serialized data
# Example: Restrict ColdFusion admin access via IP in Apache
<Location "/CFIDE/administrator">
Require ip 10.0.0.0/8
Require ip 192.168.0.0/16
</Location>
Disclaimer: This content was generated using AI. While we strive for accuracy, please verify critical information with official sources.


