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Vulnerability Database/CVE-2024-37288

CVE-2024-37288: Elastic Kibana RCE Vulnerability

CVE-2024-37288 is a deserialization RCE flaw in Elastic Kibana affecting users with AI Security tools and Amazon Bedrock connectors. This article covers technical details, affected versions, impact, and mitigation.

Updated:

CVE-2024-37288 Overview

CVE-2024-37288 is an insecure deserialization vulnerability in Elastic Kibana that can lead to arbitrary code execution when Kibana attempts to parse a YAML document containing a crafted payload. This vulnerability specifically affects users utilizing Elastic Security's built-in AI tools who have configured an Amazon Bedrock connector.

Critical Impact

Successful exploitation allows attackers with low privileges to achieve arbitrary code execution on Kibana servers through malicious YAML payloads, potentially leading to complete system compromise.

Affected Products

  • Elastic Kibana 8.15.0
  • Kibana installations using Elastic Security's built-in AI tools
  • Configurations with Amazon Bedrock connector enabled

Discovery Timeline

  • 2024-09-09 - CVE-2024-37288 published to NVD
  • 2024-09-16 - Last updated in NVD database

Technical Details for CVE-2024-37288

Vulnerability Analysis

This vulnerability stems from CWE-502 (Deserialization of Untrusted Data), a well-known class of security flaws that occurs when applications deserialize data from untrusted sources without proper validation. In the context of Kibana, the application fails to safely handle YAML documents that may contain malicious constructs.

YAML deserialization vulnerabilities are particularly dangerous because YAML parsers often support object instantiation and code execution features. When a crafted YAML document is processed, attackers can leverage these features to instantiate arbitrary objects or execute code within the application's context.

The attack requires network access and low-level authentication, but no user interaction is needed once the attacker has established connectivity. The vulnerability affects the confidentiality, integrity, and availability of the affected system, as successful exploitation grants the attacker code execution capabilities.

Root Cause

The root cause lies in Kibana's YAML parsing implementation within the Elastic Security AI tools feature. When processing YAML documents, particularly in the context of Amazon Bedrock connector integration, the parser does not adequately validate or sanitize the document structure before deserialization. This allows attackers to craft YAML documents containing malicious type tags or object instantiation directives that execute arbitrary code during the parsing phase.

Attack Vector

The attack is conducted over the network against Kibana instances that have both Elastic Security's AI tools enabled and an Amazon Bedrock connector configured. An attacker with low-privilege access can submit a specially crafted YAML document to the vulnerable parsing endpoint. When Kibana processes this document, the malicious payload is deserialized and executed, granting the attacker code execution capabilities on the server.

The exploitation chain typically involves:

  1. Identifying a Kibana instance with the vulnerable configuration
  2. Crafting a YAML payload with malicious type tags or object instantiation
  3. Submitting the payload through an interface that triggers YAML parsing
  4. Achieving code execution when the payload is deserialized

Detection Methods for CVE-2024-37288

Indicators of Compromise

  • Unusual YAML documents containing suspicious type tags or object instantiation directives submitted to Kibana
  • Unexpected process spawning from the Kibana Node.js process
  • Anomalous network connections originating from the Kibana server
  • Evidence of code execution artifacts in Kibana logs or system audit logs

Detection Strategies

  • Monitor Kibana application logs for errors or anomalies related to YAML parsing operations
  • Implement network-based detection for malformed or suspicious YAML payloads targeting Kibana endpoints
  • Deploy endpoint detection and response (EDR) solutions to identify unexpected code execution from the Kibana process
  • Enable audit logging on Kibana servers to track API requests to AI tools and Bedrock connector endpoints

Monitoring Recommendations

  • Enable verbose logging for Elastic Security AI tools interactions
  • Monitor for unusual Amazon Bedrock connector activity patterns
  • Implement alerting on any YAML parsing exceptions or errors in Kibana logs
  • Track process creation events from the Kibana service account

How to Mitigate CVE-2024-37288

Immediate Actions Required

  • Upgrade to Kibana version 8.15.1 or later immediately
  • If immediate patching is not possible, disable the Amazon Bedrock connector temporarily
  • Review access controls to ensure only authorized users can interact with Elastic Security AI tools
  • Audit recent Kibana logs for any suspicious YAML parsing activity

Patch Information

Elastic has released Kibana 8.15.1 which addresses this vulnerability. The security update is documented in Elastic Security Advisory ESA-2024-27. Organizations should prioritize upgrading to this version to remediate the vulnerability.

Workarounds

  • Disable the Amazon Bedrock connector if it is not critical for operations until patching is complete
  • Restrict network access to Kibana to only trusted sources using firewall rules
  • Implement additional authentication requirements for accessing Elastic Security AI tools
  • Consider temporarily disabling Elastic Security's AI tools feature if upgrading is delayed
bash
# Verify Kibana version to ensure patch is applied
/usr/share/kibana/bin/kibana --version

# Check if Amazon Bedrock connector is configured (review kibana.yml)
grep -i "bedrock" /etc/kibana/kibana.yml

# Restrict access to Kibana in firewall (example for iptables)
iptables -A INPUT -p tcp --dport 5601 -s trusted_network/24 -j ACCEPT
iptables -A INPUT -p tcp --dport 5601 -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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