CVE-2024-7779 in danswer
Summary
by MITRE • 03/20/2025
A vulnerability in danswer-ai/danswer version 1 allows an attacker to perform a Regular Expression Denial of Service (ReDoS) by manipulating regular expressions. This can significantly slow down the application's response time and potentially render it completely unusable.
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Analysis
by VulDB Data Team • 03/20/2025
The vulnerability identified as CVE-2024-7779 represents a critical security flaw within the danswer-ai/danswer platform version 1, specifically targeting the application's handling of regular expressions. This issue manifests as a Regular Expression Denial of Service attack vector that can severely compromise system performance and availability. The vulnerability stems from inadequate input validation and sanitization mechanisms within the application's regex processing logic, creating an opportunity for malicious actors to exploit the system's computational resources through carefully crafted input sequences.
The technical implementation of this vulnerability involves the exploitation of poorly constructed regular expressions that can be manipulated by attackers to cause exponential backtracking during pattern matching operations. When an attacker submits maliciously formatted input data that triggers the vulnerable regex patterns, the system enters a state where the regular expression engine performs an excessive number of operations, leading to dramatic increases in processing time. This behavior aligns with the common characteristics of ReDoS attacks as defined by CWE-1321, which specifically addresses the weakness in regular expression implementations that allow for denial of service through input manipulation. The attack leverages the fundamental properties of regular expression engines where certain patterns can cause catastrophic backtracking when processing specific input strings.
The operational impact of CVE-2024-7779 extends beyond simple performance degradation to potentially complete system unavailability. Attackers can exploit this vulnerability to consume excessive CPU resources, causing legitimate requests to time out or fail, effectively creating a denial of service condition. The application's response times increase exponentially with the size and complexity of the malicious input, making it particularly dangerous in production environments where the system handles multiple concurrent requests. This vulnerability directly impacts the availability and reliability of the danswer-ai/danswer platform, potentially affecting critical search and information retrieval functionality that organizations depend upon for their AI-powered document processing workflows.
Mitigation strategies for this vulnerability should focus on implementing robust input validation and sanitization measures that prevent malicious regular expression patterns from being processed. Security practitioners should consider implementing rate limiting and input length restrictions to limit the impact of potential attacks. The application should be updated to use more secure regular expression libraries or implementations that are resistant to catastrophic backtracking. Additionally, implementing proper regex testing and validation procedures during the development lifecycle can help identify vulnerable patterns before deployment. Organizations should also consider implementing monitoring and alerting mechanisms to detect unusual processing patterns that may indicate an ongoing ReDoS attack. This vulnerability demonstrates the importance of following security best practices outlined in the ATT&CK framework for command and control activities, particularly in relation to maintaining system availability and preventing resource exhaustion attacks that can compromise the overall security posture of AI-powered platforms.