CVE-2024-7779 is a vulnerability identified in the danswer-ai/danswer product, specifically related to inefficient regular expression complexity (CWE-1333). This flaw allows an attacker to craft malicious input that triggers excessive backtracking in the application's regex engine, causing a Regular Expression Denial of Service (ReDoS). The vulnerability exists in version 1 of the software, with unspecified affected versions, and does not require any privileges or user interaction to exploit. The attack vector is network-based, meaning an attacker can send specially crafted requests remotely to degrade or halt the application's response capabilities. The CVSS 3.0 score of 7.5 reflects a high severity, primarily due to the impact on availability (denial of service) without affecting confidentiality or integrity. No patches or fixes have been linked yet, and no known exploits have been reported in the wild, but the vulnerability's nature makes it a significant risk for service reliability. The issue stems from inefficient regex patterns that can be manipulated to cause exponential processing delays, a common problem in applications that rely heavily on user-supplied input for pattern matching or search functionalities. Organizations using danswer-ai/danswer for AI-driven data querying or analysis should prioritize identifying vulnerable instances and applying mitigations to avoid service disruption.

The primary impact of CVE-2024-7779 is on the availability of the danswer-ai/danswer application. Exploitation can cause severe performance degradation or complete denial of service, disrupting business operations that depend on this software for AI-based data querying or analysis. For European organizations, this could mean downtime in critical AI services, leading to operational delays, reduced productivity, and potential financial losses. Since the vulnerability does not affect confidentiality or integrity, data breaches or unauthorized data modifications are not a direct concern. However, service unavailability can indirectly affect customer trust and compliance with service-level agreements. The lack of required authentication and user interaction increases the risk of widespread exploitation if the software is exposed to untrusted networks. Industries in Europe that rely heavily on AI and data analytics, such as finance, healthcare, and manufacturing, may face significant operational risks if their deployments of danswer-ai/danswer are vulnerable.

1. Monitor for official patches or updates from the danswer-ai project and apply them promptly once available. 2. Until patches are released, implement input validation and sanitization to restrict or reject inputs that could trigger complex regex evaluation, focusing on limiting input length and disallowing suspicious patterns. 3. Review and optimize regular expressions used within the application to reduce backtracking and complexity, potentially replacing vulnerable regex constructs with safer alternatives. 4. Employ Web Application Firewalls (WAFs) or Intrusion Prevention Systems (IPS) with rules designed to detect and block ReDoS attack patterns targeting regex processing. 5. Limit network exposure of the danswer-ai/danswer service by restricting access to trusted IPs or internal networks only. 6. Monitor application performance metrics and logs for unusual spikes in processing time or resource consumption indicative of ReDoS attempts. 7. Conduct regular security assessments and fuzz testing focused on input handling to identify and remediate similar vulnerabilities proactively.