CVE-2026-23842 is a vulnerability classified under CWE-400 (Uncontrolled Resource Consumption) affecting the ChatterBot conversational AI framework developed by gunthercox. The issue exists in versions prior to 1.2.11 due to improper handling of database sessions and connection pools managed by SQLAlchemy. Specifically, the get_response() method, which processes user inputs to generate chatbot replies, can be invoked concurrently in a way that exhausts the available connections in the SQLAlchemy pool. Since the connection pool is not properly managed or replenished, this leads to resource starvation, causing the chatbot service to become unresponsive. Recovery from this denial-of-service condition requires a manual restart of the application or database connections, resulting in downtime. The vulnerability can be exploited remotely without any authentication or user interaction, making it accessible to unauthenticated attackers. While confidentiality and integrity of data are not compromised, the availability of the chatbot service is severely impacted. No public exploits have been reported yet, but the vulnerability has been assigned a CVSS 3.1 base score of 7.5, indicating a high severity level. The fix was introduced in ChatterBot version 1.2.11, which properly manages database connections to prevent exhaustion.

For European organizations, the primary impact of CVE-2026-23842 is service disruption due to denial-of-service conditions in applications using vulnerable ChatterBot versions. Organizations relying on conversational AI for customer support, internal automation, or user engagement may experience prolonged outages, leading to degraded user experience and potential loss of business continuity. Although no data breach or integrity compromise is involved, the unavailability of chatbot services can affect operational efficiency and customer satisfaction. In sectors such as finance, healthcare, and public services where chatbots are increasingly integrated, such disruptions could indirectly impact compliance and service-level agreements. Additionally, the need for manual intervention to restore service increases operational overhead and response times. The vulnerability’s ease of exploitation without authentication raises the risk of automated attacks targeting exposed chatbot endpoints, potentially amplifying the impact during peak usage periods.

The primary mitigation is to upgrade all instances of ChatterBot to version 1.2.11 or later, where the connection pool management issue is resolved. Organizations should audit their deployments to identify any use of vulnerable versions. Beyond patching, implement monitoring of database connection pools to detect abnormal exhaustion patterns early. Rate limiting or throttling concurrent requests to the get_response() API can reduce the risk of resource exhaustion. Employing web application firewalls (WAFs) to detect and block unusual traffic spikes targeting chatbot endpoints is advisable. Additionally, consider isolating chatbot services in containerized or sandboxed environments to limit the blast radius of potential denial-of-service attacks. Regularly review and update dependency libraries such as SQLAlchemy to benefit from performance and security improvements. Finally, establish incident response procedures to quickly restart services and restore availability if an attack occurs.