CVE-2026-110886 in Conversational Forms Plugin
Summary
by MITRE • 10/18/2026
Deserialization of Untrusted Data vulnerability in QuantumCloud Conversational Forms for ChatBot conversational-forms allows Object Injection.This issue affects Conversational Forms for ChatBot: from n/a through 1.5.1.
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Analysis
by VulDB Data Team • 10/18/2026
The identified vulnerability represents a critical security flaw within the QuantumCloud Conversational Forms component, specifically affecting versions ranging from initial releases up to version 1.5.1 of the plugin designed for chatbot integration. This issue is classified as an Object Injection vulnerability resulting from the deserialization of untrusted data. In software architecture, particularly in Java-based environments which are common for such plugins, object serialization allows complex objects to be converted into a byte stream for storage or transmission. The core technical flaw lies in the application's failure to validate or sanitize input data before it is passed through an insecure deserialization mechanism. When a chatbot receives user-generated content via conversational forms, this data is often processed and reconstructed into internal object structures. If the system blindly trusts these inputs without verifying their integrity or source, an attacker can craft malicious serialized payloads that exploit specific gadget chains within the application's classpath.
From a technical perspective, this vulnerability aligns with CWE-502, which denotes Deserialization of Untrusted Data. The danger arises because deserialized objects are instantiated and executed by the runtime environment. An adversary who controls the input stream can manipulate these objects to execute arbitrary code on the server hosting the chatbot service. This is not merely a data leakage issue but a potential Remote Code Execution (RCE) vector. By injecting malicious payloads, an attacker could bypass standard authentication mechanisms, escalate privileges within the application context, or pivot further into the internal network infrastructure where the QuantumCloud system resides. The impact extends beyond simple data corruption; it compromises the confidentiality, integrity, and availability of the entire chatbot ecosystem and potentially the underlying server operating system.
The operational impact is severe for organizations relying on this plugin for customer interaction or automated support services. Successful exploitation could allow an attacker to gain unauthorized access to sensitive backend systems, exfiltrate proprietary data processed by the chatbot, or disrupt service availability through denial-of-service conditions triggered by malformed object instantiation. Furthermore, because chatbots often handle personal identifiable information (PII) and other regulated data, this vulnerability poses significant compliance risks under frameworks such as GDPR or HIPAA if customer data is compromised during exploitation. The attack surface is broadened by the interactive nature of conversational forms, which inherently accept diverse user inputs that may be manipulated to trigger the deserialization flaw without requiring complex network-level interactions beyond standard HTTP requests.
Mitigation strategies must prioritize immediate remediation and defensive coding practices. The most effective solution is to upgrade the QuantumCloud Conversational Forms plugin to a version later than 1.5.1, where this vulnerability has presumably been patched by implementing strict input validation or replacing insecure deserialization methods with safer alternatives such as JSON parsing that does not execute arbitrary code during object reconstruction. For environments where upgrading is temporarily unfeasible, administrators should implement network-level controls such as web application firewalls to filter out known malicious serialization patterns and restrict outbound connections from the chatbot server to prevent post-exploitation command-and-control communications. Additionally, developers must adhere to secure coding standards that mandate whitelisting allowed classes during deserialization processes, ensuring that only expected data types are instantiated. Regular security audits and static code analysis tools should be employed to detect similar insecure patterns in future development cycles, aligning with ATT&CK techniques related to initial access via web applications and execution through command scripting or binary operations.