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C3 AI 8.12 Patch Notes

Last updated: November 9, 2026

The following document identifies known issues, known CVEs, and patch fixes in the C3 AI Platform 8.12 release (all these patches are backwards compatible).

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8.12.0 Known Common Vulnerabilities and Exposures (CVE)

C3 AI has accounted for all critical vulnerabilities and maintains a stringent internal patching policy. At this time, there are no critical vulnerabilities for C3 AI developed code. For open-source code vulnerabilities (CVEs), Critical and High issues are patched once fixes are available. In the interim, C3 AI provides mitigation remedies and statements as part of the patch notes. Vulnerabilities in open-source and third-party containers are remediated when new versions addressing the vulnerabilities are available and have been tested internally.

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General CVEs

CVE ID	Problem Title	C3 AI Severity Rating	Mitigation Statement
CVE-2025-55131	A flaw in Node.js's buffer allocation logic can expose uninitialized memory when allocations are interrupted, when using the vm module with the timeout option.	High	Expand Data leakage in C3-built containers occurs when sensitive information is exposed through improper access controls, insufficient encryption, or misconfigured data handling pathways. Such exposure can result in unauthorized access to application data, credentials, or internal system state. The C3 AI Platform addresses data leakage risks in C3-built containers through layered security controls: * Application-Level Encryption: Sensitive fields are protected using @PII(encrypt=true) annotations, enforcing encryption at the data model level independently of transport mechanisms. * Vault-Based Key Management: Secrets and credentials are centrally managed via C3 Vault, ensuring encrypted storage and scoped access. * Role-Based Access Control (RBAC): Enforces least-privilege principles to restrict access to sensitive data and operations. * Network Segmentation: Containers reside in isolated execution environments with network access control lists (NACLs) and cloud provider security groups, minimizing lateral movement and data exposure. * Encrypted Communications: All service-to-service communication is authenticated and encrypted, preventing interception or exfiltration of data in transit. * Web Application Firewall (WAF): Filters requests targeting data extraction endpoints and blocks common exfiltration techniques. * Audit Logging and Real-Time Telemetry: Provide visibility into data access patterns and anomalous flows, enabling rapid detection of leakage attempts. These controls collectively ensure that sensitive data within C3-built containers remains protected against unauthorized access and exfiltration, preserving confidentiality across operational environments.
CVE-2026-97687	urllib3: HTTPS proxy TLS configuration may be ignored or overridden	High	Expand TLS and transport-layer weaknesses can contribute to network-interface spoofing, downgrade, or leakage when peers cannot reliably authenticate endpoints or when sensitive traffic crosses trust boundaries without consistent encryption and policy enforcement. The C3 AI Platform reduces exposure by encrypting service-to-service and client-facing traffic using TLS where applicable, enforcing RBAC and least-privilege access at API boundaries, and segmenting workloads so compromise of one interface cannot broadly impersonate platform services. Web Application Firewall (WAF) and reverse-proxy configurations apply consistent TLS policies where those components are present, while audit logging and telemetry monitor for anomalous connection patterns. Vault-based key management and application-level encryption further protect secrets and credentials used to establish trusted channels. These controls collectively limit the practical impact of TLS-adjacent weaknesses within the C3 AI Platform environment.
CVE-2026-101905	Axios: Node HTTP adapter prototype-pollution gadget allows request socket hijack via inherited createConnection	High	Expand Data leakage in C3-built containers occurs when sensitive information is exposed through improper access controls, insufficient encryption, or misconfigured data handling pathways. Such exposure can result in unauthorized access to application data, credentials, or internal system state. The C3 AI Platform addresses data leakage risks in C3-built containers through layered security controls: * Application-Level Encryption: Sensitive fields are protected using @PII(encrypt=true) annotations, enforcing encryption at the data model level independently of transport mechanisms. * Vault-Based Key Management: Secrets and credentials are centrally managed via C3 Vault, ensuring encrypted storage and scoped access. * Role-Based Access Control (RBAC): Enforces least-privilege principles to restrict access to sensitive data and operations. * Network Segmentation: Containers reside in isolated execution environments with network access control lists (NACLs) and cloud provider security groups, minimizing lateral movement and data exposure. * Encrypted Communications: All service-to-service communication is authenticated and encrypted, preventing interception or exfiltration of data in transit. * Web Application Firewall (WAF): Filters requests targeting data extraction endpoints and blocks common exfiltration techniques. * Audit Logging and Real-Time Telemetry: Provide visibility into data access patterns and anomalous flows, enabling rapid detection of leakage attempts. These controls collectively ensure that sensitive data within C3-built containers remains protected against unauthorized access and exfiltration, preserving confidentiality across operational environments.