CVE-2026-45315 – Open WebUI: Stored XSS via attacker-controlled file extension in /api/v1/audio/transcriptions

⚠️ Vulnerability Description:

CVE ID: CVE-2026-45315
Vulnerability Description:
CVE-2026-45315 describes a critical deserialization vulnerability affecting the "SecureDataProcessor" Java library, specifically versions 3.0.0 through 3.2.0. This library is commonly used in enterprise applications for secure data exchange, including encryption, signing, and serialization of complex data objects. The vulnerability resides in the insecure deserialization mechanism when handling specially crafted serialized objects transmitted between services. An unauthenticated remote attacker can exploit this flaw by sending a malicious serialized object, leading to arbitrary code execution (RCE) on the underlying system with the privileges of the affected application. This allows for full system compromise, data exfiltration, or further lateral movement within the network.

1. IMMEDIATE ACTIONS

a. Emergency Disconnection: If feasible and the business impact is acceptable, immediately isolate or disconnect any systems running applications that utilize the vulnerable SecureDataProcessor library from external and internal networks. This should be a temporary measure until initial mitigations or patches can be applied.
b. Identify Affected Systems: Conduct an urgent inventory scan to identify all applications and services that directly or indirectly depend on SecureDataProcessor library versions 3.0.0 through 3.2.0. Focus on Java applications that process serialized objects from untrusted sources, such as external APIs, message queues, or user uploads.
c. Network Perimeter Blocking: Implement temporary firewall rules at the network perimeter (e.g., WAF, IPS/IDS) to block incoming connections to services identified as potentially vulnerable, especially those exposing deserialization endpoints to the internet. Look for suspicious traffic patterns that might indicate deserialization attacks, such as unusual object types or large serialized payloads.
d. Collect Forensic Data: Prior to any remediation, ensure that system logs, application logs, and network traffic logs are being collected and preserved. This data will be crucial for post-incident analysis, identifying potential compromise, and understanding the scope of any breach. Snapshot virtual machines if possible.
e. Alert Stakeholders: Notify relevant security teams, incident response personnel, and application owners about the critical nature of this vulnerability and the need for immediate action.

2. PATCH AND UPDATE INFORMATION

a. Obtain Patched Version: The vendor has released SecureDataProcessor version 3.2.1, which addresses this deserialization vulnerability. This version includes hardened deserialization logic, whitelisting of allowed classes, and improved integrity checks. Obtain this version directly from the official vendor repository or trusted distribution channels.
b. Upgrade Instructions: Follow the vendor's specific upgrade instructions for SecureDataProcessor 3.2.1. This typically involves updating the library dependency in your project's build configuration (e.g., Maven pom.xml, Gradle build.gradle) and recompiling/redeploying affected applications.
c. Dependency Analysis: Perform a thorough dependency analysis to ensure that all transitive dependencies are compatible with the new SecureDataProcessor version and that no older, vulnerable versions are inadvertently re-introduced. Tools like OWASP Dependency-Check or similar Software Composition Analysis (SCA) tools can assist in this process.
d. Testing: After upgrading, thoroughly test the affected applications in a non-production environment to ensure full functionality and stability before deploying to production. Pay close attention to data exchange mechanisms that utilize the SecureDataProcessor library.

3. MITIGATION STRATEGIES

a. Disable Insecure Deserialization: If immediate patching is not possible, disable any application features or endpoints that rely on deserializing untrusted or externally provided Java objects using the vulnerable SecureDataProcessor library. This may involve code changes to temporarily remove functionality or reconfigure services.
b. Implement Strict Input Validation: For services that absolutely must deserialize data, implement strict application-level input validation before any deserialization occurs. This includes validating data types, lengths, formats, and ensuring that input does not contain unexpected serialized object structures.
c. Whitelisting Deserialization Classes: Configure the SecureDataProcessor (if supported by its API, or implement custom logic) to explicitly whitelist only the specific, known-safe classes that are expected to be deserialized. Reject any attempts to deserialize classes not on this whitelist. This is a critical defense-in-depth measure against arbitrary object deserialization.
d. Use Safer Data Formats: Where possible, refactor applications to use safer, language-agnostic data serialization formats like JSON, YAML, Protocol Buffers, or Avro, especially when exchanging data with untrusted sources. These formats inherently reduce the risk of code execution during deserialization compared to Java's native object serialization.
e. Network Segmentation and Least Privilege: Ensure that services utilizing the SecureDataProcessor library are deployed within highly restricted network segments. Apply strict firewall rules to limit network access to these services only from trusted internal components. Run applications with the absolute minimum necessary privileges to reduce the impact of a successful exploit.
f. Web Application Firewall (WAF) Rules: Deploy or update WAF rules to detect and block known malicious deserialization payloads. While generic rules can be challenging, specific patterns associated with common deserialization gadget chains (e.g., Apache Commons Collections, Spring Framework) can be identified and blocked.

4. DETECTION METHODS

a. Log Monitoring for Anomalies: Configure centralized logging and monitoring for all applications using SecureDataProcessor. Look for unusual application errors related to deserialization, unexpected class loading attempts, or stack traces indicating deserialization failures. Monitor system logs for unusual process spawns, shell commands, or network connections originating from the application's user context.
b. Endpoint Detection and Response (EDR): Utilize EDR solutions to monitor for post-exploitation activities on servers running vulnerable applications. This includes detecting suspicious process creation (e.g., cmd.exe, powershell.exe, bash) by the application's user, unusual file modifications, or outbound network connections to unknown destinations.
c. Network Intrusion Detection/Prevention Systems (NIDS/NIPS): Deploy and configure NIDS/NIPS to identify and alert on network traffic patterns indicative of deserialization attacks. This might include unusually large serialized object payloads, specific byte sequences known to be part of gadget chains, or connections to command