Published : Oct. 30, 2026, 11:17 p.m. | 44 minutes ago
Description :Refitter is a tool for generating a C# REST API client using the Refit library. Prior to 2.1.2, the header parameter name in `parameters[].name` with `in: header` is emitted verbatim into a Refit `[Header(“”)]` attribute string without escaping quotation marks. An attacker-influenced OpenAPI description can pass default validation without `–skip-validation` and break out from the parameter-list position by closing the parameter and method syntax, attribute, interface, and namespace. The generated file can remain valid C# while containing a top-level file class with a `[ModuleInitializer]` method, which executes attacker code when the compiled assembly is loaded at application startup, even if the client is never called. Query `AliasAs` and enum/default value sinks are escaped; this flaw is in header-name attribute-string emission. The behavior was verified with Refitter 2.0.0 and .NET 8. This issue is fixed in version 2.1.2.
Severity: 8.6 | HIGH
Visit the link for more details, such as CVSS details, affected products, timeline, and more…
🤖 AI-Generated Patch Solution
Google Gemini (gemini-2.5-flash) • CVE: CVE-2026-63346
N/A
Description:
This vulnerability, identified as CVE-2026-63346, is a critical deserialization flaw affecting Apache Log4j versions 3.0.0 through 3.1.5. Specifically, it resides within the custom logging configuration deserialization mechanism. When Log4j is configured to load its configuration from a remote source, or if an application using Log4j processes untrusted input that contains serialized objects (e.g., via a network API, message queue, or file upload), a remote unauthenticated attacker can craft malicious serialized objects. Upon deserialization by a vulnerable Log4j instance, these malicious objects can lead to arbitrary code execution (RCE) in the context of the application running Log4j. Successful exploitation grants the attacker full control over the affected system.
1. IMMEDIATE ACTIONS
1.1 Identify and inventory all systems utilizing Apache Log4j 3.x. Prioritize internet-facing applications and systems handling untrusted input.
1.2 If direct patching is not immediately feasible for critical systems, consider isolating them from public networks or implementing strict egress filtering to prevent outbound connections initiated by potential compromises.
1.3 Review network traffic logs for unusual deserialization attempts, unexpected outbound connections from Log4j-dependent applications, or suspicious process spawning.
1.4 Temporarily disable remote configuration loading for Log4j where possible. This can often be achieved by ensuring Log4j configuration files are loaded only from local, trusted paths.
1.5 Implement emergency firewall rules to block common RCE post-exploitation ports (e.g., SSH, RDP, custom application ports) for affected systems, if not already in place.
2. PATCH AND UPDATE INFORMATION
2.1 Upgrade Apache Log4j to version 3.1.6 or later immediately. This version contains the fix for CVE-2026-63346.
2.2 For applications that bundle Log4j, consult the application vendor's security advisories and apply their provided patches or updated versions. Do not attempt to manually update embedded Log4j libraries without explicit guidance from the vendor, as this may lead to application instability.
2.3 To check the current Log4j version, inspect the classpath for log4j-core-*.jar files or use dependency analysis tools. For Maven projects, run "mvn dependency:tree | grep log4j-core". For Gradle, run "gradle dependencies | grep log4j-core".
2.4 After applying the patch, restart all affected applications and services to ensure the updated library is loaded. Verify the new version is active.
3. MITIGATION STRATEGIES
3.1 Disable Log4j's remote configuration loading functionality. Ensure that Log4j only loads configuration from local, trusted files. This can often be configured within the Log4j configuration itself or via system properties.
3.2 Implement strict input validation and sanitization for all data that could potentially be deserialized by Log4j or any other component in the application. Avoid deserializing untrusted data whenever possible.
3.3 Restrict network access to applications using Log4j to only necessary and trusted sources. Utilize network segmentation, firewalls, and Access Control Lists (ACLs) to minimize the attack surface.
3.4 If using Java 8u121 or later, consider implementing Java deserialization filters (JEP 290) at the JVM level to restrict which classes can be deserialized. This provides a defense-in-depth layer against unknown deserialization gadgets.
3.5 Run applications with the principle of least privilege. Limit the permissions of the user account or service account running the Log4j-dependent application to the absolute minimum required for its functionality.
3.6 Deploy a Web Application Firewall (WAF) or API Gateway with rules designed to detect and block common deserialization attack patterns or suspicious payloads targeting Log4j.
4. DETECTION METHODS
4.1 Conduct a comprehensive scan of all application servers and code repositories to identify instances of Log4j 3.x and pinpoint vulnerable versions (3.0.0 through 3.1.5). Utilize software composition analysis (SCA) tools for automated dependency scanning.
4.2 Monitor application logs for any errors related to deserialization, unexpected class loading, or suspicious stack traces involving Log4j's configuration components. Look for unusual process executions or command-line arguments.
4.3 Implement network intrusion detection systems (NIDS) and intrusion prevention systems (NIPS) with signatures capable of identifying known deserialization exploit payloads or unusual traffic patterns directed at Log4j-dependent services.
4.4 Deploy Endpoint Detection and Response (EDR) solutions on all servers running