Hi @raboof, all checks have passed. Thank you.

All checks have passed. We are ready to merge. Please let me know if you have any concerns. Thank you very much for your support.

@JinwooHwang while this is a solid implementation, I would like to discuss architecturally should we combine this with existing serialization filter infrastructure that is already present rather than making it separate. See my email in dev mailing list and lets discuss there. Once we align I can provide some feedback on the implementation. Thanks.

Thank you so much for the thoughtful review, @sboorlagadda. I appreciate you taking the time to look into this. Your architectural perspective makes a lot of sense, and I agree that aligning this work with the broader community consensus would be the right path forward.
Once we’re aligned, I’d be grateful for any further feedback you may have on the implementation.
Thanks again for your guidance and support.

MINOR ISSUE #1: Missing Test Coverage

Location: Missing tests for SecureClassLoaderObjectInputStream

What's Missing:

1. Test for null filter validation (IllegalArgumentException expected)
2. Test for resolveClass() fallback to context ClassLoader
3. Test for resolveProxyClass() with non-public interfaces
4. Integration test with actual serialization/deserialization flow

Impact: Medium - Core functionality of SecureClassLoaderObjectInputStream is not unit tested

MINOR ISSUE #2: Missing Integration Test

Location: No end-to-end test for GemfireHttpSession.getAttribute() with malicious payload

What's Missing: Test that simulates:

1. Storing a session attribute with different ClassLoader
2. Attempting to deserialize a blocked class
3. Verifying SecurityException is caught and null is returned
4. Verifying security log contains the blocked attempt

Impact: Medium - The actual integration point is not tested

🔍 Security Review

Threat Model Coverage

Defense-in-Depth Layers

1. ✅ Layer 1: Blacklist known dangerous classes (BLOCKED_CLASSES)
2. ✅ Layer 2: Blacklist dangerous package patterns (BLOCKED_PATTERNS)
3. ✅ Layer 3: Whitelist only known-safe classes (ALLOWED_CLASSES)
4. ✅ Layer 4: Whitelist safe package patterns (ALLOWED_PATTERNS)
5. ✅ Layer 5: Resource limits (depth, references, arrays, bytes)
6. ✅ Layer 6: Security logging for audit trail
7. ✅ Layer 7: Fail-safe exception handling (return null vs throw)

Nice-to-Have

1. 💡 Consider adding performance benchmark test to validate <1ms overhead claim
2. 💡 Consider documenting upgrade path for users with custom session attributes
3. 💡 Consider adding configuration property to extend whitelist at runtime (for custom DTOs)

Hi @sboorlagadda,

Thank you so much for your thorough review and for raising these thoughtful architectural concerns. I appreciate the time and care you’ve taken to consider the design in depth. I would like to address each of your points with supporting technical evidence and references to industry best practices.

Why These Must Be Separate Systems

The architectural concern lists four issues:

• Configuration complexity (two separate whitelist systems)
• Operational burden (maintaining dual security policies)
• User confusion (different config for sessions vs regions)
• Potential security gaps (inconsistent policies)

These aren't problems - they're the expected and necessary characteristics of layered security architecture. Each concern reflects proper separation of security boundaries, not architectural weakness.

This separation is intentional. The two layers serve different purposes and protect distinct attack surfaces with different threat models.

Geode's infrastructure filter protects:

• Cluster communication (peer-to-peer messages)
• Internal region operations
• Distributed system metadata
• Cache consistency protocols
• Threats: Malicious cluster members, corrupted internal data, version incompatibilities

Session filter must protect:

• HTTP request boundary (untrusted user input)
• Application-level objects from web clients
• Session hijacking attempts
• Deserialization gadget chains in user data
• Threats: External attackers via HTTP, compromised client applications, RCE exploits

These are fundamentally different security boundaries.

Real-world analogy:
Your firewall filters network packets. Your application still validates HTTP input. Both are active simultaneously, both filter "data entering the system," but at different trust boundaries with different policies. You wouldn't merge them just because they both filter.

Similarly:

• Network layer: Firewall blocks malicious IPs, port scans, DDoS
• Application layer: WAF blocks SQL injection, XSS, malformed requests

Both active. Different purposes. Different policies.

Industry Validation: Defense-in-Depth

This approach isn’t something I invented; it’s a well-established industry practice:

Spring Framework (OWASP layered security):

• Web layer: OncePerRequestFilter, CSRF protection, HTTP request filters, secure headers
  Handles HTTP-level security (authentication, session management, CSRF, input validation)
  Operates independently from service and data layers.

• Service layer: @PreAuthorize, @PostAuthorize, @secured annotations, method-level security
  Enforces authorization and business rules at the service/business-logic level.
  Provides a separate control boundary independent of web filters.

• Data layer: Safe data-access patterns (prepared statements, parameter binding in JDBC/JPA)
  Protects against SQL injection when used correctly.

Each layer has independent security controls. Web-layer filters are not merged with service or database security, enabling defense-in-depth and reducing the impact of a single-layer compromise.

AWS multi-layer architecture:

• ALB/WAF: HTTP-level filtering
• Lambda/EC2: IAM roles, network security groups
• RDS/DynamoDB: Database-specific encryption, access controls

Apache Kafka (CWE-502 context-specific filters):

• Internal Protocol: Kafka's binary protocol, only Kafka internal classes
• User Data: Configurable deserializers (StringDeserializer, ByteArrayDeserializer, or custom).
• Separation: User data serialization should be isolated from internal messages.

Apache Cassandra:

• Internal cluster communication: Custom binary protocol, only Cassandra classes
• User data (CQL queries): User-defined types (UDTs) and application objects can be queried and stored.

Hazelcast (direct competitor of our Apache Geode):

Config config = new Config();

// Internal cluster objects
config.getSerializationConfig()
    .addDataSerializableFactory(100, new MyInternalFactory());

// Application/user objects
config.getSerializationConfig()
    .addPortableFactory(200, new MyApplicationFactory())
    .setAllowUnsafe(false);

Hazelcast explicitly separates internal vs application serialization.

Microsoft SDL Trust Boundary Analysis (accurate, generalized):

• Trust Boundary 1: External (HTTP clients) → apply safe deserialization and input validation; use a whitelist of classes for deserialization.
• Trust Boundary 2: Internal (cluster members) → validate serialized objects exchanged between nodes; apply appropriate deserialization safeguards.
• Principle: Different trust boundaries have different threat models, requiring independent controls.

Real-world CVE fixes validate this:

• CVE-2015-7501 (JBoss): Fixed by safe deserialization and class whitelisting in HTTP/EJB entry points.
• CVE-2016-0638 (WebLogic): Fixed by restricting allowed classes for T3 protocol and HTTP deserialization.
• CVE-2017-5645 (Log4j): Fixed by patching JMS deserialization logic and enforcing allowed class lists.
  Principle: These CVEs demonstrate the importance of context-aware, layer-specific deserialization safeguards, rather than generic “layered filters.”

Industry consensus: Multi-layered, context-specific filters are the standard.

Addressing the Specific Concerns

"Configuration complexity (two separate whitelist systems)"

This is defense-in-depth, not complexity. Each boundary needs its own policy:

• Geode allowlist: 485 classes for internal operations (ResourceManager, StatisticDescriptor, DistributionMessage, etc.)
• Session allowlist: 80 classes for user data (String, Integer, ArrayList, HashMap, etc.)

"Operational burden (maintaining dual security policies)"

The policies serve different purposes and must be maintained separately:

Geode's 485-class allowlist includes:

• org.apache.geode.internal.cache.tier.sockets.command.*
• org.apache.geode.distributed.internal.*
• org.apache.geode.management.internal.*
• Classes needed for cluster operations

Session's 80-class allowlist includes:

• java.lang.String, Integer, Boolean
• java.util.ArrayList, HashMap, HashSet
• java.util.Date, Calendar
• Classes safe for user-facing web applications

These lists have zero overlap in purpose.

"User confusion (different config for sessions vs regions)"

This is expected and correct. Different architectural layers have different configuration:

Infrastructure layer (managed by cluster admins):

• Geode cluster setup
• Region replication policies
• validate-serializable-objects configuration
• Internal class allowlist (485 Geode classes)

Application layer (managed by application developers):

• Session timeout settings
• Custom session class registration via SafeDeserializationFilter.allowAdditionalClasses()
• Application-specific allowlist (80 JDK classes + custom classes)

Having different configuration at different layers isn't confusion - it's separation of concerns.

"Potential security gaps (inconsistent policies)"

The "gap" is actually the security boundary. Inconsistent policies are correct here - they enforce isolation:

• HTTP boundary: Strict 80-class allowlist (only safe user data types)
• Cluster boundary: 485-class allowlist (internal operations need more classes)

The security gap exists when boundaries don't have appropriate policies. PR-7941 adds the missing policy at the HTTP boundary.

Discussion Points Answered

1. Should we extend existing Geode serialization infrastructure?

I don't think we should, because they protect different things:

• Geode infrastructure: Protects cluster integrity (peer communication, internal operations)
• Session filter: Protects against external attackers via HTTP

The fix must be at the HTTP boundary with an HTTP-appropriate policy.

2. How do we provide unified configuration for users?

I don't believe we do, because unification breaks isolation. The configurations serve different purposes and are typically managed by different roles:

3. What's the migration path for existing session deployments?

Zero migration for standard use cases:

• PR-7941 includes 80 common JDK classes in the hardcoded allowlist
• Covers String, Integer, Collections, Date, etc.

Existing sessions stored in regions continue working. The filter only applies during deserialization, and legitimate classes pass through once added to the allowlist.

4. How do we handle the different threat models?

By maintaining appropriate policies at appropriate boundaries:

Web application threat model:

• Attacker: External, untrusted HTTP clients
• Attack vector: Crafted session attributes with gadget chains
• Required defense: Strict allowlist of safe user-facing classes (80 classes)
• Boundary: HTTP session setAttribute/getAttribute

Distributed cache threat model:

• Attacker: Compromised cluster member, corrupted internal data
• Attack vector: Malicious region data, corrupted metadata
• Required defense: Allowlist of internal operation classes (485 classes)
• Boundary: Cluster communication, region operations

The correct approach: Different threats require different policies at different boundaries. This is standard security architecture.

The Complete Architecture: Two Filters, Two Boundaries

PR-7941 implements defense-in-depth with filters at both security boundaries:

┌──────────────────────────────────────────────────────────────────┐
│  External Attacker (HTTP Client)                                 │
└────────────────┬─────────────────────────────────────────────────┘
                 │
                 ▼
         ┌──────────────────────────────┐
         │  SafeDeserializationFilter   │  ← NEW: PR-7941
         │      (80 JDK classes)        │     HTTP Boundary Protection
         └──────────────┬───────────────┘
                        │ ✓ String, Integer, ArrayList allowed
                        │ ✗ ResourceManager, CacheConfig BLOCKED
                        ▼
         ┌──────────────────────────────┐
         │      Session Object          │
         │      (validated data)        │
         └──────────────┬───────────────┘
                        │
                        ▼
         ┌──────────────────────────────┐
         │       Geode Region           │
         │     (serialized bytes)       │
         └──────────────┬───────────────┘
                        │
         ┌──────────────▼───────────────┐
         │    Region Replication        │
         │    Internal Operations       │
         │   Cluster Communication      │
         └──────────────┬───────────────┘
                        │
                        ▼
         ┌──────────────────────────────┐
         │  validate-serializable-      │  ← EXISTING: Geode Infrastructure
         │         objects              │     Cluster Boundary Protection
         │     (485 Geode classes)      │
         └──────────────┬───────────────┘
                        │ ✓ BucketAdvisor, DistributionMessage allowed
                        │ ✗ Untrusted application classes BLOCKED
                        ▼
         ┌──────────────────────────────┐
         │      Cluster Member          │
         │        (peer node)           │
         └──────────────────────────────┘

Two independent security layers designed for different boundaries:

1. SafeDeserializationFilter (HTTP → Session) - NEW, Always Active:

   • Protects against external attackers sending malicious session attributes
   • Prevents gadget chain RCE attacks via HTTP (CVSS 9.8 vulnerability)
   • Blocks internal Geode classes (ResourceManager, CacheConfig) from HTTP input
   • Allows only safe user-facing types (String, Integer, Collections)

2. validate-serializable-objects (Cluster Operations) - Existing, Opt-in (disabled by default):

   • When enabled, protects against corrupted internal data during replication
   • Prevents malicious cluster members from injecting bad classes
   • Blocks arbitrary application classes from internal operations
   • Allows only Geode infrastructure classes needed for cluster integrity

Why separate filters at separate boundaries:

• Session data CAN flow through both filters - but at different points in its lifecycle:

  • Filter 1 (SafeDeserializationFilter) applies when user calls session.setAttribute() (HTTP boundary) - always active
  • Filter 2 (validate-serializable-objects) applies when Geode replicates session region to other nodes (cluster boundary) - only if enabled by admin

• Different attack vectors require different defenses:

  • HTTP attacker tries to inject malicious classes via session → Filter 1 blocks (new protection)
  • Compromised cluster member tries to inject malicious classes via replication → Filter 2 blocks (if enabled)

• Critical insight: PR-7941 adds the FIRST layer of defense:

  • Before PR-7941: Zero protection at HTTP boundary (CVSS 9.8 RCE vulnerability)
  • After PR-7941: HTTP boundary protected with strict 80-class allowlist
  • Geode's cluster filter: Exists but disabled by default - users can enable for additional defense-in-depth

This is the same pattern every distributed system uses:

• Spring Security: FilterChainProxy with multiple filters for different URL patterns and layers
• AWS: Security groups (network) + IAM policies (identity) + S3 bucket policies (data)
• Kubernetes: NetworkPolicies (network) + RBAC (API) + PodSecurityPolicies (runtime)
• Database systems: Connection authentication + SQL authorization + row-level security
  The architectural principle: Match security controls to trust boundaries, not to minimize filter count.

Current state and impact of PR-7941:

• Before PR-7941:

  • HTTP boundary (most exposed): No protection
  • Cluster boundary: Optional protection (disabled by default)

• After PR-7941:

  • HTTP boundary: Always protected with SafeDeserializationFilter
  • Cluster boundary: Optional protection (unchanged - users can enable if needed)

This PR closes the critical vulnerability by adding mandatory protection at the HTTP boundary where the attack occurs. The cluster-level filter remains available as an optional additional layer for users who want defense-in-depth against internal threats.
Before this PR, Geode had zero protection at the HTTP boundary - the most exposed attack surface. This fix adds the missing layer where the vulnerability exists.

Hi @leonfin. Thank you so much for the thorough review and identifying these test coverage gaps. You were absolutely right about the issues. I've just pushed comprehensive test coverage. Your feedback significantly improved the robustness of this security fix. Really appreciate you catching these.

Thank you for the comprehensive work on addressing this critical vulnerability. The implementation is solid and the security analysis is thorough. However, I'd like to propose an alternative architectural approach that could provide the same security benefits while maintaining better consistency with Geode's existing infrastructure.

The Core Issue

The vulnerability exists because session management bypasses Geode's robust ClassLoader resolution and uses manual ClassLoaderObjectInputStream reconstruction:

// Current vulnerable code in GemfireHttpSession.getAttribute() (lines 147-149)
ObjectInputStream ois = new ClassLoaderObjectInputStream(
    new ByteArrayInputStream(baos.toByteArray()), loader);
tmpObj = ois.readObject();  // No filtering applied!

Why ClassLoader Reconstruction is Needed in Session Management

Session management has a unique requirement that regular cache operations don't face: web application isolation. Here's the scenario that triggers the vulnerable code:

Tomcat Server 1: WebApp A (ClassLoader A)
    ↓ session.setAttribute("user", userObject)
    ↓ Session stored in Geode region
    ↓ Server 1 fails

Tomcat Server 2: WebApp B (ClassLoader B)
    ↓ Session fails over due to server failure
    ↓ session.getAttribute("user") called
    ↓ Object deserialized with ClassLoader A (from original server)
    ↓ ClassLoader mismatch detected: userObject.getClass().getClassLoader() != ClassLoader B
    ↓ Manual reconstruction needed to make object compatible with WebApp B

Technical Requirement: Objects must be reconstructed with the current web application's ClassLoader for proper functionality. In Java, MyClass from WebApp A ≠ MyClass from WebApp B (even with identical bytecode) due to ClassLoader identity rules.

The Security Problem: The reconstruction process bypasses Geode's security infrastructure by using raw ClassLoaderObjectInputStream.

Understanding Why Regular Cache Operations Don't Have This Problem

To understand why this vulnerability is specific to session management, let's examine how regular Geode cache operations handle ClassLoader mismatches securely. This analysis reveals that Geode's core infrastructure already has robust mechanisms for handling ClassLoader issues - which makes the session management vulnerability even more concerning since it bypasses these proven protections.

Regular Geode Cache Operations (Secure)

Server A: region.put("key", myObject)
    ↓ DataSerializer.writeObject()
    ↓ Bytes stored and replicated
Server B: Object obj = region.get("key")
    ↓ BlobHelper.deserializeBlob() → DataSerializer.readObject()
    ↓ InternalDataSerializer.getCachedClass()
    ↓ ClassPathLoader.getLatest().forName()  ← Uses secure delegation chain
    ✅ Object deserialized with appropriate ClassLoader + all filters applied

Session Management (Current Vulnerability)

Web App A: session.setAttribute("key", myObject)
    ↓ Session fails over to Web App B (different ClassLoader)
Web App B: Object obj = session.getAttribute("key")
    ↓ AbstractSessionAttributes.getAttribute() → BlobHelper.deserializeBlob() ← This works fine!
    ↓ BUT: obj.getClass().getClassLoader() != webAppB.getClassLoader()
    ↓ GemfireHttpSession detects ClassLoader mismatch
    ↓ Manual reconstruction with ClassLoaderObjectInputStream
    ❌ Bypasses ALL existing Geode security infrastructure

The key insight is that session management implements parallel ClassLoader resolution instead of extending Geode's existing, proven mechanisms.

Proposed Alternative Solution: Thread Context ClassLoader Integration

Instead of creating new filtering infrastructure, we can leverage Geode's existing ClassPathLoader delegation chain. While we considered several implementation approaches (custom DataSerializer integration, filtered ObjectInputStream extensions, custom ClassLoader chains), the thread context ClassLoader approach provides the best balance of simplicity, security, and architectural consistency.

Here's how it works:

Current Vulnerable Code:

// In GemfireHttpSession.getAttribute() (lines 147-149)
if (obj.getClass().getClassLoader() != loader) {
    // VULNERABLE: Manual reconstruction bypasses all filters
    ObjectInputStream ois = new ClassLoaderObjectInputStream(
        new ByteArrayInputStream(baos.toByteArray()), loader);
    tmpObj = ois.readObject();  // No security filtering!
}

Secure Alternative:

// In GemfireHttpSession.getAttribute() - proposed replacement
private Object reconstructAttributeSecurely(Object obj, ClassLoader webAppLoader)
        throws IOException, ClassNotFoundException {

    // Serialize using Geode's secure serialization (BlobHelper.java)
    byte[] serializedData = BlobHelper.serializeToBlob(obj);

    // Set thread context ClassLoader for proper resolution
    ClassLoader originalTCCL = Thread.currentThread().getContextClassLoader();
    try {
        Thread.currentThread().setContextClassLoader(webAppLoader);

        // Deserialize using Geode's secure, filtered deserialization
        // This automatically applies ALL existing security filters
        // BlobHelper → DataSerializer → InternalDataSerializer → ClassPathLoader
        return BlobHelper.deserializeBlob(serializedData);

    } finally {
        Thread.currentThread().setContextClassLoader(originalTCCL);
    }
}

Why This Works

Geode's ClassPathLoader already implements this delegation order:

// From ClassPathLoader.java documentation
// Class loading order:
// 1. Any custom loaders in the order they were added
// 2. Thread.currentThread().getContextClassLoader() ← We control this
// 3. ClassPathLoader.class.getClassLoader()
// 4. System ClassLoader

When we set the thread context ClassLoader to the web application's ClassLoader:

1. BlobHelper.deserializeBlob() calls DataSerializer.readObject()
2. DataSerializer.readObject() calls InternalDataSerializer.getCachedClass()
3. InternalDataSerializer.getCachedClass() calls ClassPathLoader.getLatest().forName()
4. ClassPathLoader.forName() checks thread context ClassLoader first
5. Classes get loaded with web app ClassLoader ✅
6. All existing security filters are applied ✅

Evidence: Geode Already Handles ClassLoader Mismatches

The test BlobHelperWithThreadContextClassLoaderTest.java demonstrates this works:

// From BlobHelperWithThreadContextClassLoaderTest.java
@Test
public void handlesObjectWithStateFromOtherClassLoader() throws Exception {
    // Load class with custom ClassLoader
    Class loadedClass = Class.forName(CLASS_NAME, true,
        Thread.currentThread().getContextClassLoader());

    Object instance = loadedClass.newInstance();
    byte[] bytes = BlobHelper.serializeToBlob(instance);

    // BlobHelper successfully deserializes with different ClassLoader
    Object deserialized = BlobHelper.deserializeBlob(bytes);  // ✅ Works!
}

This proves that BlobHelper.deserializeBlob() already handles ClassLoader mismatches correctly using Geode's ClassPathLoader mechanism.

Developer Experience and Configuration Impact

One of our key concerns with the dual filtering approach is the configuration complexity it introduces for users:

Current PR-7941 Configuration Requirements:

# Existing Geode config (already working)
validate-serializable-objects=true
serializable-object-filter=com.enterprise.model.**,com.enterprise.dto.**

# NEW session config (must be added and maintained separately)
session.filter.enabled=true
session.filter.whitelist=com.enterprise.model.User,com.enterprise.model.Order,com.enterprise.dto.CustomerInfo
session.filter.max-depth=50

Thread Context Approach Configuration:

# Same existing Geode config (no changes needed!)
validate-serializable-objects=true
serializable-object-filter=com.enterprise.model.**,com.enterprise.dto.**
# Sessions automatically protected with same rules ✅

Key DX Benefits:

• ✅ Zero new configuration - uses existing Geode serialization settings
• ✅ Single security model - no dual systems to learn and maintain
• ✅ Consistent troubleshooting - same error messages and debugging approach
• ✅ Easier migration - existing Geode configuration just works

Benefits of This Approach

1. Same Security Protection

• Closes the vulnerability immediately
• Uses ALL existing Geode security filters, not just new ones
• Automatically benefits from future security enhancements

2. Architectural Consistency

• Single security model across all Geode components
• Leverages existing, proven infrastructure instead of duplicating it
• Follows established Geode patterns that developers understand

3. Simpler Maintenance

• No parallel filtering systems to maintain
• Easier debugging - follows standard Geode deserialization paths
• Better testability - can reuse existing Geode serialization tests

4. Future-Proof

• Evolves with Geode - automatically gets new security features
• No technical debt - doesn't create parallel infrastructure to unify later

Implementation Comparison

Addressing Potential Concerns

Q: Does this change affect performance?
A: Minimal impact - just thread context ClassLoader switching, which is a lightweight operation.

Q: Are there compatibility risks?
A: Lower risk than new infrastructure - uses existing, battle-tested Geode deserialization paths.

Q: Does this handle all ClassLoader scenarios?
A: Yes - Geode's ClassPathLoader is designed to handle complex ClassLoader hierarchies and has been proven in production.

Recommendation

While I appreciate the thorough work in PR-7941, I believe the thread context ClassLoader approach provides:

• ✅ Same immediate security protection
• ✅ Better long-term architecture
• ✅ Lower maintenance burden
• ✅ Stronger security posture (more comprehensive filtering)

Would you be open to exploring this alternative approach? I'd be happy to collaborate on a proof-of-concept implementation that demonstrates the security and architectural benefits.

The goal isn't to dismiss the excellent work already done, but to find the most elegant solution that serves both immediate security needs and long-term architectural health.

Hi @sboorlagadda,

Thank you for taking the time to review this PR and propose an alternative architectural approach. I genuinely appreciate your thoughtful consideration of how this could integrate with Geode's existing infrastructure.

I'd like to better understand the security coverage of your proposed Thread Context ClassLoader approach. You mentioned two key benefits:

"Closes the vulnerability immediately"
"Uses ALL existing Geode security filters"

I want to make sure I understand this correctly. My current implementation explicitly blocks:

• 26 specific gadget classes (InvokerTransformer, ChainedTransformer, TemplatesImpl, ObjectFactory, MethodClosure, JndiRefForwardingDataSource, etc.)
• 10 dangerous package patterns (org.apache.commons.collections.functors., org.springframework.beans.factory., java.rmi.*, etc.)

Could you help me understand how your proposed approach would block these same classes? Specifically:

1. Which existing Geode filter(s) block these gadget chains?
   I traced through the code and found that serializationFilter defaults to NullStreamSerialFilter (line 294 in InternalDataSerializer.java). Looking at the implementation:

   // NullStreamSerialFilter.java
   public class NullStreamSerialFilter implements StreamSerialFilter {
     @Override
     public void setFilterOn(ObjectInputStream objectInputStream) {
       // Do nothing, this is the case where we don't filter.
     }
   }

   This is explicitly documented as "Implementation of StreamSerialFilter that does nothing" with the comment "Do nothing, this is the case where we don't filter." So by default, no filtering is applied.

2. Does sanctioned-geode-core-serializables.txt contain gadget blocking entries?
   I examined this file (485 lines) and found it contains only Apache Geode internal classes (exceptions, cache operations, admin/management, PDX serialization).
   This appears to be a whitelist of Geode-internal classes for cluster operations, not a security blocklist. It contains 485 Geode classes but zero gadget chain blocking entries.

Regarding your statement that this "closes the vulnerability immediately" - I want to understand the mechanism. The vulnerability exists because malicious gadget chains (like InvokerTransformer) can be deserialized without any validation. For the vulnerability to be closed:

• These specific classes must be blocked during deserialization, OR
• An allowlist must reject classes not explicitly permitted

Could you clarify which of these mechanisms the TCCL approach uses? From my code analysis, I see that BlobHelper.deserializeBlob() calls through to InternalDataSerializer which applies serializationFilter (currently NullStreamSerialFilter by default). This appears to provide no blocking of gadget chains.

I may be misunderstanding how Geode's existing filter infrastructure works. If there's existing gadget chain protection in Geode that I'm missing, I'd be very grateful if you could point me to the specific code or configuration that provides this protection.

I've invested considerable effort creating 28 unit tests in this PR covering gadget blocking, resource limits, and various configuration scenarios - all demonstrating that SafeDeserializationFilter successfully blocks known attack chains. Could you share examples or point me to existing tests that demonstrate how TCCL prevents classes like InvokerTransformer from being deserialized and executed? That would really help me understand the protection mechanism you're describing.

My goal is to understand whether the Thread Context ClassLoader approach provides equivalent security coverage to the explicit SafeDeserializationFilter, or if additional work would be needed to add gadget chain protection to Geode's core infrastructure.

Specific concern: If we adopt the TCCL approach without gadget blocking, an attacker could still send a malicious InvokerTransformer object in a session attribute. The TCCL would successfully load the class (improving compatibility), but the gadget chain would execute, achieving RCE. Is there a mechanism I'm missing that prevents this?

I'm completely open to integrating with Geode's existing infrastructure if it can provide the same security guarantees. I just want to make sure we don't inadvertently leave the vulnerability open while we work on architectural improvements.

Thank you again for your guidance and expertise on this.