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Introduction:
In the high-stakes world of network security, visibility is paramount. When a FortiGate High Availability (HA) cluster fails unpredictably, administrators rely on packet analysis to diagnose issues like split-brain conditions or sync failures. However, a critical roadblock has persisted: the proprietary FortiGate Clustering Protocol (FGCP) appears in tools like Wireshark as indecipherable “Unknown Data,” forcing engineers into tedious reverse-engineering. This article delves into a groundbreaking community-led initiative to decode FGCP, highlighting the tools, methods, and urgent need for vendor transparency in enterprise security.
Learning Objectives:
- Understand the structure and obfuscation of the FortiGate Clustering Protocol (FGCP).
- Learn how to capture and analyze FGCP traffic for advanced HA troubleshooting.
- Explore the community’s reverse-engineering process and its implications for vendor accountability.
You Should Know:
- The Opaque Nature of FGCP and Its Impact on Troubleshooting
The FortiGate Clustering Protocol (FGCP) uses Ethernet types 0x8890 and 0x8893 for heartbeat, configuration sync, and session state synchronization between cluster members. Without a proper dissector, this traffic is a black box.
Step‑by‑step guide explaining what this does and how to use it.
1. Capture FGCP Traffic: On your FortiGate’s HA interfaces or a SPAN port, use tcpdump or FortiGate’s built-in diag sniffers.
Linux/Wireshark Host on a SPAN port sudo tcpdump -i eth0 -s 0 -w fgcp_capture.pcap ether proto 0x8890 or ether proto 0x8893 FortiGate CLI (execute on primary) diagnose sniffer packet internal "ether proto 0x8890" 4 0 a
2. Open in Wireshark: Load the capture. You will see FGCP frames, but the details will be “Unknown Data” or “FGCP Header” with minimal info, lacking decoded Type-Length-Value (TLV) fields for sync data.
3. The Problem: Critical TLVs containing interface states, MAC addresses, session table checksums, and configuration hashes are displayed as raw hex, requiring manual interpretation and slowing incident resolution dramatically.
- Reverse-Engineering the Protocol: From Hex Dumps to Decoded TLVs
The community analyzed patterns across thousands of packets during failover events, identifying compression (zlib) and TLV structures.
Step‑by‑step guide explaining what this does and how to use it.
1. Identify Patterns: Filter for FGCP in Wireshark (eth.type == 0x8890). Export packet bytes.
2. Analyze Payload: Using a hex editor or Python, isolate recurring headers and suspect compressed blocks.
import pcapng, zlib, struct
Example Python snippet to parse a suspected TLV block from raw hex
raw_data = bytes.fromhex('1F8B080000000000...') From Wireshark export
try:
decompressed = zlib.decompress(raw_data, wbits=-zlib.MAX_WBITS)
print(f"Decompressed: {decompressed.hex()}")
except zlib.error:
print("Not zlib or custom header.")
3. Map TLVs: By correlating network events (e.g., a link failure) with changes in the binary data, the team mapped TLV types for session sync tables and topology updates.
- Integrating Findings into Wireshark: Building a Community Dissector
The ultimate goal is a native Wireshark dissector for full protocol decoding.
Step‑by‑step guide explaining what this does and how to use it.
1. Review the GitLab Contribution: The community submitted a detailed patch to the Wireshark project. GitLab Issue 1, GitLab Issue 2.
2. Apply a Custom Dissector (Temporary): Before official integration, you can compile Wireshark with the patched `packet-fortinet-fgcp.c` file or use Lua scripting for basic decoding.
-- Wireshark Lua script example for a simple FGCP TLV
local p_fgcp = Proto("FGCP_Custom", "FortiGate Clustering Protocol")
local f_tlv_type = ProtoField.uint16("fgcp.tlv.type", "TLV Type", base.HEX)
p_fgcp.fields = { f_tlv_type }
function p_fgcp.dissector(buffer, pinfo, tree)
pinfo.cols.protocol = "FGCP_Custom"
local subtree = tree:add(p_fgcp, buffer(), "FGCP Custom Data")
subtree:add(f_tlv_type, buffer(0,2))
-- Add more field dissection based on community findings
end
local eth_table = DissectorTable.get("ethertype")
eth_table:add(0x8890, p_fgcp)
3. Test the Dissector: Capture new traffic. The custom dissector will now parse previously opaque fields, revealing TLV types like `0x0001` for Heartbeat or `0x0010` for Session Sync Data.
4. Proactive FGCP Health Monitoring and Diagnostics
With decoding capabilities, you can build proactive monitoring.
Step‑by‑step guide explaining what this does and how to use it.
1. Deploy a Dedicated Capture Sensor: Use a lightweight VM (e.g., Alpine Linux) with `tcpdump` on a HA network SPAN port.
2. Automate Analysis with Scripts: Create a Python script using `scapy` (with a custom FGCP layer) or `tshark` to alert on anomalous TLV patterns.
tshark command to extract specific TLV values from a live capture
tshark -i eth0 -Y "eth.type == 0x8890" -T fields -e fgcp.tlv.type -e fgcp.tlv.value 2>/dev/null | awk '$1 == "0x0010" {print "Session Sync TLV Found:", $2}'
3. Monitor for Signs of Failure: High rates of specific “Unknown” TLVs or missing heartbeat intervals can preempt failover issues.
5. Hardening Cluster Security Through Protocol Analysis
Understanding FGCP exposes potential attack surfaces for cluster integrity.
Step‑by‑step guide explaining what this does and how to use it.
1. Isolate HA Interfaces: Ensure HA1 and HA2 interfaces are on dedicated, isolated VLANs or physical links inaccessible to other networks.
2. Implement Control Plane Policing (CoPP): On adjacent switches, rate-limit the FGCP Ethernet types (0x8890/0x8893) to prevent flooding attacks.
Cisco IOS Example CoPP access-list 150 permit 0x8890 0x0 access-list 150 permit 0x8893 0x0 policy-map COPP-FGCP class 1 police cir 10m
3. Validate Checksums: The community-identified configuration checksum TLV can be monitored for unauthorized changes, signaling a configuration drift or compromise.
What Undercode Say:
- Vendor Obfuscation is a Security Liability: Proprietary protocols that hinder customer troubleshooting create single points of failure and increase mean time to recovery (MTTR) during incidents, contradicting the principle of defense-in-depth.
- The Power of Collective Intelligence: This effort demonstrates that skilled practitioner communities can and will reverse-engineer lacking documentation, but this is an inefficient use of critical security resources that should be focused on threat defense.
Prediction:
This incident will intensify pressure on all network security vendors (Fortinet, Palo Alto, Check Point) to open-source or thoroughly document their clustering and internal management protocols. Regulatory frameworks for critical infrastructure may soon mandate such transparency as part of “secure by design” principles. Vendors who collaborate will see enhanced trust and product reliability through community-audited code, while those who resist will face increased scrutiny, grassroots reverse-engineering, and potential market erosion in favor of more transparent competitors. The future of enterprise security tooling is collaborative transparency.
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IT/Security Reporter URL:
Reported By: Thomassautier Fortinet – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
