Files
fips/testing
Johnathan Corgan 14d2a4f2df Merge branch 'master' into next
Integrates PR #50 (peer ACL enforcement) into the XX handshake
architecture. ACL enforcement points adapted for XX's deferred
identity learning: InboundHandshake check moves from handle_msg1
to handle_msg3 (responder learns initiator identity), OutboundHandshake
check remains in handle_msg2 (initiator learns responder identity).
Borrow scopes restructured to release connection borrows before
authorize_peer calls.
2026-04-16 06:11:03 +00:00
..
2026-04-15 06:35:32 +00:00
2026-04-15 06:35:32 +00:00

FIPS Testing

Integration and simulation test harnesses for FIPS, using Docker containers running the full protocol stack.

Test Harnesses

static/ -- Static Docker Network

Fixed topologies with manual scripts for building, config generation, connectivity tests (ping, iperf), and network impairment (netem). Useful for deterministic debugging and validating specific topology configurations.

Topology Nodes Transport Description
mesh 5 UDP Sparse mesh, 6 links, multi-hop
chain 5 UDP Linear chain, max 4-hop paths
mesh-public 5+1 UDP Mesh with external public node
tcp-chain 3 TCP Linear chain over TCP (port 8443)
rekey 5 UDP Rekey integration test topology

tor/ -- Tor Transport Integration

End-to-end Tor transport testing with Docker containers running real Tor daemons. Requires internet access for Tor bootstrapping.

Scenario Description
socks5-outbound Outbound SOCKS5 connections through Tor to clearnet peer
directory-mode Inbound via HiddenServiceDir onion service (co-located)

chaos/ -- Stochastic Simulation

Automated network testing with configurable node counts, topology algorithms (random geometric, Erdos-Renyi, chain, explicit), and fault injection (netem mutation, link flaps, traffic generation, node churn). 20 scenarios covering general stress testing, cost-based parent selection, mixed link technologies (fiber/Bluetooth/WiFi), transport-specific validation (UDP, TCP, Ethernet), and ECN/congestion testing. Scenarios are defined in YAML and executed via a Python harness that manages the full lifecycle: topology generation, Docker orchestration, fault scheduling, log collection, and analysis.