Implement TCP transport for FIPS enabling firewall traversal and serving as the foundation for future Tor transport. This is the first connection-oriented transport in the system. Key design decisions: - FMP header-based framing: reuses existing 4-byte FMP common prefix for packet boundary recovery with zero framing overhead - Session survives TCP reconnection: Noise/MMP/FSP state bound to npub, not TCP connection; MMP liveness is sole authority for peer death - Connect-on-send: fresh connection on first send, transparent reconnect - close_connection() trait method for cross-connection deduplication cleanup New transport files: - src/transport/tcp/mod.rs: TcpTransport, connection pool, accept loop - src/transport/tcp/stream.rs: FMP-aware stream reader (shared with Tor) Modified: transport trait (close_connection), TcpConfig, TransportHandle match arms, create_transports(), initiate_connection() for connection- oriented links, cross-connection tie-breaker cleanup, design docs. Tree announce loop and TCP stability fixes: - Preserve tree announce rate-limit state across reconnection: carry forward last_tree_announce_sent_ms when a peer reconnects so the rate-limit window isn't reset to zero - Drop oversize TCP packets at sender: pre-send MTU check returns MtuExceeded instead of writing to the stream, preventing receiver-side connection teardown and reset-reconnect cycles Chaos harness: - TCP transport support: tcp_edges/has_tcp/tcp_peers in SimTopology, transport-aware config_gen with per-edge transport type, TCP port 443, pure-TCP node support - Include all non-Ethernet edges in directed_outbound() - Fix netem/links log messages to say "IP-based" instead of "UDP" - Add tcp-chain, tcp-only, and tcp-mesh scenario files Static harness: - Transport-aware config generation (get_default_transport, transport_port) - TCP transport injection via Python post-processing - Add tcp-chain topology and docker-compose profile
Stochastic Network Simulation
Automated stochastic network testing for FIPS. Generates random topologies, spins up Docker containers, and applies configurable stressors (network impairment, link flaps, traffic generation, node churn) over a timed simulation run. Logs are collected and analyzed automatically.
Prerequisites
- Docker with the compose plugin
- Rust toolchain (for building the FIPS binary)
- Python 3 with
pyyamlandjinja2packages
Quick Start
./testing/chaos/scripts/build.sh
./testing/chaos/scripts/chaos.sh smoke-10
Available Scenarios
| Scenario | Nodes | Topology | Duration | Netem | Link Flaps | Traffic | Node Churn | Bandwidth |
|---|---|---|---|---|---|---|---|---|
| smoke-10 | 10 | random_geometric | 60s | -- | -- | -- | -- | -- |
| chaos-10 | 10 | random_geometric | 120s | yes | yes | yes | -- | -- |
| churn-10 | 10 | random_geometric | 600s | yes | yes | yes | yes | -- |
| churn-20 | 20 | erdos_renyi | 600s | yes | yes | yes | yes | yes |
CLI Options
| Option | Description |
|---|---|
-v, --verbose |
Enable debug logging |
--seed N |
Override the scenario's random seed |
--duration secs |
Override the scenario's duration |
--list |
List available scenarios |
The scenario argument accepts either a name (churn-10) or a file
path (scenarios/churn-10.yaml).
Scenario YAML Format
Annotated example based on churn-10.yaml:
scenario:
name: "churn-10"
seed: 42 # deterministic RNG seed
duration_secs: 600 # total simulation time
topology:
num_nodes: 10
algorithm: random_geometric # or erdos_renyi, chain
params:
radius: 0.5 # algorithm-specific parameter
ensure_connected: true # retry until graph is connected
subnet: "172.20.0.0/24"
ip_start: 10 # first node gets .10
netem:
enabled: true
default_policy:
delay_ms: { min: 5, max: 50 }
jitter_ms: { min: 1, max: 10 }
loss_pct: { min: 0, max: 2 }
mutation:
interval_secs: { min: 20, max: 45 } # re-roll interval
fraction: 0.3 # fraction of links mutated
policies: # named policy profiles
normal:
delay_ms: [5, 20]
loss_pct: [0, 1]
degraded:
delay_ms: [50, 100]
jitter_ms: [10, 30]
loss_pct: [3, 8]
link_flaps:
enabled: true
interval_secs: { min: 30, max: 60 }
max_down_links: 2
down_duration_secs: { min: 10, max: 30 }
protect_connectivity: true # never partition the graph
traffic:
enabled: true
max_concurrent: 3
interval_secs: { min: 10, max: 30 }
duration_secs: { min: 5, max: 15 }
parallel_streams: 4
node_churn:
enabled: true
interval_secs: { min: 60, max: 180 }
max_down_nodes: 1
down_duration_secs: { min: 30, max: 90 }
protect_connectivity: true # never kill the last path
bandwidth:
enabled: false # per-link HTB rate limiting
tiers_mbps: [1, 10, 100, 1000] # each link randomly assigned a tier
logging:
rust_log: "debug"
output_dir: "./sim-results"
Topology Algorithms
| Algorithm | Parameters | Description |
|---|---|---|
| random_geometric | radius (default 0.5) | Place nodes in unit square, connect pairs within radius |
| erdos_renyi | p (default 0.3) | Include each edge independently with probability p |
| chain | -- | Linear chain: n01--n02--...--nN |
When ensure_connected is true (default), the generator retries up to
50 times to produce a connected graph.
Directed Outbound Configs
The config generator assigns each edge to exactly one node for outbound connection using a BFS spanning tree rooted at the lowest node ID. Tree edges are assigned parent-to-child; non-tree edges are assigned from the lower node ID to the higher. This eliminates the dual-connect race condition where both sides initiate simultaneously, and creates a clear "owning side" for each link — relevant for auto-reconnect testing.
Output
Results written to sim-results/ (configurable via
logging.output_dir):
analysis.txt-- Summary: panics, errors, sessions, metricsmetadata.txt-- Seed, node count, edges, adjacency listrunner.log-- Orchestration events (topology, netem, churn, traffic) with timestampsfips-node-nXX.log-- Per-node log output
Exit code 0 on success, 2 if panics detected.
Creating Custom Scenarios
- Copy an existing scenario from
scenarios/. - Adjust topology size, algorithm, and stressor parameters.
- Run with
./testing/chaos/scripts/chaos.sh path/to/custom.yaml.