Extends tracing to every remaining module: all 23 API route handlers,
correlation engine, sniffer (fingerprint/p0f/syslog), prober (jarm/hassh/tcpfp),
profiler behavioral analysis, logging subsystem, engine, and mutator.
Bridges the ingester→SSE trace gap by persisting trace_id/span_id columns on
the logs table and creating OTEL span links in the SSE endpoint. Adds log-trace
correlation via _TraceContextFilter injecting otel_trace_id into Python LogRecords.
Includes development/docs/TRACING.md with full span reference (76 spans),
pipeline propagation architecture, quick start guide, and troubleshooting.
The active prober emits tcpfp_fingerprint events with TTL, window, MSS etc.
from the attacker's SYN-ACK. These were invisible to the behavioral profiler
for two reasons:
1. target_ip (prober's field name for attacker IP) was not in _IP_FIELDS in
collector/worker.py or correlation/parser.py, so the profiler re-parsed
raw_lines and got attacker_ip=None, never attributing prober events to
the attacker profile.
2. sniffer_rollup only handled tcp_syn_fingerprint (passive sniffer) and
ignored tcpfp_fingerprint (active prober). Prober events use different
field names: window_size/window_scale/sack_ok vs window/wscale/has_sack.
Changes:
- Add target_ip to _IP_FIELDS in collector and parser
- Add _PROBER_TCPFP_EVENT and _INITIAL_TTL table to behavioral.py
- sniffer_rollup now processes tcpfp_fingerprint: maps field names, derives
OS from TTL via _os_from_ttl, computes hop_distance = initial_ttl - observed
- Expand prober DEFAULT_TCPFP_PORTS to [22,80,443,8080,8443,445,3389] for
better SYN-ACK coverage on attacker machines
- Add 4 tests covering prober OS detection, hop distance, and field mapping
templates/decnet_logging.py calls str(v) on all SD-PARAM values, turning a
headers dict into Python repr ('{'User-Agent': ...}') rather than JSON.
detect_tools_from_headers() called json.loads() on that string and silently
swallowed the error, returning [] for every HTTP event. Same bug prevented
the ingester from extracting User-Agent bounty fingerprints.
- templates/http/server.py: wrap headers dict in json.dumps() before passing
to syslog_line so the value is a valid JSON string in the syslog record
- behavioral.py: add ast.literal_eval fallback for existing DB rows that were
stored with the old Python repr format
- ingester.py: parse headers as JSON string in _extract_bounty so User-Agent
fingerprints are stored correctly going forward
- tests: add test_json_string_headers and test_python_repr_headers_fallback
to exercise both formats in detect_tools_from_headers
- decnet/profiler/: analyze attacker behavior timings, command sequences, service probing patterns
- Enables detection of coordinated attacks vs random scanning
- Feeds into attacker scoring and risk assessment
