Parse RFC 4253 §4.2 identification strings from the first attacker→decky
data segment on TCP/22; emit ssh_client_banner syslog events and bus
fan-out. Profiler's sniffer_rollup dedupes observed banners into a new
AttackerBehavior.ssh_client_banners JSON column.
Closes gap #3 from SIGNAL_CAPTURE_AUDIT.md.
Prober already emits kex_algorithms in hassh_fingerprint syslog events, but
the raw ordered list was only queryable via the generic bounty store. Add a
dedicated AttackerBehavior.kex_order_raw column (TEXT, JSON list) so
post-v1 KEX-order fingerprinting has a typed, indexable home.
Pipeline:
- sniffer_rollup() now consumes hassh_fingerprint events and collects
distinct kex_algorithms strings across ports.
- build_behavior_record() JSON-encodes the list (NULL when empty).
- sqlmodel_repo._deserialize_behavior() parses it back into a list.
Closes pre-v1 gap #1 from SIGNAL_CAPTURE_AUDIT.md.
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
