# SignalScope SignalScope is a local multi-source security analytics agent. Its primary mode connects to Graylog through MCP, discovers the streams and fields already available in your environment, and uses stream profiles to normalize events, build baselines, correlate entities, and explain anomalies with a local LLM. Its running only locally and if using LLM it's running also locally so no data is sent or exposed outside. FortiGate is one supported example. The same workflow applies to DNS/AdGuard, Windows Event Logs, Sysmon, Nginx, Squid, VPN, Proxmox, Filebeat-collected logs, and future Graylog streams. The Python module and legacy `fgai` command remain available for compatibility. New installations can use `signalscope`. The prioritized implementation plan is tracked in [ROADMAP.md](ROADMAP.md). Autoblocking is dry-run by default. The tool will not block RFC1918, loopback, multicast, link-local, reserved, or allowlisted addresses unless you change the code. ## Screenshots ### Settings ![Settings](images/settings.jpg) ### Findings ![Findings](images/findings.jpg) ### Correlation ![Correlation](images/correlation.jpg) ## Quick Start ```bash python -m venv .venv source .venv/bin/activate pip install -e . ``` Or use the helper script, which creates/uses `.venv` automatically and runs `pip install -e .`: ```bash ./start.sh ./start.sh status ./start.sh analyze ./start.sh stop ``` `./start.sh` starts three local background processes: - Optional UDP syslog listener writing `logs/fg_syslog.jsonl` - Continuous monitor writing `state/fgai-status.json` - Local dashboard at `http://127.0.0.1:8088` ## Primary Workflow: Graylog MCP Graylog 7.1 MCP is the primary log-source integration. In the dashboard, open `Settings`, select `Graylog MCP`, provide the MCP URL and a read-only API token, then load and enable the streams to analyze. SignalScope uses MCP `list_streams`, `list_fields`, `search_messages`, and `aggregate_messages` to work with existing log sources rather than requiring every source to be forwarded locally. The token field accepts a raw Graylog API token, the Base64 value after `Basic `, or a complete `Basic ` header. Tokens are stored only in the local runtime configuration and are never returned by the dashboard API. Use `Edit profile` on a stream to load its fields. The field table shows Graylog datatype/capability metadata and lets you select one or more entity fields, a time field, and categorical/numeric fields for the stream profile. Profiles are stored under `graylog_stream_profiles` in `state/fgai-config.json`. The settings page treats stream enablement and profile editing separately. The checkboxes decide which streams are monitored. Click `Edit profile` on one stream to load its fields and edit only that stream's profile; saving with no active profile editor leaves existing profiles unchanged. When many Graylog streams are available, use `Diagnostics -> Stream Coverage` to see which streams are enabled, which have profiles, how many profile fields are baseline-ready, how many events were fetched, and whether a stream is `ready`, `learning`, `missing_profile`, `no_events`, or `not_enabled`. Enabled streams are normalized through the same event model. Stream profiles define the entity, timestamp, categorical, and numeric fields used for baselines. The dashboard and Ollama then correlate behavior across sources, for example a client IP appearing in FortiGate, AdGuard/DNS, Windows Security, Nginx, Squid, VPN, or Proxmox. A stream profile can track multiple entities from the same event, such as `username`, `srcip`, and `hostname`. SignalScope stores profile baselines for each selected entity value, which makes cross-source investigation work even when one source is user-centric and another is IP- or host-centric. SignalScope keeps a common alias map for fields such as source IP, destination IP, ports, action, severity, service/protocol, DNS query, URL, message, and event type. This lets Related Activity and correlations work with firewall/proxy/DNS streams that use names like `src_addr`, `destination.ip`, `dest_port`, `fw_action`, `priority`, `proto`, or `full_message` without adding a new parser for every product. Correlation is entity-aware rather than FortiGate-specific. SignalScope recognizes common IP fields such as `srcip`, `source_ip`, `remote_addr`, and Windows event IP fields; account fields such as `username`, `user`, and `TargetUserName`; and host fields such as `hostname`, `computer`, and `winlog_computer_name`. Configure the exact entity field per stream in the profile when your Graylog schema differs. Each profile baseline is stored per stream, entity, selected field, and five-minute bucket. Once enough history exists, SignalScope compares the current rate or numeric value to the same UTC weekday/hour where possible, then falls back to the stream's overall history. Repeated MCP pages are fingerprinted so the same Graylog event is not learned repeatedly. Related anomalies, profile deviations, and multi-stream correlations are grouped into investigation incidents with a compact evidence timeline. Timeline and related-activity rows include copyable Graylog query details built from normalized source, destination, action, and DNS fields. These are query details rather than hard-coded web links, so they work with MCP and with Graylog deployments behind different URLs or reverse proxies. Incident lifecycle state is stored locally in `state/signalscope-incidents.json`. Use the dashboard incident actions to acknowledge, resolve, or reopen an incident and attach a note. The state is keyed to a stable incident fingerprint so it can survive monitor refreshes even when the current detection window changes. Export the current investigation view when you need to share or archive an incident outside the dashboard: ```bash signalscope export-investigation --format markdown --output exports/investigation.md signalscope export-investigation --incident-id --format json ``` The report is built from `state/fgai-status.json` by default and includes summary counters, stream coverage, incident state, analyst notes, evidence, timeline rows, and Graylog query details. The dashboard exposes the same data at `/api/export/incidents?format=markdown` or `format=json`. With a stream profile in place, SignalScope also builds independent burst baselines for authentication failures, DNS queries, and deny/block actions when those events are present. These are evaluated per configured entity, so a Windows account, DNS client, or firewall source is compared to its own history. SignalScope also detects ordered behavior sequences across any streams that share an entity. The built-in sequence is category-based, not source-specific: `dns_query -> network_connection -> auth_failure`. Those categories can come from AdGuard, Windows DNS, a proxy, firewall, VPN, endpoint, or any other Graylog stream as long as the fields normalize into the same generic event model. Stream profiles can also carry `field_weights` to tune scoring without changing the baseline itself. Weights are multipliers from `0` to `5` and can target a field, a detector, or a field+detector pair: ```json { "url": 1.5, "auth_failure_burst": 2, "query_domain": { "rare_value": 1.8 } } ``` Use replay or `replay-graylog --compare-config-file` to test score changes before applying them to the live profile. Replay a historic JSONL or Graylog export without changing the live baseline: ```bash signalscope replay --logs exports/windows-history.jsonl --stream-id ``` Replay uses a temporary SQLite baseline and evaluates events in timestamp order. It reports detector counts and the findings that would have been generated. Use the configured stream ID so the export is evaluated with that stream's profile. Replay directly from Graylog MCP without touching the live baseline: ```bash signalscope replay-graylog --range-seconds 86400 ``` By default this uses the enabled streams from the dashboard configuration. Limit the run to one or more streams with repeated `--stream-id` flags. To test a candidate detector/profile configuration before applying it, compare it against the current runtime config: ```bash signalscope replay-graylog --range-seconds 86400 --compare-config-file exports/candidate-config.json ``` The comparison reports detector-count, field-finding, and source-anomaly deltas using the same fetched event window. The current MCP endpoint is `http://:9000/api/mcp`. Enable it in Graylog under `System -> Configurations -> MCP` and use stream IDs internally; the fgAI stream picker resolves titles in the UI. For live monitoring, `graylog_range_seconds` controls how far back each MCP poll searches. The default is one hour, which keeps findings and correlations more stable than a very short window while still limiting MCP query cost. ## Monitoring Export The dashboard also exposes Prometheus text metrics at: ```text http://127.0.0.1:8088/metrics ``` This endpoint is passive and has no Prometheus or Grafana dependency. It reports low-cardinality event counts, anomaly severities, incident counts, baseline readiness, and Graylog MCP health. Use it later as a Prometheus scrape target or as input for a Checkmk local check. Do not use source IPs, domains, or raw event IDs as metric labels. Enable cached Ollama analyst notes in the dashboard: ```bash FGAI_LLM=1 OLLAMA_MODEL=llama3.1 ./start.sh restart ``` The monitor refreshes deterministic detections every `FGAI_MONITOR_INTERVAL` seconds and refreshes the LLM note every `FGAI_LLM_INTERVAL` seconds, default `300`. The script activates `.venv` inside the script process. If you also want your current shell prompt to show the venv, run: ```bash source .venv/bin/activate ``` For UDP `514`, the script starts only the listener command with `sudo`: ```bash FGAI_SYSLOG_PORT=514 ./start.sh ``` The syslog receiver rotates the active JSONL input at 25 MB by default. Rotated files are gzip-compressed and 14 archives are retained. Override this when needed: ```bash FGAI_LOG_ROTATE_BYTES=$((100 * 1024 * 1024)) FGAI_LOG_ROTATE_COUNT=30 ./start.sh restart ``` The continuous monitor also stores a local SQLite behavior baseline at `state/fgai-baseline.sqlite3`. A source becomes baseline-ready after 12 completed five-minute windows. Historical rate and hitcount-rate deviations then contribute to its anomaly score. Set `FGAI_BASELINE_DB` to use another location. Analyze local logs: ```bash fgai analyze-logs --logs logs/fg_syslog.jsonl ``` Open the live UI after `./start.sh`: ```bash xdg-open http://127.0.0.1:8088 ``` Score likely traffic anomalies: ```bash fgai detect-anomalies --logs logs/fg_syslog.jsonl --min-score 35 fgai detect-anomalies --logs logs/fg_syslog.jsonl --min-score 35 --llm --llm-timeout 300 ``` Generate response and policy recommendations: ```bash fgai recommend --logs logs/fg_syslog.jsonl --min-score 35 ``` Optional external reputation enrichment is disabled by default. To use VirusTotal for public source/destination IP reputation: ```bash export FGAI_THREAT_INTEL=1 export ABUSEIPDB_API_KEY='...' fgai recommend --logs logs/fg_syslog.jsonl --min-score 35 --threat-intel ``` VirusTotal is also supported: ```bash export FGAI_THREAT_INTEL=1 export FGAI_THREAT_INTEL_PROVIDER=virustotal export VIRUSTOTAL_API_KEY='...' fgai recommend --logs logs/fg_syslog.jsonl --min-score 35 --threat-intel ``` Threat intelligence responses are cached locally in `state/threat-intel-cache.json`. Successful results are reused for seven days by default, failures for one hour, and SignalScope permits at most 100 new provider lookups per UTC day. Cached responses are returned even after that budget is reached. Tune these safeguards with `FGAI_THREAT_INTEL_TTL_SECONDS`, `FGAI_THREAT_INTEL_ERROR_TTL_SECONDS`, and `FGAI_THREAT_INTEL_DAILY_LIMIT`. Listen for FortiGate syslog locally: ```bash fgai listen-syslog --port 5514 --output logs/fg_syslog.jsonl ``` Run the listener quietly in the background: ```bash ./start.sh ``` Stop the background listener: ```bash ./start.sh stop ``` UDP port `514` normally needs root privileges on Linux: ```bash sudo .venv/bin/fgai listen-syslog --port 514 --output logs/fg_syslog.jsonl ``` Test FortiGate API access: ```bash export FORTIGATE_HOST=192.0.2.10 export FORTIGATE_API_TOKEN='...' export FORTIGATE_VERIFY_TLS=false fgai test-connection fgai fetch-policies --output exports/policies.json ``` Audit a FortiGate policy export: ```bash fgai audit-policies --config exports/fortigate.conf ``` Or fetch policies through the FortiGate API and audit that JSON: ```bash fgai fetch-policies --output exports/policies.json fgai audit-policies --config exports/policies.json --llm --llm-timeout 300 ``` Find block candidates without changing the firewall: ```bash fgai suggest-blocks --logs logs/fg_syslog.jsonl ``` Execute guarded quarantine actions: ```bash export FORTIGATE_HOST=192.0.2.10 export FORTIGATE_API_TOKEN='...' fgai suggest-blocks --logs logs/fg_syslog.jsonl --execute --expiry-minutes 60 ``` Optional local LLM summary through Ollama: ```bash ollama pull llama3.3 fgai analyze-logs --logs logs/fg_syslog.jsonl --llm --llm-timeout 300 ``` For slower machines or large models: ```bash OLLAMA_MODEL=llama3.1 OLLAMA_TIMEOUT=300 fgai analyze-logs --logs logs/fg_syslog.jsonl --llm ``` ## Optional FortiGate Input ## Synthetic Windows Test Input For testing a Graylog Beats input without a Windows host, generate Windows Security-style JSONL events locally, then use Filebeat to ship them over TCP: ```bash python scripts/generate_windows_events.py --interval 0.5 filebeat -e -c examples/filebeat-windows-synthetic.yml ``` Update the absolute JSONL path and Graylog host in the Filebeat template first. Route `stream_hint: Windows` to a dedicated Graylog stream, then enable that stream in SignalScope and configure a profile such as entity `user` or `source_ip`, categorical `event_id`, `status`, `logon_type`, and numeric fields when present. Filebeat uses its Logstash output to communicate with Graylog's Beats input on TCP `5044`. [Graylog Beats input documentation](https://go2docs.graylog.org/current/getting_in_log_data/beats_input.html) For logs, configure FortiGate syslog to write into a local file such as `logs/fg_syslog.jsonl`. The parser supports common key/value syslog lines and JSONL. For policies, export a FortiOS config backup and pass it to `audit-policies`. Example FortiGate syslog target, run on the FortiGate CLI and replace the server IP with this machine: ```text config log syslogd setting set status enable set server "192.0.2.50" set port 5514 set mode udp set format default end ``` ## Environment - `FORTIGATE_HOST`: firewall hostname or IP. - `FORTIGATE_API_TOKEN`: REST API token. - `FORTIGATE_VERIFY_TLS`: `true` or `false`, defaults to `true`. - `FGAI_ALLOWLIST`: comma-separated IPs/CIDRs never to block. - `OLLAMA_HOST`: defaults to `http://127.0.0.1:11434`. - `OLLAMA_MODEL`: defaults to `llama3.1`. - `OLLAMA_TIMEOUT`: Ollama request timeout in seconds, defaults to `180`. - `FGAI_LLM`: set to `1` to enable dashboard Ollama analyst notes. - `FGAI_LLM_INTERVAL`: seconds between dashboard LLM notes, defaults to `300`. - `FGAI_THREAT_INTEL`: set to `1` to enable external threat intelligence lookups. - `ABUSEIPDB_API_KEY`: AbuseIPDB API key for public IP reputation enrichment. - `ABUSEIPDB_MAX_AGE_DAYS`: report age window for AbuseIPDB, defaults to `90`. - `FGAI_THREAT_INTEL_PROVIDER`: `auto`, `abuseipdb`, or `virustotal`. - `VIRUSTOTAL_API_KEY`: VirusTotal API key for public IP reputation enrichment. ## Safety Model The agent separates detection from enforcement: - UTM events are scored from FortiGate logs (`ips`, `virus`, `anomaly`, `ddos`, `webfilter`, `app-ctrl`, `waf`, `dns`). - Source IPs must be globally routable and outside the allowlist. - Blocking requires `--execute`. - The FortiGate API call is limited to the quarantine/banned user monitor endpoint.