316 lines
14 KiB
Python
316 lines
14 KiB
Python
from __future__ import annotations
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import argparse
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import json
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import sys
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from pathlib import Path
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from .anomaly import anomaly_summary, detect_source_anomalies
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from .dashboard import serve_dashboard
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from .llm import ollama_summary
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from .logs import local_in_failures, read_events, summarize_events, top_field_values
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from .mitigation import FortiGateClient, parse_allowlist, suggest_block_candidates
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from .policies import audit_policies, read_policies
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from .recommendations import build_recommendations
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from .syslog_server import listen_udp_syslog
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from .monitor import monitor_loop
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from .threat_intel import enrich_ips, is_public_ip
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def _print_json(data: object) -> None:
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print(json.dumps(data, indent=2, sort_keys=True))
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def analyze_logs(args: argparse.Namespace) -> int:
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events = read_events(args.logs)
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candidates = suggest_block_candidates(
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events,
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min_events=args.min_events,
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min_score=args.min_score,
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allowlist=parse_allowlist(args.allowlist),
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)
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anomalies = detect_source_anomalies(events, limit=args.anomaly_limit)
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analysis = {
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"summary": summarize_events(events),
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"anomaly_summary": anomaly_summary(anomalies),
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"diagnostics": {
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"top_source_ips": top_field_values(events, "srcip", limit=10),
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"top_services": top_field_values(events, "service", limit=10),
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"top_actions": top_field_values(events, "action", limit=10),
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"top_subtypes": top_field_values(events, "subtype", limit=10),
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"local_in_failures": local_in_failures(events, limit=10),
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},
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"block_candidates": [
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{"src_ip": candidate.src_ip, "score": candidate.score, "reasons": candidate.reasons}
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for candidate in candidates
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],
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"anomalies": [
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{
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"subject": finding.subject,
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"score": finding.score,
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"severity": finding.severity,
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"confidence": finding.confidence,
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"reasons": finding.reasons,
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"evidence": finding.evidence,
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}
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for finding in anomalies
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],
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}
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_print_json(analysis)
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if args.llm:
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print("\nLLM summary:")
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print(ollama_summary([], candidates, args.model, analysis=analysis, timeout=args.llm_timeout))
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return 0
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def audit_policy_file(args: argparse.Namespace) -> int:
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findings = audit_policies(read_policies(args.config))
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_print_json([finding.__dict__ for finding in findings])
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if args.llm:
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print("\nLLM summary:")
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print(ollama_summary(findings, [], args.model, timeout=args.llm_timeout))
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return 0
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def suggest_blocks(args: argparse.Namespace) -> int:
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events = read_events(args.logs)
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candidates = suggest_block_candidates(
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events,
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min_events=args.min_events,
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min_score=args.min_score,
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allowlist=parse_allowlist(args.allowlist),
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)
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if not candidates:
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print("No block candidates met the current thresholds.")
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return 0
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for candidate in candidates:
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print(f"{candidate.src_ip} score={candidate.score} reasons={', '.join(candidate.reasons)}")
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if not args.execute:
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print(" dry-run: not blocked")
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continue
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client = FortiGateClient.from_env()
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reason = f"fgAI UTM mitigation score={candidate.score}"
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response = client.quarantine_ip(candidate.src_ip, args.expiry_minutes, reason)
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print(f" blocked: {response}")
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return 0
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def detect_anomalies(args: argparse.Namespace) -> int:
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events = read_events(args.logs)
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anomalies = detect_source_anomalies(events, limit=args.limit)
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output = {
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"summary": anomaly_summary(anomalies),
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"anomalies": [
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{
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"subject": finding.subject,
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"score": finding.score,
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"severity": finding.severity,
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"confidence": finding.confidence,
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"reasons": finding.reasons,
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"evidence": finding.evidence,
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}
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for finding in anomalies
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if finding.score >= args.min_score
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],
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}
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_print_json(output)
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if args.llm:
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print("\nLLM summary:")
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print(ollama_summary([], [], args.model, analysis=output, timeout=args.llm_timeout))
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return 0
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def recommend(args: argparse.Namespace) -> int:
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events = read_events(args.logs)
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anomalies = detect_source_anomalies(events, limit=args.limit)
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intel_ips = sorted(
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{
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ip
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for event in events
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for ip in (event.src_ip, event.dst_ip)
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if is_public_ip(ip)
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}
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)
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reputation = enrich_ips(intel_ips, limit=args.intel_limit) if args.threat_intel else {}
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recommendations = build_recommendations(events, anomalies, reputation)
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output = {
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"recommendations": [
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{
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"subject": item.subject,
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"score": item.score,
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"severity": item.severity,
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"title": item.title,
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"recommendation": item.recommendation,
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"reasons": item.reasons,
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"related_policy_ids": item.related_policy_ids,
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"related_services": item.related_services,
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}
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for item in recommendations
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if item.score >= args.min_score
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],
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"reputation": reputation,
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}
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_print_json(output)
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if args.llm:
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print("\nLLM summary:")
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print(ollama_summary([], [], args.model, analysis=output, timeout=args.llm_timeout))
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return 0
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def test_connection(args: argparse.Namespace) -> int:
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client = FortiGateClient.from_env()
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status = client.system_status()
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results = status.get("results", status)
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print("FortiGate API connection OK")
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_print_json(results)
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return 0
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def fetch_policies(args: argparse.Namespace) -> int:
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client = FortiGateClient.from_env()
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policies = client.firewall_policies()
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if args.output:
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output = Path(args.output)
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output.parent.mkdir(parents=True, exist_ok=True)
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output.write_text(json.dumps(policies, indent=2, sort_keys=True), encoding="utf-8")
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print(f"Wrote {output}")
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else:
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_print_json(policies)
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return 0
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def listen_syslog(args: argparse.Namespace) -> int:
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listen_udp_syslog(
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args.host,
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args.port,
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args.output,
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rotate_bytes=args.rotate_bytes,
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rotate_count=args.rotate_count,
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quiet=args.quiet,
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)
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return 0
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def run_monitor(args: argparse.Namespace) -> int:
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monitor_loop(
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args.logs,
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args.output,
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policy_path=args.policies,
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interval=args.interval,
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anomaly_limit=args.anomaly_limit,
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llm=args.llm,
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llm_interval=args.llm_interval,
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llm_model=args.model,
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llm_timeout=args.llm_timeout,
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)
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return 0
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def run_dashboard(args: argparse.Namespace) -> int:
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serve_dashboard(args.host, args.port, args.status_file, image_dir=args.image_dir)
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return 0
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def build_parser() -> argparse.ArgumentParser:
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parser = argparse.ArgumentParser(description="Local FortiGate AI/ML inspection tool")
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subparsers = parser.add_subparsers(required=True)
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logs = subparsers.add_parser("analyze-logs", help="Analyze local FortiGate logs")
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logs.add_argument("--logs", required=True, help="Path to syslog JSONL or key/value log file")
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logs.add_argument("--min-events", type=int, default=3)
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logs.add_argument("--min-score", type=int, default=7)
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logs.add_argument("--allowlist", default=None, help="Comma-separated IPs/CIDRs never to block")
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logs.add_argument("--llm", action="store_true", help="Ask local Ollama to summarize results")
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logs.add_argument("--model", default=None, help="Ollama model name")
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logs.add_argument("--llm-timeout", type=int, default=None, help="Ollama request timeout in seconds")
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logs.add_argument("--anomaly-limit", type=int, default=20, help="Maximum anomaly findings to include")
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logs.set_defaults(func=analyze_logs)
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anomalies = subparsers.add_parser("detect-anomalies", help="Score likely traffic anomalies by source IP")
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anomalies.add_argument("--logs", required=True, help="Path to syslog JSONL or key/value log file")
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anomalies.add_argument("--limit", type=int, default=20, help="Maximum anomaly findings to include")
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anomalies.add_argument("--min-score", type=int, default=1, help="Minimum anomaly score to output")
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anomalies.add_argument("--llm", action="store_true", help="Ask local Ollama to summarize results")
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anomalies.add_argument("--model", default=None, help="Ollama model name")
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anomalies.add_argument("--llm-timeout", type=int, default=None, help="Ollama request timeout in seconds")
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anomalies.set_defaults(func=detect_anomalies)
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recommendations = subparsers.add_parser("recommend", help="Generate policy and response recommendations from anomalies")
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recommendations.add_argument("--logs", required=True, help="Path to syslog JSONL or key/value log file")
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recommendations.add_argument("--limit", type=int, default=20, help="Maximum anomaly findings to evaluate")
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recommendations.add_argument("--min-score", type=int, default=35, help="Minimum recommendation score to output")
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recommendations.add_argument("--threat-intel", action="store_true", help="Use enabled external threat intelligence lookups")
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recommendations.add_argument("--intel-limit", type=int, default=25, help="Maximum public IPs to enrich")
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recommendations.add_argument("--llm", action="store_true", help="Ask local Ollama to summarize results")
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recommendations.add_argument("--model", default=None, help="Ollama model name")
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recommendations.add_argument("--llm-timeout", type=int, default=None, help="Ollama request timeout in seconds")
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recommendations.set_defaults(func=recommend)
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policies = subparsers.add_parser("audit-policies", help="Audit FortiOS firewall policy config")
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policies.add_argument("--config", required=True, help="Path to FortiOS config backup")
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policies.add_argument("--llm", action="store_true", help="Ask local Ollama to summarize results")
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policies.add_argument("--model", default=None, help="Ollama model name")
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policies.add_argument("--llm-timeout", type=int, default=None, help="Ollama request timeout in seconds")
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policies.set_defaults(func=audit_policy_file)
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blocks = subparsers.add_parser("suggest-blocks", help="Suggest or execute guarded source IP blocks")
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blocks.add_argument("--logs", required=True, help="Path to syslog JSONL or key/value log file")
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blocks.add_argument("--min-events", type=int, default=3)
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blocks.add_argument("--min-score", type=int, default=7)
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blocks.add_argument("--allowlist", default=None, help="Comma-separated IPs/CIDRs never to block")
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blocks.add_argument("--execute", action="store_true", help="Actually call the FortiGate quarantine API")
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blocks.add_argument("--expiry-minutes", type=int, default=60)
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blocks.set_defaults(func=suggest_blocks)
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connection = subparsers.add_parser("test-connection", help="Test FortiGate REST API credentials")
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connection.set_defaults(func=test_connection)
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fetch = subparsers.add_parser("fetch-policies", help="Fetch firewall policies through the FortiGate REST API")
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fetch.add_argument("--output", help="Write JSON response to this file")
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fetch.set_defaults(func=fetch_policies)
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listener = subparsers.add_parser("listen-syslog", help="Listen for UDP syslog and append to a local log file")
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listener.add_argument("--host", default="0.0.0.0", help="Bind address")
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listener.add_argument("--port", type=int, default=5514, help="UDP port. Use 514 only with sudo/capability.")
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listener.add_argument("--output", default="logs/fg_syslog.jsonl", help="File to append received logs to")
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listener.add_argument("--rotate-bytes", type=int, default=25 * 1024 * 1024, help="Rotate active log at this size; 0 disables rotation")
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listener.add_argument("--rotate-count", type=int, default=14, help="Number of compressed log archives to retain")
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listener.add_argument("--quiet", action="store_true", help="Do not print each received syslog message")
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listener.set_defaults(func=listen_syslog)
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monitor = subparsers.add_parser("monitor", help="Continuously analyze logs and write dashboard status JSON")
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monitor.add_argument("--logs", required=True, help="Path to syslog JSONL or key/value log file")
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monitor.add_argument("--output", default="state/fgai-status.json", help="Status JSON written for dashboard")
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monitor.add_argument("--policies", default=None, help="Optional FortiGate policy JSON/config file to audit continuously")
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monitor.add_argument("--interval", type=int, default=10, help="Seconds between analysis runs")
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monitor.add_argument("--anomaly-limit", type=int, default=20, help="Maximum anomaly findings to include")
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monitor.add_argument("--llm", action="store_true", help="Generate cached Ollama analyst note for dashboard")
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monitor.add_argument("--llm-interval", type=int, default=300, help="Seconds between Ollama dashboard assessments")
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monitor.add_argument("--model", default=None, help="Ollama model name")
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monitor.add_argument("--llm-timeout", type=int, default=None, help="Ollama request timeout in seconds")
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monitor.set_defaults(func=run_monitor)
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dashboard = subparsers.add_parser("dashboard", help="Serve local fgAI dashboard")
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dashboard.add_argument("--host", default="127.0.0.1", help="Dashboard bind address")
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dashboard.add_argument("--port", type=int, default=8088, help="Dashboard TCP port")
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dashboard.add_argument("--status-file", default="state/fgai-status.json", help="Status JSON produced by monitor")
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dashboard.add_argument("--image-dir", default="images", help="Directory containing dashboard images")
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dashboard.set_defaults(func=run_dashboard)
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return parser
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def main(argv: list[str] | None = None) -> int:
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parser = build_parser()
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args = parser.parse_args(argv)
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try:
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return args.func(args)
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except Exception as exc:
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print(f"fgai: {exc}", file=sys.stderr)
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return 1
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if __name__ == "__main__":
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raise SystemExit(main())
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