mirror of
https://github.com/SHOGGOTH-SECTOR/sica-fondt.git
synced 2026-08-01 16:40:24 +00:00
24f816b6a3
Place useful parts of the surrounding repos into sica-fondt by layer, per the
body model (Ada = membrane; brain/endocrine/capabilities/knowledge non-Ada):
- brain/ LLM reasoning + providers (dapr, hermes, MoMoA)
- capabilities/ REPRAG sidecars: hermes tools/skills, dapr tools, parallel
dispatch, A51 channels, and the OSINT cluster
- knowledge/ LORAG corpus: 754 cyber-skills, agency personas, secure-coding,
MITRE ATT&CK data
- reference/ defensive threat-reference (C3, shhbruh doc) + AdaYaml parser
License handling: AGPL sources (worldosint, advanced_evolution, mercury,
Reticulum) and GPL DeTTECT are SPEC-only clean-room/port descriptions — no
copyleft code copied. MIT/Apache/data parts copied as working trees.
Safety: shhbruh escape/persistence material and C3 covert-C2 kept as reference
only, not wired into the running organism. See CONSOLIDATION.md.
https://claude.ai/code/session_01UehUqEXXJJCsHoA4voCU5c
32 lines
1.6 KiB
Python
32 lines
1.6 KiB
Python
#!/usr/bin/env python3
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"""Browser Forensics Analyzer - Parses Chrome History SQLite for investigation."""
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import sqlite3, json, os, sys
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from datetime import datetime, timedelta
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CHROME_EPOCH = datetime(1601, 1, 1)
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def chrome_ts(ts):
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if not ts: return None
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try: return str(CHROME_EPOCH + timedelta(microseconds=ts))
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except: return None
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def analyze_chrome(profile: str, output_dir: str) -> str:
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os.makedirs(output_dir, exist_ok=True)
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history_db = os.path.join(profile, "History")
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conn = sqlite3.connect(f"file:{history_db}?mode=ro", uri=True)
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c = conn.cursor()
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c.execute("SELECT u.url, u.title, v.visit_time, u.visit_count FROM visits v JOIN urls u ON v.url=u.id ORDER BY v.visit_time DESC LIMIT 2000")
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visits = [{"url": r[0], "title": r[1], "time": chrome_ts(r[2]), "count": r[3]} for r in c.fetchall()]
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c.execute("SELECT target_path, tab_url, start_time, total_bytes, mime_type FROM downloads ORDER BY start_time DESC LIMIT 500")
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downloads = [{"path": r[0], "url": r[1], "time": chrome_ts(r[2]), "size": r[3], "mime": r[4]} for r in c.fetchall()]
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conn.close()
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report = {"visits": len(visits), "downloads": len(downloads), "visit_data": visits, "download_data": downloads}
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out = os.path.join(output_dir, "browser_forensics.json")
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with open(out, "w") as f: json.dump(report, f, indent=2)
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print(f"[*] Visits: {len(visits)}, Downloads: {len(downloads)}")
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return out
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if __name__ == "__main__":
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if len(sys.argv) < 3: print("Usage: process.py <chrome_profile> <output>"); sys.exit(1)
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analyze_chrome(sys.argv[1], sys.argv[2])
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