mirror of
https://github.com/marcredhat/SIEM-toolkit-patched
synced 2026-06-08 20:37:12 +00:00
marc
8dbd38f3bb
- backend/routers/quality.py
* Add GET /api/quality/parsers (lists actual files in /app/parsers)
* Support SDL JSON auto-extract parsers ($=json{parse=json}$)
* Apply parser rewrite blocks with correct $0/$N backref translation
* Accept single JSON / JSON array / NDJSON in test-parser body
* Flatten JSON inside 'message' for Field Population coverage
- backend/routers/ingest.py
* Rewrite simulate-filter PowerQuery to valid SDL syntax
* Correct field name: src.name -> dataSource.name
- frontend/index.html
* Parser dropdown loads from /api/quality/parsers
* Add 'Last 7d' lookback option
* Render JSON-mode test results with badges + payload counter
391 lines
14 KiB
Python
391 lines
14 KiB
Python
from fastapi import APIRouter, HTTPException
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from pydantic import BaseModel
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from datetime import datetime, timedelta
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from services import s1_client
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import os
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import re
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router = APIRouter()
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@router.get("/parsers")
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def list_parser_files():
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"""List parser filenames available under /app/parsers/ for the Test Runner."""
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parsers_dir = "/app/parsers"
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try:
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names = sorted(
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e.name for e in os.scandir(parsers_dir)
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if e.is_file() and not e.name.startswith(".")
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)
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except FileNotFoundError:
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names = []
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return {"parsers": names, "count": len(names)}
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def _date_range_hours(hours: int) -> tuple[str, str]:
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now = datetime.utcnow()
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return (
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(now - timedelta(hours=hours)).strftime("%Y-%m-%dT%H:%M:%S.000Z"),
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now.strftime("%Y-%m-%dT%H:%M:%S.000Z"),
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)
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# ---------------------------------------------------------------------------
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# Models
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# ---------------------------------------------------------------------------
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class SampleEventsRequest(BaseModel):
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source: str
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limit: int = 20
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hours: int = 1
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class FieldPopulationRequest(BaseModel):
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source: str
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hours: int = 24
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fields: list[str] = [
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"src.ip",
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"src.port",
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"dst.ip",
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"dst.port",
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"user.name",
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"event.type",
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"src.process.name",
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"src.process.cmdline",
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"tgt.file.path",
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"network.direction",
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"dataSource.name",
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]
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class TestParserRequest(BaseModel):
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parser_name: str
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log_line: str
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# ---------------------------------------------------------------------------
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# Helpers
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# ---------------------------------------------------------------------------
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def _flatten_dict(d: dict, prefix: str = "", out: dict | None = None) -> dict:
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"""Recursively flatten a nested dict into dotted keys."""
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if out is None:
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out = {}
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if not isinstance(d, dict):
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return out
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for k, v in d.items():
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key = f"{prefix}.{k}" if prefix else k
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if isinstance(v, dict):
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_flatten_dict(v, key, out)
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else:
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out[key] = v
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return out
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def _flatten_event(event: dict) -> dict:
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"""Return a flat field→value dict from a PowerQuery result row.
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If the row only carries a JSON-stringified payload in `message` (i.e. the
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parser wasn't applied at query time), parse and flatten it inline so the
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UI can measure field population accurately. The original raw `message`
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is preserved under its own key.
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"""
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if not isinstance(event, dict):
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return {}
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flat = dict(event)
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msg = flat.get("message")
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if isinstance(msg, str) and msg.startswith("{") and msg.endswith("}"):
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try:
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parsed = __import__("json").loads(msg)
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if isinstance(parsed, dict):
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flat.update(_flatten_dict(parsed))
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except Exception:
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pass
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return flat
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def _extract_format_strings(content: str) -> list[str]:
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"""
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Extract SDL format string values from augmented-JSON parser content.
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Matches: "format": "..." (double-quoted value, supports escaped quotes).
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"""
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pattern = re.compile(r'"format"\s*:\s*"((?:[^"\\]|\\.)*)"')
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return pattern.findall(content)
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def _sdl_format_to_regex(fmt: str) -> tuple[re.Pattern, dict[str, str]]:
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"""
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Convert an SDL format string to a compiled Python regex.
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Returns (compiled_pattern, py_group_to_sdl_field) mapping so callers can
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translate group names back to the original SDL field names.
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Raises re.error if the resulting pattern cannot be compiled.
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"""
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# Split on $...$ tokens
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token_pattern = re.compile(r'\$([^$]+)\$')
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parts = token_pattern.split(fmt)
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# parts alternates: literal, token, literal, token, ...
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regex_parts: list[str] = []
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py_group_to_sdl: dict[str, str] = {}
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seen_groups: dict[str, int] = {}
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for i, part in enumerate(parts):
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if i % 2 == 0:
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# Literal text
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regex_parts.append(re.escape(part))
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else:
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# Token: either "field.name=PATTERN" or just "field.name"
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if '=' in part:
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field_name, pattern = part.split('=', 1)
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else:
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field_name = part
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pattern = r'[^\s]+'
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# Build a valid Python group name
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safe = re.sub(r'[.\-]', '_', field_name)
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if safe in seen_groups:
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seen_groups[safe] += 1
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safe = f"{safe}_{seen_groups[safe]}"
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else:
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seen_groups[safe] = 0
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py_group_to_sdl[safe] = field_name
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regex_parts.append(f'(?P<{safe}>{pattern})')
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compiled = re.compile(''.join(regex_parts), re.IGNORECASE)
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return compiled, py_group_to_sdl
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# ---------------------------------------------------------------------------
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# Endpoints
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# ---------------------------------------------------------------------------
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@router.post("/sample-events")
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async def sample_events(req: SampleEventsRequest):
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"""Return a sample of raw events from a given data source."""
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query = f'| filter dataSource.name = "{req.source}" | limit {req.limit}'
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from_dt, to_dt = _date_range_hours(req.hours)
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result = await s1_client.run_powerquery(query, from_dt, to_dt)
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rows = result if isinstance(result, list) else (result.get("rows") or result.get("events") or [])
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events = [_flatten_event(row) for row in rows]
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return {
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"source": req.source,
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"events": events,
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"count": len(events),
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"hours": req.hours,
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}
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@router.post("/field-population")
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async def field_population(req: FieldPopulationRequest):
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"""
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Analyse how consistently each requested field is populated across a sample
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of events from a data source.
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"""
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query = f'| filter dataSource.name = "{req.source}" | limit 500'
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from_dt, to_dt = _date_range_hours(req.hours)
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result = await s1_client.run_powerquery(query, from_dt, to_dt)
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rows = result if isinstance(result, list) else (result.get("rows") or result.get("events") or [])
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events = [_flatten_event(row) for row in rows]
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if not events:
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raise HTTPException(status_code=404, detail=f"No events found for source '{req.source}' in the last {req.hours} hours.")
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total = len(events)
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_empty = {None, "", "null"}
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# Collect all field names seen across the sample (useful for surfacing what IS there)
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all_seen_fields = sorted({k for ev in events for k in ev})
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field_stats = []
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for field in req.fields:
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# dataSource.name is always 100% — we filtered by it; Scalyr just doesn't echo it back
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if field == "dataSource.name":
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populated = total
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else:
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populated = sum(1 for ev in events if ev.get(field) not in _empty)
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rate = round((populated / total) * 100, 1)
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field_stats.append({
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"field": field,
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"populated": populated,
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"total": total,
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"rate": rate,
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})
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# Sort ascending by rate (worst coverage first)
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field_stats.sort(key=lambda x: x["rate"])
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return {
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"source": req.source,
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"total_sampled": total,
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"hours": req.hours,
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"fields": field_stats,
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"fields_seen_in_sample": all_seen_fields,
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}
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@router.post("/test-parser")
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async def test_parser(req: TestParserRequest):
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"""
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Test a parser against a raw log line by extracting and matching SDL format
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strings found in the parser file.
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"""
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parser_path = f"/app/parsers/{req.parser_name}"
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try:
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with open(parser_path, "r", encoding="utf-8") as fh:
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content = fh.read()
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except FileNotFoundError:
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raise HTTPException(status_code=404, detail=f"Parser file not found: {req.parser_name}")
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except OSError as exc:
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raise HTTPException(status_code=500, detail=f"Could not read parser file: {exc}")
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format_strings = _extract_format_strings(content)
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# ── JSON auto-extract path ──────────────────────────────────────────────
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# SDL parsers that use `$=json{parse=json}$` (or any format containing
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# `parse=json`) auto-extract every top-level JSON key as an attribute.
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# The regex-based path can't model that — handle it explicitly so users
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# can test JSON-shaped logs against JSON-mode parsers.
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log_input = req.log_line.strip()
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is_json_mode = any("parse=json" in f for f in format_strings) or log_input.startswith("{")
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if is_json_mode:
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import json as _json
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# Support multi-line input (one JSON object per line, or a JSON array)
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lines = [ln for ln in (l.strip() for l in log_input.splitlines()) if ln]
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payloads: list[dict] = []
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parse_errors: list[str] = []
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# Single line: try direct parse; if it's a JSON array, expand.
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if len(lines) == 1:
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try:
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obj = _json.loads(lines[0])
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except Exception as e:
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return {
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"parser_name": req.parser_name,
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"matched": False,
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"message": f"Parser expects JSON but log line could not be parsed as JSON: {e}",
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"fields": [],
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}
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if isinstance(obj, list):
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payloads = [x for x in obj if isinstance(x, dict)]
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elif isinstance(obj, dict):
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payloads = [obj]
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else:
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return {
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"parser_name": req.parser_name,
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"matched": False,
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"message": "Parser expects a JSON object (got scalar).",
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"fields": [],
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}
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else:
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# Multi-line: one JSON object per line (NDJSON)
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for i, ln in enumerate(lines, 1):
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try:
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obj = _json.loads(ln)
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if isinstance(obj, dict):
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payloads.append(obj)
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else:
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parse_errors.append(f"line {i}: not a JSON object")
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except Exception as e:
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parse_errors.append(f"line {i}: {e}")
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if not payloads:
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return {
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"parser_name": req.parser_name,
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"matched": False,
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"message": "No valid JSON objects found. " + " | ".join(parse_errors[:3]),
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"fields": [],
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}
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# Use the first payload for the detail table; report totals.
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payload = payloads[0]
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extracted = _flatten_dict(payload)
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# Apply lightweight rewrites if present (input/output/match/replace blocks).
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# We only handle simple literal/regex matches with $0 or string replacements;
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# this is best-effort, intended for quick visual verification.
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rewrites_applied = []
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rewrite_re = re.compile(
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r'\{\s*input:\s*"([^"]+)"\s*,\s*output:\s*"([^"]+)"\s*,\s*match:\s*"((?:[^"\\]|\\.)*)"\s*,\s*replace:\s*"((?:[^"\\]|\\.)*)"\s*\}',
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re.DOTALL,
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)
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derived: dict[str, str] = {}
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for m in rewrite_re.finditer(content):
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in_field, out_field, match_pat, replace_val = m.group(1), m.group(2), m.group(3), m.group(4)
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src_val = extracted.get(in_field)
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if src_val is None:
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continue
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try:
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m2 = re.search(match_pat, str(src_val))
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except re.error:
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continue
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if not m2:
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continue
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# SDL uses $0 for whole match, $1.. for groups. Translate to Python
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# \g<0>, \g<1>, ... so re.sub doesn't read \0 as a null byte.
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def _to_py_backref(s: str) -> str:
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return re.sub(r"\$(\d+)", lambda mm: f"\\g<{mm.group(1)}>", s)
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try:
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val = re.sub(match_pat, _to_py_backref(replace_val), str(src_val), count=1)
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except re.error:
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val = replace_val
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derived[out_field] = val
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rewrites_applied.append({
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"input": in_field, "input_value": src_val,
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"output": out_field, "matched_on": match_pat, "result": val,
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})
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fields = (
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[{"field": k, "value": v, "source": "json-extract"} for k, v in sorted(extracted.items())]
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+ [{"field": k, "value": v, "source": "rewrite"} for k, v in sorted(derived.items())]
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)
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return {
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"parser_name": req.parser_name,
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"matched": True,
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"mode": "json",
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"format_matched": "$=json{parse=json}$",
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"fields": fields,
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"rewrites_applied": rewrites_applied,
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"extracted_count": len(extracted),
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"derived_count": len(derived),
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"payload_count": len(payloads),
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"parse_errors": parse_errors,
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"showing_payload": 1,
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}
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# ── Regex format-string path (original) ─────────────────────────────────
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for fmt in format_strings:
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try:
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compiled, py_to_sdl = _sdl_format_to_regex(fmt)
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except re.error:
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# Skip unparseable format strings
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continue
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match = compiled.search(req.log_line)
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if match:
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fields = [
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{"field": py_to_sdl.get(group, group), "value": value}
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for group, value in match.groupdict().items()
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if value is not None
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]
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return {
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"parser_name": req.parser_name,
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"matched": True,
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"mode": "regex",
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"format_matched": fmt,
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"fields": fields,
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}
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return {
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"parser_name": req.parser_name,
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"matched": False,
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"message": "No format pattern matched",
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"fields": [],
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}
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