| 1 | from datetime import datetime |
| 2 | from typing import Dict |
| 3 | from typing import List |
| 4 | from typing import Optional |
| 5 | from typing import Union |
| 6 | |
| 7 | import httpx |
| 8 | from fastapi import HTTPException |
| 9 | from loguru import logger |
| 10 | from sqlalchemy.ext.asyncio import AsyncSession |
| 11 | |
| 12 | from app.connectors.velociraptor.schema.artifacts import ArtifactParametersResponse |
| 13 | from app.connectors.velociraptor.schema.artifacts import ArtifactReccomendationRequest |
| 14 | from app.connectors.velociraptor.schema.artifacts import ArtifactReccomendationResponse |
| 15 | from app.connectors.velociraptor.schema.artifacts import Artifacts |
| 16 | from app.connectors.velociraptor.schema.artifacts import ArtifactsResponse |
| 17 | from app.connectors.velociraptor.schema.artifacts import CollectArtifactBody |
| 18 | from app.connectors.velociraptor.schema.artifacts import CollectArtifactResponse |
| 19 | from app.connectors.velociraptor.schema.artifacts import CollectFileBody |
| 20 | from app.connectors.velociraptor.schema.artifacts import ParameterKeyValue |
| 21 | from app.connectors.velociraptor.schema.artifacts import QuarantineBody |
| 22 | from app.connectors.velociraptor.schema.artifacts import QuarantineResponse |
| 23 | from app.connectors.velociraptor.schema.artifacts import RunCommandBody |
| 24 | from app.connectors.velociraptor.schema.artifacts import RunCommandResponse |
| 25 | from app.connectors.velociraptor.utils.universal import UniversalService |
| 26 | |
| 27 | |
| 28 | def create_query(query: str) -> str: |
| 29 | """ |
| 30 | Create a query string. |
| 31 | |
| 32 | Args: |
| 33 | query (str): The query to be executed. |
| 34 | |
| 35 | Returns: |
| 36 | str: The created query string. |
| 37 | """ |
| 38 | return query |
| 39 | |
| 40 | |
| 41 | def get_artifact_key(analyzer_body: CollectArtifactBody) -> str: |
| 42 | """ |
| 43 | Construct the artifact key. |
| 44 | |
| 45 | Args: |
| 46 | analyzer_body: The collector body with artifact details |
| 47 | |
| 48 | Returns: |
| 49 | str: The constructed artifact key. |
| 50 | """ |
| 51 | action = getattr(analyzer_body, "action", None) |
| 52 | command = getattr(analyzer_body, "command", None) |
| 53 | parameters = getattr(analyzer_body, "parameters", None) |
| 54 | |
| 55 | if action == "quarantine": |
| 56 | return ( |
| 57 | f'collect_client(org_id="{analyzer_body.velociraptor_org}", client_id="{analyzer_body.velociraptor_id}", ' |
| 58 | f'artifacts=["{analyzer_body.artifact_name}"], ' |
| 59 | f"spec=dict(`{analyzer_body.artifact_name}`=dict()))" |
| 60 | ) |
| 61 | elif action == "remove_quarantine": |
| 62 | return ( |
| 63 | f'collect_client(org_id="{analyzer_body.velociraptor_org}", client_id="{analyzer_body.velociraptor_id}", ' |
| 64 | f'artifacts=["{analyzer_body.artifact_name}"], ' |
| 65 | f'spec=dict(`{analyzer_body.artifact_name}`=dict(`RemovePolicy`="Y")))' |
| 66 | ) |
| 67 | elif command is not None: |
| 68 | return ( |
| 69 | f"collect_client(org_id='{analyzer_body.velociraptor_org}', client_id='{analyzer_body.velociraptor_id}', " |
| 70 | f"urgent=true, artifacts=['{analyzer_body.artifact_name}'], " |
| 71 | f"env=dict(Command='{analyzer_body.command}'))" |
| 72 | ) |
| 73 | elif parameters is not None: |
| 74 | # Parameters are provided, will be included in the query |
| 75 | return ( |
| 76 | f"collect_client(org_id='{analyzer_body.velociraptor_org}', client_id='{analyzer_body.velociraptor_id}', " |
| 77 | f"artifacts=['{analyzer_body.artifact_name}'])" |
| 78 | ) |
| 79 | else: |
| 80 | return ( |
| 81 | f"collect_client(org_id='{analyzer_body.velociraptor_org}', client_id='{analyzer_body.velociraptor_id}', " |
| 82 | f"artifacts=['{analyzer_body.artifact_name}'])" |
| 83 | ) |
| 84 | |
| 85 | |
| 86 | async def get_artifacts() -> ArtifactsResponse: |
| 87 | """ |
| 88 | Get all artifacts from Velociraptor. |
| 89 | |
| 90 | Returns: |
| 91 | ArtifactsResponse: A dictionary containing the artifacts. |
| 92 | """ |
| 93 | logger.info("Fetching artifacts from Velociraptor") |
| 94 | velociraptor_service = await UniversalService.create("Velociraptor") |
| 95 | query = create_query("SELECT name,description,parameters FROM artifact_definitions()") |
| 96 | all_artifacts = velociraptor_service.execute_query(query) |
| 97 | try: |
| 98 | if all_artifacts["success"]: |
| 99 | artifacts = [Artifacts(**artifact) for artifact in all_artifacts["results"]] |
| 100 | return ArtifactsResponse( |
| 101 | success=True, |
| 102 | message="All artifacts retrieved", |
| 103 | artifacts=artifacts, |
| 104 | ) |
| 105 | else: |
| 106 | raise HTTPException( |
| 107 | status_code=500, |
| 108 | detail=f"Failed to get all artifacts: {all_artifacts['message']}", |
| 109 | ) |
| 110 | except Exception as err: |
| 111 | logger.error(f"Failed to get all artifacts: {err}") |
| 112 | raise HTTPException( |
| 113 | status_code=500, |
| 114 | detail=f"Failed to get all artifacts: {err}", |
| 115 | ) |
| 116 | |
| 117 | |
| 118 | async def get_artifact_by_name(artifact_name: str) -> ArtifactsResponse: |
| 119 | """ |
| 120 | Get a specific artifact by name from Velociraptor. |
| 121 | |
| 122 | Args: |
| 123 | artifact_name (str): The name of the artifact to retrieve. |
| 124 | |
| 125 | Returns: |
| 126 | ArtifactsResponse: A response containing the specific artifact. |
| 127 | """ |
| 128 | logger.info(f"Fetching artifact '{artifact_name}' from Velociraptor") |
| 129 | velociraptor_service = await UniversalService.create("Velociraptor") |
| 130 | |
| 131 | # Query for a specific artifact by name |
| 132 | query = create_query(f"SELECT name,description,parameters FROM artifact_definitions() WHERE name = '{artifact_name}'") |
| 133 | artifact_result = velociraptor_service.execute_query(query) |
| 134 | |
| 135 | try: |
| 136 | if artifact_result["success"]: |
| 137 | if artifact_result["results"]: |
| 138 | artifacts = [Artifacts(**artifact) for artifact in artifact_result["results"]] |
| 139 | return ArtifactsResponse( |
| 140 | success=True, |
| 141 | message=f"Artifact '{artifact_name}' retrieved successfully", |
| 142 | artifacts=artifacts, |
| 143 | ) |
| 144 | else: |
| 145 | return ArtifactsResponse( |
| 146 | success=True, |
| 147 | message=f"Artifact '{artifact_name}' not found", |
| 148 | artifacts=[], |
| 149 | ) |
| 150 | else: |
| 151 | raise HTTPException( |
| 152 | status_code=500, |
| 153 | detail=f"Failed to get artifact '{artifact_name}': {artifact_result['message']}", |
| 154 | ) |
| 155 | except Exception as err: |
| 156 | logger.error(f"Failed to get artifact '{artifact_name}': {err}") |
| 157 | raise HTTPException( |
| 158 | status_code=500, |
| 159 | detail=f"Failed to get artifact '{artifact_name}': {err}", |
| 160 | ) |
| 161 | |
| 162 | |
| 163 | async def validate_artifact_parameters( |
| 164 | artifact_name: str, |
| 165 | provided_parameters: Optional[Dict[str, Union[str, List[ParameterKeyValue]]]], |
| 166 | ) -> None: |
| 167 | """ |
| 168 | Validates that the provided parameters match the artifact's expected parameters. |
| 169 | |
| 170 | Args: |
| 171 | artifact_name (str): The name of the artifact to validate against. |
| 172 | provided_parameters (Optional[Dict]): The parameters provided in the request. |
| 173 | |
| 174 | Raises: |
| 175 | HTTPException: If any provided parameter is not valid for the artifact. |
| 176 | """ |
| 177 | if not provided_parameters: |
| 178 | return # No parameters to validate |
| 179 | |
| 180 | # Fetch the artifact details |
| 181 | artifact_response = await get_artifact_by_name(artifact_name) |
| 182 | |
| 183 | if not artifact_response.artifacts or len(artifact_response.artifacts) == 0: |
| 184 | raise HTTPException( |
| 185 | status_code=404, |
| 186 | detail=f"Artifact {artifact_name} not found", |
| 187 | ) |
| 188 | |
| 189 | artifact = artifact_response.artifacts[0] |
| 190 | |
| 191 | # If the artifact has no parameters defined, reject any provided parameters |
| 192 | if not artifact.parameters: |
| 193 | raise HTTPException( |
| 194 | status_code=400, |
| 195 | detail=f"Artifact {artifact_name} does not accept any parameters", |
| 196 | ) |
| 197 | |
| 198 | # Get valid parameter names from the artifact |
| 199 | valid_param_names = {param.name for param in artifact.parameters} |
| 200 | |
| 201 | logger.info(f"Valid parameters for artifact {artifact_name}: {valid_param_names}") |
| 202 | logger.info(f"Provided parameters for artifact {artifact_name}: {provided_parameters}") |
| 203 | |
| 204 | # Check if provided parameters are valid |
| 205 | # Handle both direct key-value pairs and the 'env' list format |
| 206 | if isinstance(provided_parameters, dict): |
| 207 | if "env" in provided_parameters and isinstance(provided_parameters["env"], list): |
| 208 | # Handle env list format |
| 209 | for param_pair in provided_parameters["env"]: |
| 210 | # Check if it's a ParameterKeyValue model or a dict |
| 211 | if isinstance(param_pair, ParameterKeyValue): |
| 212 | param_name = param_pair.key |
| 213 | elif isinstance(param_pair, dict) and "key" in param_pair: |
| 214 | param_name = param_pair["key"] |
| 215 | else: |
| 216 | continue |
| 217 | |
| 218 | if param_name not in valid_param_names: |
| 219 | raise HTTPException( |
| 220 | status_code=400, |
| 221 | detail=f"Parameter '{param_name}' is not valid for artifact {artifact_name}. Valid parameters: {', '.join(sorted(valid_param_names))}", |
| 222 | ) |
| 223 | else: |
| 224 | # Handle direct key-value format |
| 225 | for param_name in provided_parameters.keys(): |
| 226 | if param_name not in valid_param_names: |
| 227 | raise HTTPException( |
| 228 | status_code=400, |
| 229 | detail=f"Parameter '{param_name}' is not valid for artifact {artifact_name}. Valid parameters: {', '.join(sorted(valid_param_names))}", |
| 230 | ) |
| 231 | |
| 232 | logger.info(f"All provided parameters are valid for artifact {artifact_name}") |
| 233 | |
| 234 | |
| 235 | async def get_artifact_parameters_by_prefix_service( |
| 236 | artifact_name: str, |
| 237 | parameter_prefix: str, |
| 238 | ) -> ArtifactParametersResponse: |
| 239 | """ |
| 240 | Get parameters from a specific artifact that match a given prefix. |
| 241 | |
| 242 | Args: |
| 243 | artifact_name (str): The name of the artifact to retrieve parameters from. |
| 244 | parameter_prefix (str): The prefix to filter parameters by. |
| 245 | |
| 246 | Returns: |
| 247 | ArtifactParametersResponse: A response containing matching parameters. |
| 248 | """ |
| 249 | logger.info(f"Fetching parameters with prefix '{parameter_prefix}' from artifact '{artifact_name}'") |
| 250 | |
| 251 | try: |
| 252 | # First, get the artifact with its parameters |
| 253 | artifact_response = await get_artifact_by_name(artifact_name) |
| 254 | |
| 255 | if not artifact_response.success or not artifact_response.artifacts: |
| 256 | return ArtifactParametersResponse( |
| 257 | success=False, |
| 258 | message=f"Artifact '{artifact_name}' not found", |
| 259 | artifact_name=artifact_name, |
| 260 | parameter_prefix=parameter_prefix, |
| 261 | matching_parameters=[], |
| 262 | total_matches=0, |
| 263 | ) |
| 264 | |
| 265 | artifact = artifact_response.artifacts[0] |
| 266 | |
| 267 | # Filter parameters by prefix |
| 268 | matching_parameters = [] |
| 269 | if artifact.parameters: |
| 270 | for param in artifact.parameters: |
| 271 | if param.name.startswith(parameter_prefix): |
| 272 | matching_parameters.append(param) |
| 273 | |
| 274 | # Sort the matching parameters for consistent ordering |
| 275 | matching_parameters.sort(key=lambda x: x.name) |
| 276 | |
| 277 | total_matches = len(matching_parameters) |
| 278 | |
| 279 | if total_matches == 0: |
| 280 | message = f"No parameters found matching prefix '{parameter_prefix}' in artifact '{artifact_name}'" |
| 281 | elif total_matches == 1: |
| 282 | message = f"Found 1 parameter matching prefix '{parameter_prefix}' in artifact '{artifact_name}'" |
| 283 | else: |
| 284 | message = f"Found {total_matches} parameters matching prefix '{parameter_prefix}' in artifact '{artifact_name}'" |
| 285 | |
| 286 | logger.info(message) |
| 287 | |
| 288 | return ArtifactParametersResponse( |
| 289 | success=True, |
| 290 | message=message, |
| 291 | artifact_name=artifact_name, |
| 292 | parameter_prefix=parameter_prefix, |
| 293 | matching_parameters=matching_parameters, |
| 294 | total_matches=total_matches, |
| 295 | ) |
| 296 | |
| 297 | except Exception as err: |
| 298 | error_message = f"Failed to get parameters with prefix '{parameter_prefix}' from artifact '{artifact_name}': {err}" |
| 299 | logger.error(error_message) |
| 300 | raise HTTPException( |
| 301 | status_code=500, |
| 302 | detail=error_message, |
| 303 | ) |
| 304 | |
| 305 | |
| 306 | # async def run_artifact_collection( |
| 307 | # collect_artifact_body: CollectArtifactBody, |
| 308 | # ) -> CollectArtifactResponse: |
| 309 | # """ |
| 310 | # Run an artifact collection on a client with optional parameters. |
| 311 | |
| 312 | # Args: |
| 313 | # collect_artifact_body: The body of the request with optional parameters. |
| 314 | |
| 315 | # Returns: |
| 316 | # CollectArtifactResponse: A dictionary containing the success status, message and results. |
| 317 | # """ |
| 318 | # velociraptor_service = await UniversalService.create("Velociraptor") |
| 319 | # try: |
| 320 | # # Build the query dynamically based on whether parameters are provided |
| 321 | # parameters = getattr(collect_artifact_body, "parameters", None) |
| 322 | |
| 323 | # if parameters: |
| 324 | # # Velociraptor expects parameters in a very specific format |
| 325 | # # For the "env" parameter, we need to construct a dict |
| 326 | # if "env" in parameters and isinstance(parameters["env"], list): |
| 327 | # env_dict = {} |
| 328 | # for item in parameters["env"]: |
| 329 | # env_dict[item.key] = item.value |
| 330 | |
| 331 | # # Format the query with proper VQL syntax |
| 332 | # query = create_query( |
| 333 | # f"SELECT collect_client(" |
| 334 | # f"org_id='{collect_artifact_body.velociraptor_org}', " |
| 335 | # f"client_id='{collect_artifact_body.velociraptor_id}', " |
| 336 | # f"artifacts=['{collect_artifact_body.artifact_name}'], " |
| 337 | # f"env=dict(", |
| 338 | # ) |
| 339 | |
| 340 | # # Add each environment variable as a key-value pair |
| 341 | # env_parts = [] |
| 342 | # for key, value in env_dict.items(): |
| 343 | # # Escape any single quotes in the values |
| 344 | # escaped_value = value.replace("'", "\\'") |
| 345 | # env_parts.append(f"`{key}`='{escaped_value}'") |
| 346 | |
| 347 | # query += ", ".join(env_parts) |
| 348 | # query += ")) FROM scope()" |
| 349 | # else: |
| 350 | # # Handle other types of parameters |
| 351 | # query = create_query( |
| 352 | # f"SELECT collect_client(" |
| 353 | # f"org_id='{collect_artifact_body.velociraptor_org}', " |
| 354 | # f"client_id='{collect_artifact_body.velociraptor_id}', " |
| 355 | # f"artifacts=['{collect_artifact_body.artifact_name}']", |
| 356 | # ) |
| 357 | |
| 358 | # # Add other parameters if needed |
| 359 | # for param_key, param_value in parameters.items(): |
| 360 | # if isinstance(param_value, str): |
| 361 | # query += f", `{param_key}`='{param_value}'" |
| 362 | |
| 363 | # query += ") FROM scope()" |
| 364 | # else: |
| 365 | # # Original query without parameters |
| 366 | # query = create_query( |
| 367 | # f"SELECT collect_client(" |
| 368 | # f"org_id='{collect_artifact_body.velociraptor_org}', " |
| 369 | # f"client_id='{collect_artifact_body.velociraptor_id}', " |
| 370 | # f"artifacts=['{collect_artifact_body.artifact_name}']) " |
| 371 | # f"FROM scope()", |
| 372 | # ) |
| 373 | |
| 374 | # logger.info(f"Running artifact collection with query: {query}") |
| 375 | # flow = velociraptor_service.execute_query(query, org_id=collect_artifact_body.velociraptor_org) |
| 376 | # logger.info(f"Successfully ran artifact collection on {flow}") |
| 377 | |
| 378 | # # Check if results are available |
| 379 | # if not flow.get("results") or len(flow["results"]) == 0: |
| 380 | # logger.error("No results returned from query execution") |
| 381 | # raise HTTPException( |
| 382 | # status_code=500, |
| 383 | # detail="Query execution did not return any results", |
| 384 | # ) |
| 385 | |
| 386 | # # Instead of relying on get_artifact_key, extract the flow_id directly from results |
| 387 | # # by checking all keys in the first result for a flow_id |
| 388 | # result_dict = flow["results"][0] |
| 389 | # flow_id = None |
| 390 | |
| 391 | # # Look for any key that has a flow_id in its value |
| 392 | # for key, value in result_dict.items(): |
| 393 | # if isinstance(value, dict) and "flow_id" in value: |
| 394 | # flow_id = value["flow_id"] |
| 395 | # logger.debug(f"Found flow_id {flow_id} in key: {key}") |
| 396 | # break |
| 397 | |
| 398 | # if not flow_id: |
| 399 | # logger.error(f"Could not find flow_id in results: {result_dict}") |
| 400 | # raise HTTPException( |
| 401 | # status_code=500, |
| 402 | # detail="Failed to extract flow ID from results", |
| 403 | # ) |
| 404 | |
| 405 | # logger.info(f"Extracted flow_id: {flow_id}") |
| 406 | |
| 407 | # completed = velociraptor_service.watch_flow_completion(flow_id, org_id=collect_artifact_body.velociraptor_org) |
| 408 | # logger.info(f"Successfully watched flow completion on {completed}") |
| 409 | |
| 410 | # results = velociraptor_service.read_collection_results( |
| 411 | # client_id=collect_artifact_body.velociraptor_id, |
| 412 | # flow_id=flow_id, |
| 413 | # org_id=collect_artifact_body.velociraptor_org, |
| 414 | # artifact=collect_artifact_body.artifact_name, |
| 415 | # ) |
| 416 | |
| 417 | # logger.info(f"Successfully read collection results on {results}") |
| 418 | |
| 419 | # return CollectArtifactResponse( |
| 420 | # success=results["success"], |
| 421 | # message=results["message"], |
| 422 | # results=results["results"], |
| 423 | # ) |
| 424 | # except HTTPException as he: # Catch HTTPException separately to propagate the original message |
| 425 | # logger.error( |
| 426 | # f"HTTPException while running artifact collection on {collect_artifact_body}: {he.detail}", |
| 427 | # ) |
| 428 | # raise he |
| 429 | # except Exception as err: |
| 430 | # logger.error( |
| 431 | # f"Failed to run artifact collection on {collect_artifact_body}: {err}", |
| 432 | # ) |
| 433 | # raise HTTPException( |
| 434 | # status_code=500, |
| 435 | # detail=f"Failed to run artifact collection on {collect_artifact_body}: {err}", |
| 436 | # ) |
| 437 | |
| 438 | async def run_artifact_collection( |
| 439 | collect_artifact_body: CollectArtifactBody, |
| 440 | session: AsyncSession, |
| 441 | ) -> CollectArtifactResponse: |
| 442 | """ |
| 443 | Run an artifact collection on a client with optional parameters and upload results to MinIO. |
| 444 | |
| 445 | Args: |
| 446 | collect_artifact_body: The body of the request with optional parameters. |
| 447 | session: Database session for storing metadata. |
| 448 | |
| 449 | Returns: |
| 450 | CollectArtifactResponse: A dictionary containing the success status, message and results. |
| 451 | """ |
| 452 | from sqlalchemy import select |
| 453 | |
| 454 | from app.db.universal_models import AgentDataStore |
| 455 | from app.db.universal_models import Agents |
| 456 | |
| 457 | velociraptor_service = await UniversalService.create("Velociraptor") |
| 458 | try: |
| 459 | # Get agent details from database |
| 460 | result = await session.execute( |
| 461 | select(Agents).where(Agents.velociraptor_id == collect_artifact_body.velociraptor_id), |
| 462 | ) |
| 463 | agent = result.scalars().first() |
| 464 | |
| 465 | if not agent: |
| 466 | raise HTTPException( |
| 467 | status_code=404, |
| 468 | detail=f"Agent with velociraptor_id {collect_artifact_body.velociraptor_id} not found", |
| 469 | ) |
| 470 | |
| 471 | # Build the query dynamically based on whether parameters are provided |
| 472 | parameters = getattr(collect_artifact_body, "parameters", None) |
| 473 | |
| 474 | if parameters: |
| 475 | # Velociraptor expects parameters in a very specific format |
| 476 | # For the "env" parameter, we need to construct a dict |
| 477 | if "env" in parameters and isinstance(parameters["env"], list): |
| 478 | env_dict = {} |
| 479 | for item in parameters["env"]: |
| 480 | env_dict[item.key] = item.value |
| 481 | |
| 482 | # Format the query with proper VQL syntax |
| 483 | query = create_query( |
| 484 | f"SELECT collect_client(" |
| 485 | f"org_id='{collect_artifact_body.velociraptor_org}', " |
| 486 | f"client_id='{collect_artifact_body.velociraptor_id}', " |
| 487 | f"artifacts=['{collect_artifact_body.artifact_name}'], " |
| 488 | f"env=dict(", |
| 489 | ) |
| 490 | |
| 491 | # Add each environment variable as a key-value pair |
| 492 | env_parts = [] |
| 493 | for key, value in env_dict.items(): |
| 494 | # Escape any single quotes in the values |
| 495 | escaped_value = value.replace("'", "\\'") |
| 496 | env_parts.append(f"`{key}`='{escaped_value}'") |
| 497 | |
| 498 | query += ", ".join(env_parts) |
| 499 | query += ")) FROM scope()" |
| 500 | else: |
| 501 | # Handle other types of parameters |
| 502 | query = create_query( |
| 503 | f"SELECT collect_client(" |
| 504 | f"org_id='{collect_artifact_body.velociraptor_org}', " |
| 505 | f"client_id='{collect_artifact_body.velociraptor_id}', " |
| 506 | f"artifacts=['{collect_artifact_body.artifact_name}']", |
| 507 | ) |
| 508 | |
| 509 | # Add other parameters if needed |
| 510 | for param_key, param_value in parameters.items(): |
| 511 | if isinstance(param_value, str): |
| 512 | query += f", `{param_key}`='{param_value}'" |
| 513 | |
| 514 | query += ") FROM scope()" |
| 515 | else: |
| 516 | # Original query without parameters |
| 517 | query = create_query( |
| 518 | f"SELECT collect_client(" |
| 519 | f"org_id='{collect_artifact_body.velociraptor_org}', " |
| 520 | f"client_id='{collect_artifact_body.velociraptor_id}', " |
| 521 | f"artifacts=['{collect_artifact_body.artifact_name}']) " |
| 522 | f"FROM scope()", |
| 523 | ) |
| 524 | |
| 525 | logger.info(f"Running artifact collection with query: {query}") |
| 526 | flow = velociraptor_service.execute_query(query, org_id=collect_artifact_body.velociraptor_org) |
| 527 | logger.info(f"Successfully ran artifact collection on {flow}") |
| 528 | |
| 529 | # Check if results are available |
| 530 | if not flow.get("results") or len(flow["results"]) == 0: |
| 531 | logger.error("No results returned from query execution") |
| 532 | raise HTTPException( |
| 533 | status_code=500, |
| 534 | detail="Query execution did not return any results", |
| 535 | ) |
| 536 | |
| 537 | # Instead of relying on get_artifact_key, extract the flow_id directly from results |
| 538 | # by checking all keys in the first result for a flow_id |
| 539 | result_dict = flow["results"][0] |
| 540 | flow_id = None |
| 541 | |
| 542 | # Look for any key that has a flow_id in its value |
| 543 | for key, value in result_dict.items(): |
| 544 | if isinstance(value, dict) and "flow_id" in value: |
| 545 | flow_id = value["flow_id"] |
| 546 | logger.debug(f"Found flow_id {flow_id} in key: {key}") |
| 547 | break |
| 548 | |
| 549 | if not flow_id: |
| 550 | logger.error(f"Could not find flow_id in results: {result_dict}") |
| 551 | raise HTTPException( |
| 552 | status_code=500, |
| 553 | detail="Failed to extract flow ID from results", |
| 554 | ) |
| 555 | |
| 556 | logger.info(f"Extracted flow_id: {flow_id}") |
| 557 | |
| 558 | completed = velociraptor_service.watch_flow_completion(flow_id, org_id=collect_artifact_body.velociraptor_org) |
| 559 | logger.info(f"Successfully watched flow completion on {completed}") |
| 560 | |
| 561 | # Only read collection results if data_store_only is False |
| 562 | results = None |
| 563 | if not collect_artifact_body.data_store_only: |
| 564 | results = velociraptor_service.read_collection_results( |
| 565 | client_id=collect_artifact_body.velociraptor_id, |
| 566 | flow_id=flow_id, |
| 567 | org_id=collect_artifact_body.velociraptor_org, |
| 568 | artifact=collect_artifact_body.artifact_name, |
| 569 | ) |
| 570 | logger.info(f"Successfully read collection results on {results}") |
| 571 | |
| 572 | # Fetch the collected file from filestore and upload to MinIO |
| 573 | file_data = None |
| 574 | try: |
| 575 | logger.info("Fetching collected file from filestore and uploading to MinIO") |
| 576 | file_data = await fetch_file_from_filestore( |
| 577 | client_id=collect_artifact_body.velociraptor_id, |
| 578 | flow_id=flow_id, |
| 579 | org_id=collect_artifact_body.velociraptor_org, |
| 580 | agent_id=agent.agent_id, |
| 581 | ) |
| 582 | |
| 583 | # Save metadata to database if file upload was successful |
| 584 | if file_data.get("success"): |
| 585 | agent_data_store = AgentDataStore( |
| 586 | agent_id=agent.agent_id, |
| 587 | velociraptor_id=collect_artifact_body.velociraptor_id, |
| 588 | artifact_name=collect_artifact_body.artifact_name, |
| 589 | flow_id=flow_id, |
| 590 | bucket_name=file_data["bucket_name"], |
| 591 | object_key=file_data["object_key"], |
| 592 | file_name=file_data["file_name"], |
| 593 | content_type=file_data.get("content_type", "application/zip"), |
| 594 | file_size=file_data["file_size"], |
| 595 | file_hash=file_data["file_hash"], |
| 596 | collection_time=datetime.utcnow(), |
| 597 | status="completed", |
| 598 | ) |
| 599 | session.add(agent_data_store) |
| 600 | await session.commit() |
| 601 | await session.refresh(agent_data_store) |
| 602 | |
| 603 | logger.info(f"Saved artifact metadata to database with ID {agent_data_store.id}") |
| 604 | except Exception as file_err: |
| 605 | logger.warning(f"Failed to upload file to MinIO, but artifact collection succeeded: {file_err}") |
| 606 | # Continue execution even if file upload fails |
| 607 | |
| 608 | # Build response based on data_store_only flag |
| 609 | if collect_artifact_body.data_store_only: |
| 610 | return CollectArtifactResponse( |
| 611 | success=True, |
| 612 | message="Artifact collected and stored successfully. Results not retrieved.", |
| 613 | results=None, |
| 614 | file_info=file_data if file_data and file_data.get("success") else None, |
| 615 | ) |
| 616 | else: |
| 617 | return CollectArtifactResponse( |
| 618 | success=results["success"], |
| 619 | message=results["message"], |
| 620 | results=results["results"], |
| 621 | file_info=file_data if file_data and file_data.get("success") else None, |
| 622 | ) |
| 623 | except HTTPException as he: # Catch HTTPException separately to propagate the original message |
| 624 | logger.error( |
| 625 | f"HTTPException while running artifact collection on {collect_artifact_body}: {he.detail}", |
| 626 | ) |
| 627 | raise he |
| 628 | except Exception as err: |
| 629 | logger.error( |
| 630 | f"Failed to run artifact collection on {collect_artifact_body}: {err}", |
| 631 | ) |
| 632 | raise HTTPException( |
| 633 | status_code=500, |
| 634 | detail=f"Failed to run artifact collection on {collect_artifact_body}: {err}", |
| 635 | ) |
| 636 | |
| 637 | |
| 638 | async def run_file_collection( |
| 639 | collect_artifact_body: CollectFileBody, |
| 640 | session: AsyncSession, # Add this parameter |
| 641 | ) -> CollectArtifactResponse: |
| 642 | """ |
| 643 | Run an artifact collection on a client and store the result in MinIO. |
| 644 | """ |
| 645 | from sqlalchemy import select |
| 646 | |
| 647 | from app.db.universal_models import AgentDataStore |
| 648 | from app.db.universal_models import Agents |
| 649 | |
| 650 | velociraptor_service = await UniversalService.create("Velociraptor") |
| 651 | |
| 652 | try: |
| 653 | # Get agent details from database |
| 654 | result = await session.execute( |
| 655 | select(Agents).where(Agents.velociraptor_id == collect_artifact_body.velociraptor_id), |
| 656 | ) |
| 657 | agent = result.scalars().first() |
| 658 | |
| 659 | if not agent: |
| 660 | raise HTTPException( |
| 661 | status_code=404, |
| 662 | detail=f"Agent with velociraptor_id {collect_artifact_body.velociraptor_id} not found", |
| 663 | ) |
| 664 | |
| 665 | # Build the query with proper VQL syntax |
| 666 | query = create_query( |
| 667 | f"SELECT collect_client(" |
| 668 | f"org_id='{collect_artifact_body.velociraptor_org}', " |
| 669 | f"client_id='{collect_artifact_body.velociraptor_id}', " |
| 670 | f"artifacts=['{collect_artifact_body.artifact_name}'], " |
| 671 | f"spec=dict(`{collect_artifact_body.artifact_name}`=dict(" |
| 672 | f"`collectionSpec`='{collect_artifact_body.file}', " |
| 673 | f"`Root`='{collect_artifact_body.root_disk}'" |
| 674 | f"))) " |
| 675 | f"FROM scope()", |
| 676 | ) |
| 677 | |
| 678 | logger.info(f"Query: {query}") |
| 679 | flow = velociraptor_service.execute_query(query, org_id=collect_artifact_body.velociraptor_org) |
| 680 | logger.info(f"Successfully ran artifact collection on {flow}") |
| 681 | |
| 682 | # Check if results are available |
| 683 | if not flow.get("results") or len(flow["results"]) == 0: |
| 684 | logger.error("No results returned from query execution") |
| 685 | raise HTTPException( |
| 686 | status_code=500, |
| 687 | detail="Query execution did not return any results", |
| 688 | ) |
| 689 | |
| 690 | # Extract flow_id from results |
| 691 | result_dict = flow["results"][0] |
| 692 | flow_id = None |
| 693 | |
| 694 | for key, value in result_dict.items(): |
| 695 | if isinstance(value, dict) and "flow_id" in value: |
| 696 | flow_id = value["flow_id"] |
| 697 | logger.debug(f"Found flow_id {flow_id} in key: {key}") |
| 698 | break |
| 699 | |
| 700 | if not flow_id: |
| 701 | logger.error(f"Could not find flow_id in results: {result_dict}") |
| 702 | raise HTTPException( |
| 703 | status_code=500, |
| 704 | detail="Failed to extract flow ID from results", |
| 705 | ) |
| 706 | |
| 707 | logger.info(f"Extracted flow_id: {flow_id}") |
| 708 | |
| 709 | completed = velociraptor_service.watch_flow_completion(flow_id, org_id=collect_artifact_body.velociraptor_org) |
| 710 | logger.info(f"Successfully watched flow completion on {completed}") |
| 711 | |
| 712 | results = velociraptor_service.read_collection_results( |
| 713 | client_id=collect_artifact_body.velociraptor_id, |
| 714 | flow_id=flow_id, |
| 715 | org_id=collect_artifact_body.velociraptor_org, |
| 716 | artifact=collect_artifact_body.artifact_name, |
| 717 | ) |
| 718 | |
| 719 | logger.info("Successfully read collection results") |
| 720 | |
| 721 | # Fetch the collected file from filestore and upload to MinIO |
| 722 | logger.info("Fetching collected file from filestore and uploading to MinIO") |
| 723 | file_data = await fetch_file_from_filestore( |
| 724 | client_id=collect_artifact_body.velociraptor_id, |
| 725 | flow_id=flow_id, |
| 726 | org_id=collect_artifact_body.velociraptor_org, |
| 727 | agent_id=agent.agent_id, |
| 728 | ) |
| 729 | |
| 730 | # Save metadata to database |
| 731 | if file_data.get("success"): |
| 732 | agent_data_store = AgentDataStore( |
| 733 | agent_id=agent.agent_id, |
| 734 | velociraptor_id=collect_artifact_body.velociraptor_id, |
| 735 | artifact_name=collect_artifact_body.artifact_name, |
| 736 | flow_id=flow_id, |
| 737 | bucket_name=file_data["bucket_name"], |
| 738 | object_key=file_data["object_key"], |
| 739 | file_name=file_data["file_name"], |
| 740 | content_type=file_data.get("content_type", "application/zip"), |
| 741 | file_size=file_data["file_size"], |
| 742 | file_hash=file_data["file_hash"], |
| 743 | collection_time=datetime.utcnow(), |
| 744 | status="completed", |
| 745 | ) |
| 746 | session.add(agent_data_store) |
| 747 | await session.commit() |
| 748 | await session.refresh(agent_data_store) |
| 749 | |
| 750 | logger.info(f"Saved artifact metadata to database with ID {agent_data_store.id}") |
| 751 | |
| 752 | return CollectArtifactResponse( |
| 753 | success=results["success"], |
| 754 | message=results["message"], |
| 755 | results=results["results"], |
| 756 | file_info=file_data if file_data.get("success") else None, |
| 757 | ) |
| 758 | |
| 759 | except HTTPException as he: |
| 760 | logger.error(f"HTTPException while running artifact collection: {he.detail}") |
| 761 | raise he |
| 762 | except Exception as err: |
| 763 | logger.error(f"Failed to run artifact collection: {err}") |
| 764 | raise HTTPException( |
| 765 | status_code=500, |
| 766 | detail=f"Failed to run artifact collection: {err}", |
| 767 | ) |
| 768 | |
| 769 | |
| 770 | async def fetch_file_from_filestore( |
| 771 | client_id: str, |
| 772 | flow_id: str, |
| 773 | org_id: str, |
| 774 | agent_id: str, # Add this parameter |
| 775 | hostname: Optional[str] = None, |
| 776 | password: Optional[str] = None, |
| 777 | format: str = "json", |
| 778 | expand_sparse: bool = False, |
| 779 | ) -> dict: |
| 780 | """ |
| 781 | Fetch a file from Velociraptor's filestore and save it to MinIO. |
| 782 | First creates a download pack for the flow, then fetches and uploads to MinIO. |
| 783 | """ |
| 784 | import base64 |
| 785 | import os |
| 786 | |
| 787 | from app.data_store.data_store_operations import upload_agent_artifact_file |
| 788 | |
| 789 | velociraptor_service = await UniversalService.create("Velociraptor") |
| 790 | |
| 791 | try: |
| 792 | # If hostname is not provided, fetch it from client metadata |
| 793 | if not hostname: |
| 794 | logger.info(f"Fetching hostname for client {client_id}") |
| 795 | query = create_query( |
| 796 | f"SELECT os_info.hostname AS Hostname " |
| 797 | f"FROM clients(client_id='{client_id}')", |
| 798 | ) |
| 799 | client_info = velociraptor_service.execute_query(query, org_id=org_id) |
| 800 | |
| 801 | if client_info.get("results") and len(client_info["results"]) > 0: |
| 802 | hostname = client_info["results"][0].get("Hostname", client_id) |
| 803 | else: |
| 804 | hostname = client_id |
| 805 | logger.warning(f"Could not fetch hostname, using client_id: {client_id}") |
| 806 | |
| 807 | # Step 1: Create the flow download |
| 808 | logger.info(f"Creating flow download for client {client_id}, flow {flow_id}") |
| 809 | |
| 810 | download_query_parts = [ |
| 811 | f"client_id='{client_id}'", |
| 812 | f"flow_id='{flow_id}'", |
| 813 | "wait=true", |
| 814 | f"format='{format}'", |
| 815 | f"expand_sparse={str(expand_sparse).lower()}", |
| 816 | ] |
| 817 | |
| 818 | if password: |
| 819 | download_query_parts.append(f"password='{password}'") |
| 820 | |
| 821 | zip_filename = f"{hostname}-{client_id}-{flow_id}.zip" |
| 822 | download_query_parts.append(f"name='{hostname}-{client_id}-{flow_id}'") |
| 823 | |
| 824 | create_download_query = create_query( |
| 825 | f"SELECT create_flow_download({', '.join(download_query_parts)}) " |
| 826 | f"FROM scope()", |
| 827 | ) |
| 828 | |
| 829 | logger.info(f"Create download query: {create_download_query}") |
| 830 | download_result = velociraptor_service.execute_query(create_download_query, org_id=org_id) |
| 831 | |
| 832 | if not download_result.get("success"): |
| 833 | raise HTTPException( |
| 834 | status_code=500, |
| 835 | detail=f"Failed to create flow download: {download_result.get('message')}", |
| 836 | ) |
| 837 | |
| 838 | logger.info("Flow download created successfully") |
| 839 | |
| 840 | # Step 2: Fetch the file from Velociraptor |
| 841 | vfs_path = f"downloads/{client_id}/{flow_id}/{zip_filename}" |
| 842 | logger.info(f"Fetching file from VFS path: {vfs_path}") |
| 843 | |
| 844 | # Save to temporary location first |
| 845 | temp_file_path = os.path.join(os.getcwd(), zip_filename) |
| 846 | offset = 0 |
| 847 | chunk_size = 1024 * 1024 # 1MB chunks |
| 848 | total_bytes = 0 |
| 849 | |
| 850 | with open(temp_file_path, 'wb') as f: |
| 851 | while True: |
| 852 | query = create_query( |
| 853 | f"SELECT base64encode(string=read_file(" |
| 854 | f"accessor='fs', " |
| 855 | f"filename='/{vfs_path}', " |
| 856 | f"offset={offset}, " |
| 857 | f"length={chunk_size})) AS Data " |
| 858 | f"FROM scope()", |
| 859 | ) |
| 860 | |
| 861 | result = velociraptor_service.execute_query(query, org_id=org_id) |
| 862 | |
| 863 | if not result.get("success"): |
| 864 | raise HTTPException( |
| 865 | status_code=500, |
| 866 | detail=f"Failed to fetch file chunk: {result.get('message')}", |
| 867 | ) |
| 868 | |
| 869 | if not result.get("results") or len(result["results"]) == 0: |
| 870 | break |
| 871 | |
| 872 | data = result["results"][0].get("Data") |
| 873 | if not data: |
| 874 | break |
| 875 | |
| 876 | try: |
| 877 | decoded_data = base64.b64decode(data) |
| 878 | if len(decoded_data) == 0: |
| 879 | break |
| 880 | |
| 881 | f.write(decoded_data) |
| 882 | chunk_bytes = len(decoded_data) |
| 883 | total_bytes += chunk_bytes |
| 884 | offset += chunk_bytes |
| 885 | |
| 886 | logger.debug(f"Fetched {chunk_bytes} bytes, total: {total_bytes}") |
| 887 | |
| 888 | if chunk_bytes < chunk_size: |
| 889 | break |
| 890 | except Exception as e: |
| 891 | logger.error(f"Failed to decode chunk: {e}") |
| 892 | break |
| 893 | |
| 894 | if total_bytes == 0: |
| 895 | logger.warning(f"No file data found at path: {vfs_path}") |
| 896 | if os.path.exists(temp_file_path): |
| 897 | os.remove(temp_file_path) |
| 898 | return { |
| 899 | "success": False, |
| 900 | "message": f"No file found at path: {vfs_path}", |
| 901 | "file_path": None, |
| 902 | "file_size": 0, |
| 903 | } |
| 904 | |
| 905 | logger.info(f"Successfully fetched file of size {total_bytes} bytes") |
| 906 | |
| 907 | # Step 3: Upload to MinIO |
| 908 | logger.info(f"Uploading artifact file to MinIO for agent {agent_id}") |
| 909 | upload_result = await upload_agent_artifact_file( |
| 910 | agent_id=agent_id, |
| 911 | flow_id=flow_id, |
| 912 | file_path=temp_file_path, |
| 913 | file_name=zip_filename, |
| 914 | ) |
| 915 | |
| 916 | # Remove temporary file |
| 917 | os.remove(temp_file_path) |
| 918 | logger.info(f"Removed temporary file {temp_file_path}") |
| 919 | |
| 920 | return { |
| 921 | "success": True, |
| 922 | "message": "Successfully fetched file from Velociraptor and uploaded to MinIO", |
| 923 | **upload_result, |
| 924 | } |
| 925 | |
| 926 | except HTTPException as he: |
| 927 | logger.error(f"HTTPException while fetching file: {he.detail}") |
| 928 | raise he |
| 929 | except Exception as err: |
| 930 | logger.error(f"Failed to fetch file from filestore: {err}") |
| 931 | raise HTTPException( |
| 932 | status_code=500, |
| 933 | detail=f"Failed to fetch file from filestore: {err}", |
| 934 | ) |
| 935 | |
| 936 | |
| 937 | async def run_remote_command(run_command_body: RunCommandBody) -> RunCommandResponse: |
| 938 | """ |
| 939 | Run a remote command on a client. |
| 940 | |
| 941 | Args: |
| 942 | run_analyzer_body (RunAnalyzerBody): The body of the request. |
| 943 | |
| 944 | Returns: |
| 945 | RunAnalyzerResponse: A dictionary containing the success status and a message. |
| 946 | """ |
| 947 | velociraptor_service = await UniversalService.create("Velociraptor") |
| 948 | try: |
| 949 | run_command_body.artifact_name = run_command_body.artifact_name.value |
| 950 | logger.info(f"Running remote command on {run_command_body}") |
| 951 | query = create_query( |
| 952 | ( |
| 953 | f"SELECT collect_client(org_id='{run_command_body.velociraptor_org}', client_id='{run_command_body.velociraptor_id}', " |
| 954 | f"urgent=true, artifacts=['{run_command_body.artifact_name}'], " |
| 955 | f"env=dict(Command='{run_command_body.command}')) " |
| 956 | "FROM scope()" |
| 957 | ), |
| 958 | ) |
| 959 | flow = velociraptor_service.execute_query(query, org_id=run_command_body.velociraptor_org) |
| 960 | logger.info(f"Successfully ran artifact collection on {flow}") |
| 961 | |
| 962 | artifact_key = get_artifact_key(analyzer_body=run_command_body) |
| 963 | |
| 964 | flow_id = flow["results"][0][artifact_key]["flow_id"] |
| 965 | logger.info(f"Extracted flow_id: {flow_id}") |
| 966 | |
| 967 | completed = velociraptor_service.watch_flow_completion(flow_id, org_id=run_command_body.velociraptor_org) |
| 968 | logger.info(f"Successfully watched flow completion on {completed}") |
| 969 | |
| 970 | results = velociraptor_service.read_collection_results( |
| 971 | client_id=run_command_body.velociraptor_id, |
| 972 | flow_id=flow_id, |
| 973 | org_id=run_command_body.velociraptor_org, |
| 974 | artifact=run_command_body.artifact_name, |
| 975 | ) |
| 976 | |
| 977 | logger.info(f"Successfully read collection results on {results}") |
| 978 | |
| 979 | return RunCommandResponse( |
| 980 | success=results["success"], |
| 981 | message=results["message"], |
| 982 | results=results["results"], |
| 983 | ) |
| 984 | except Exception as err: |
| 985 | logger.error(f"Failed to run artifact collection on {run_command_body}: {err}") |
| 986 | raise HTTPException( |
| 987 | status_code=500, |
| 988 | detail=f"Failed to run artifact collection on {run_command_body}: {err}", |
| 989 | ) |
| 990 | |
| 991 | |
| 992 | async def quarantine_host(quarantine_body: QuarantineBody) -> QuarantineResponse: |
| 993 | """ |
| 994 | Quarantine a host. |
| 995 | |
| 996 | Args: |
| 997 | quarantine_body (QuarantineBody): The body of the request. |
| 998 | |
| 999 | Returns: |
| 1000 | QuarantineResponse: A dictionary containing the success status and a message. |
| 1001 | """ |
| 1002 | velociraptor_service = await UniversalService.create("Velociraptor") |
| 1003 | try: |
| 1004 | quarantine_body.artifact_name = quarantine_body.artifact_name.value |
| 1005 | quarantine_body.action = quarantine_body.action.value |
| 1006 | if quarantine_body.action == "quarantine": |
| 1007 | query = create_query( |
| 1008 | ( |
| 1009 | f'SELECT collect_client(org_id="{quarantine_body.velociraptor_org}", client_id="{quarantine_body.velociraptor_id}", ' |
| 1010 | f'artifacts=["{quarantine_body.artifact_name}"], ' |
| 1011 | f"spec=dict(`{quarantine_body.artifact_name}`=dict())) " |
| 1012 | "FROM scope()" |
| 1013 | ), |
| 1014 | ) |
| 1015 | else: |
| 1016 | query = create_query( |
| 1017 | ( |
| 1018 | f'SELECT collect_client(org_id="{quarantine_body.velociraptor_org}", client_id="{quarantine_body.velociraptor_id}", ' |
| 1019 | f'artifacts=["{quarantine_body.artifact_name}"], ' |
| 1020 | f'spec=dict(`{quarantine_body.artifact_name}`=dict(`RemovePolicy`="Y"))) ' |
| 1021 | "FROM scope()" |
| 1022 | ), |
| 1023 | ) |
| 1024 | flow = velociraptor_service.execute_query(query, org_id=quarantine_body.velociraptor_org) |
| 1025 | logger.info(f"Successfully ran artifact collection on {flow}") |
| 1026 | |
| 1027 | artifact_key = get_artifact_key(analyzer_body=quarantine_body) |
| 1028 | |
| 1029 | flow_id = flow["results"][0][artifact_key]["flow_id"] |
| 1030 | logger.info(f"Extracted flow_id: {flow_id}") |
| 1031 | |
| 1032 | completed = velociraptor_service.watch_flow_completion(flow_id, org_id=quarantine_body.velociraptor_org) |
| 1033 | logger.info(f"Successfully watched flow completion on {completed}") |
| 1034 | |
| 1035 | results = velociraptor_service.read_collection_results( |
| 1036 | client_id=quarantine_body.velociraptor_id, |
| 1037 | flow_id=flow_id, |
| 1038 | org_id=quarantine_body.velociraptor_org, |
| 1039 | artifact=quarantine_body.artifact_name, |
| 1040 | ) |
| 1041 | |
| 1042 | logger.info(f"Successfully read collection results on {results}") |
| 1043 | |
| 1044 | return QuarantineResponse( |
| 1045 | success=results["success"], |
| 1046 | message=results["message"], |
| 1047 | results=results["results"], |
| 1048 | ) |
| 1049 | except Exception as err: |
| 1050 | logger.error(f"Failed to run artifact collection on {quarantine_body}: {err}") |
| 1051 | raise HTTPException( |
| 1052 | status_code=500, |
| 1053 | detail=f"Failed to run artifact collection on {quarantine_body}: {err}", |
| 1054 | ) |
| 1055 | |
| 1056 | |
| 1057 | ################# ! ARTIFACT RECOMMENDATION ! ################# |
| 1058 | async def post_to_copilot_ai_module(data: ArtifactReccomendationRequest) -> ArtifactReccomendationResponse: |
| 1059 | """ |
| 1060 | Send a POST request to the copilot-ai-module Docker container. |
| 1061 | |
| 1062 | Args: |
| 1063 | data (ArtifactReccomendationRequest): The data to send to the copilot-ai-module Docker container. |
| 1064 | """ |
| 1065 | logger.info(f"Sending POST request to http://copilot-ai-module/velociraptor-artifact-recommendation with data: {data.model_dump()}") |
| 1066 | # raise HTTPException(status_code=501, detail="Not Implemented Yet") |
| 1067 | async with httpx.AsyncClient() as client: |
| 1068 | data = await client.post( |
| 1069 | "http://copilot-ai-module/velociraptor-artifact-recommendation", |
| 1070 | json=data.model_dump(), |
| 1071 | timeout=120, |
| 1072 | ) |
| 1073 | response_data = data.json() |
| 1074 | |
| 1075 | if not response_data.get("success"): |
| 1076 | raise HTTPException( |
| 1077 | status_code=400, |
| 1078 | detail=response_data.get("message", "Request to copilot-ai-module was not successful"), |
| 1079 | ) |
| 1080 | return ArtifactReccomendationResponse(**data.json()) |