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OpenEnv Environment for API Integration Testing.
The agent interacts with a deliberately buggy REST API, discovering endpoints,
crafting requests, and finding bugs. Rewards are multi-signal: coverage,
validity, bug discovery, and exploration.
"""
import logging
import random
import time
import json
from typing import Any, Optional
from fastapi.testclient import TestClient
from openenv.core.env_server.interfaces import Environment
try:
from ..models import APITestAction, APITestObservation, APITestState
except ImportError:
from models import APITestAction, APITestObservation, APITestState
from .buggy_api.database import Database
from .buggy_api.main import create_buggy_api
from .bug_detector import BugDetector
from .reward import RewardComputer
from .graders import TaskGrader, generate_bug_report
from .graders import TaskGrader
logger = logging.getLogger(__name__)
# Task definitions
TASKS = {
"basic_validation": {
"id": "basic_validation",
"description": (
"Test all CRUD endpoints with valid inputs and verify correct status codes. "
"Find basic bugs like wrong status codes and missing field handling. "
"Available endpoints: GET /tasks, POST /tasks, GET /tasks/{id}, PUT /tasks/{id}, "
"DELETE /tasks/{id}, GET /users, POST /users, POST /auth/login. "
"Try different methods on each endpoint and verify responses match the expected behavior."
),
"difficulty": "easy",
"max_steps": 25,
"total_bugs": 3,
},
"edge_cases": {
"id": "edge_cases",
"description": (
"Test boundary conditions, invalid inputs, and error responses. "
"Send missing fields, wrong types, negative page numbers, huge limits. "
"Test with non-existent resource IDs (e.g., /tasks/999999). "
"Chain operations: create a resource, then read/update/delete it. "
"Find bugs in input validation, pagination, and error handling."
),
"difficulty": "medium",
"max_steps": 35,
"total_bugs": 9,
},
"security_workflows": {
"id": "security_workflows",
"description": (
"Discover authorization flaws, injection vulnerabilities, and workflow bugs. "
"Login as different users (alice/password, bob/password, charlie/password) and "
"try accessing each other's resources. Test SQL injection patterns in input fields. "
"Execute multi-step workflows: create -> modify -> verify -> delete -> re-fetch. "
"Check if auth tokens properly scope access. Test with very long inputs."
),
"difficulty": "hard",
"max_steps": 45,
"total_bugs": 13,
},
}
# OpenAPI-like spec for the agent
API_SPEC = [
{
"method": "GET",
"path": "/tasks",
"summary": "List all tasks. Supports filtering by status, priority; pagination with page & limit; sorting with sort.",
"parameters": [
{"name": "status", "in": "query", "type": "string", "enum": ["pending", "in_progress", "done"]},
{"name": "priority", "in": "query", "type": "string", "enum": ["low", "medium", "high"]},
{"name": "sort", "in": "query", "type": "string", "enum": ["created_at", "updated_at", "title"]},
{"name": "page", "in": "query", "type": "integer"},
{"name": "limit", "in": "query", "type": "integer"},
],
},
{
"method": "POST",
"path": "/tasks",
"summary": "Create a new task. Requires 'title' field. Optional: description, status, priority, assignee_email.",
"request_body": {
"required": ["title"],
"properties": {
"title": {"type": "string"},
"description": {"type": "string"},
"status": {"type": "string", "enum": ["pending", "in_progress", "done"]},
"priority": {"type": "string", "enum": ["low", "medium", "high"]},
"assignee_email": {"type": "string", "format": "email"},
},
},
},
{
"method": "GET",
"path": "/tasks/{id}",
"summary": "Get a specific task by ID.",
"parameters": [{"name": "id", "in": "path", "type": "integer", "required": True}],
},
{
"method": "PUT",
"path": "/tasks/{id}",
"summary": "Update a task. All fields optional.",
"parameters": [{"name": "id", "in": "path", "type": "integer", "required": True}],
"request_body": {
"properties": {
"title": {"type": "string"},
"description": {"type": "string"},
"status": {"type": "string"},
"priority": {"type": "string"},
"assignee_email": {"type": "string", "format": "email"},
},
},
},
{
"method": "DELETE",
"path": "/tasks/{id}",
"summary": "Delete a task by ID.",
"parameters": [{"name": "id", "in": "path", "type": "integer", "required": True}],
},
{
"method": "GET",
"path": "/users",
"summary": "List all users.",
},
{
"method": "POST",
"path": "/users",
"summary": "Create a new user. Requires username, email, password.",
"request_body": {
"required": ["username", "email", "password"],
"properties": {
"username": {"type": "string"},
"email": {"type": "string", "format": "email"},
"password": {"type": "string"},
"role": {"type": "string", "enum": ["user", "admin"]},
},
},
},
{
"method": "GET",
"path": "/users/{id}",
"summary": "Get a specific user by ID.",
"parameters": [{"name": "id", "in": "path", "type": "integer", "required": True}],
},
{
"method": "POST",
"path": "/auth/login",
"summary": "Login and receive an auth token. Pre-seeded users: alice, bob, charlie (password: any string).",
"request_body": {
"required": ["username", "password"],
"properties": {
"username": {"type": "string"},
"password": {"type": "string"},
},
},
},
]
class APITestEnvironment(Environment):
"""OpenEnv environment for API integration testing.
The agent tests a deliberately buggy REST API by sending HTTP requests
and analyzing responses. It earns rewards for coverage, finding bugs,
and exploring edge cases.
"""
SUPPORTS_CONCURRENT_SESSIONS = False
def __init__(self, **kwargs):
super().__init__(**kwargs)
self._db: Optional[Database] = None
self._api: Optional[TestClient] = None
self._bug_detector: Optional[BugDetector] = None
self._reward_computer: Optional[RewardComputer] = None
self._task: Optional[dict] = None
self._found_bugs: set[str] = set()
self._steps_taken: int = 0
self._cumulative_reward: float = 0.0
self._action_history: list[dict] = []
self._auth_tokens: dict[str, str] = {}
self._episode_id: str = ""
def reset(self, seed=None, episode_id=None, **kwargs) -> APITestObservation:
"""Reset the environment for a new episode.
Args:
seed: Random seed for domain randomization. When provided, the
database is populated with different users, tasks, and data
so each training episode is unique. None = fixed default data.
episode_id: Optional episode identifier for tracking.
kwargs:
task_id: str - one of "basic_validation", "edge_cases", "security_workflows"
"""
task_id = kwargs.get("task_id", "basic_validation")
if task_id not in TASKS:
task_id = "basic_validation"
self._task = TASKS[task_id]
self._seed = seed
self._episode_id = episode_id or f"ep_{int(time.time())}"
# Reset database with seed for domain randomization
# seed=None → fixed data (manual testing / Gradio)
# seed=int → randomized data (GRPO training)
self._db = Database(seed=seed)
buggy_app = create_buggy_api(self._db)
self._api = TestClient(buggy_app, raise_server_exceptions=False)
# Build dynamic task description that includes actual usernames
user_names = self._db.user_names
user_list = ", ".join(user_names)
dynamic_description = (
f"{self._task['description']} "
f"Users in the system: {user_list} (use any password to login)."
)
# Reset tracking
self._bug_detector = BugDetector(task_id)
self._reward_computer = RewardComputer()
self._found_bugs = set()
self._steps_taken = 0
self._cumulative_reward = 0.0
self._action_history = []
self._auth_tokens = {}
logger.info(f"Reset environment: task={task_id}, seed={seed}, episode={self._episode_id}")
return APITestObservation(
available_endpoints=API_SPEC,
status_code=0,
response_body=None,
response_headers={},
response_time_ms=0,
feedback=(
f"Environment reset. Task: {dynamic_description} "
f"You have {self._task['max_steps']} steps. Start testing the API!"
),
bugs_found_so_far=0,
coverage_summary=self._reward_computer.coverage.summary(),
known_resource_ids=self._reward_computer.created_ids,
auth_tokens=self._auth_tokens,
task_id=task_id,
task_description=dynamic_description,
steps_taken=0,
max_steps=self._task["max_steps"],
done=False,
reward=0.0,
)
def step(self, action: APITestAction, timeout_s=None, **kwargs) -> APITestObservation:
"""Execute an API test action and return observation + reward."""
self._steps_taken += 1
# Forward request to buggy API
method = action.method.value if hasattr(action.method, "value") else str(action.method)
endpoint = action.endpoint
headers = dict(action.headers) if action.headers else {}
query_params = dict(action.query_params) if action.query_params else {}
body = action.body
# Make the request
start_time = time.time()
try:
response = self._api.request(
method=method.upper(),
url=endpoint,
headers=headers,
params=query_params if query_params else None,
json=body,
)
elapsed_ms = (time.time() - start_time) * 1000
response_status = response.status_code
try:
response_body = response.json()
except Exception:
response_body = response.text
response_headers = dict(response.headers)
except Exception as e:
elapsed_ms = (time.time() - start_time) * 1000
response_status = 0
response_body = {"error": str(e)}
response_headers = {}
# Track auth tokens from login responses
if (
endpoint == "/auth/login"
and response_status == 200
and isinstance(response_body, dict)
and "token" in response_body
):
username = body.get("username", "unknown") if body else "unknown"
self._auth_tokens[username] = response_body["token"]
# Check for bug detection
detection = self._bug_detector.check(
method=method,
endpoint=endpoint,
headers=headers,
query_params=query_params,
body=body,
expected_status=action.expected_status,
response_status=response_status,
response_body=response_body,
action_history=self._action_history,
found_bugs=self._found_bugs,
)
bug_severity = None
bug_id = None
if detection:
bug_severity = detection.bug.severity
bug_id = detection.bug.id
self._found_bugs.add(bug_id)
# Compute reward
reward_breakdown = self._reward_computer.compute(
method=method,
endpoint=endpoint,
headers=headers,
query_params=query_params,
body=body,
expected_status=action.expected_status,
response_status=response_status,
response_body=response_body,
bug_found=bug_severity,
bug_id=bug_id,
)
self._cumulative_reward += reward_breakdown.total
# Record action in history
self._action_history.append({
"method": method,
"endpoint": endpoint,
"headers": headers,
"query_params": query_params,
"body": body,
"response_status": response_status,
"response_body": response_body,
})
# Generate feedback
feedback_parts = [f"{method} {endpoint} -> {response_status}"]
if detection:
feedback_parts.append(f"BUG FOUND ({detection.bug.severity})! {detection.evidence}")
if reward_breakdown.coverage > 0:
feedback_parts.append(f"Coverage +{reward_breakdown.coverage:.2f}")
if reward_breakdown.penalty < 0:
feedback_parts.append("Repeated request penalty")
done = self._steps_taken >= self._task["max_steps"]
# Compute final grade if done
if done:
grade = TaskGrader.grade(
task_id=self._task["id"],
bugs_found=self._found_bugs,
coverage_pct=self._reward_computer.coverage.summary()["coverage_pct"],
endpoints_tested=len(self._reward_computer.coverage.endpoints_hit),
total_endpoints=self._reward_computer.coverage.total_endpoints,
method_endpoint_pairs=len(self._reward_computer.coverage.method_endpoint_pairs),
status_codes_seen=self._reward_computer.coverage.status_codes_seen,
action_history=self._action_history,
created_resources=self._reward_computer.created_ids,
)
# Generate bug bounty report
report = generate_bug_report(list(self._found_bugs), self._action_history)
feedback_parts.append(
f"\n=== EPISODE COMPLETE ===\n"
f"Final Score: {grade.score:.4f}\n"
f"Bugs Found: {len(self._found_bugs)}/{self._task['total_bugs']}\n"
f"Grade Breakdown: {json.dumps(grade.breakdown, indent=2)}\n"
f"Feedback: {grade.feedback}\n\n"
f"{report}"
)
# Add grade as bonus on top of step reward (not replacement)
final_reward = reward_breakdown.total + grade.score
else:
final_reward = reward_breakdown.total
return APITestObservation(
available_endpoints=API_SPEC,
status_code=response_status,
response_body=response_body,
response_headers={k: v for k, v in list(response_headers.items())[:20]},
response_time_ms=round(elapsed_ms, 2),
feedback=" | ".join(feedback_parts),
bugs_found_so_far=len(self._found_bugs),
coverage_summary=self._reward_computer.coverage.summary(),
known_resource_ids=self._reward_computer.created_ids,
auth_tokens=self._auth_tokens,
task_id=self._task["id"],
task_description=self._task["description"],
steps_taken=self._steps_taken,
max_steps=self._task["max_steps"],
done=done,
reward=final_reward,
metadata={"reward_breakdown": reward_breakdown.as_dict()},
)
@property
def state(self) -> APITestState:
"""Return current episode state."""
if not self._task:
return APITestState()
coverage = self._reward_computer.coverage.summary() if self._reward_computer else {}
return APITestState(
episode_id=self._episode_id,
step_count=self._steps_taken,
task_id=self._task["id"],
task_description=self._task["description"],
difficulty=self._task["difficulty"],
steps_taken=self._steps_taken,
max_steps=self._task["max_steps"],
bugs_found=len(self._found_bugs),
total_bugs=self._task["total_bugs"],
bugs_found_ids=list(self._found_bugs),
coverage_pct=coverage.get("coverage_pct", 0.0),
endpoints_tested=coverage.get("endpoints_tested", 0),
total_endpoints=coverage.get("total_endpoints", 0),
current_score=0.0,
cumulative_reward=round(self._cumulative_reward, 4),
)
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