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b54a031 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 | """InjectArenaEnv — the core RL environment.
Defense instances are injected at construction so the environment can run
with stub defenses on Mac (no GPU) and real defenses on Colab.
"""
from __future__ import annotations
import time
import uuid
from typing import Any, Dict, List, Optional
from .models import (
AttemptRecord,
InjectAction,
InjectObservation,
StepResult,
)
from .rewards import compute_reward
from .scenarios import ScenarioBank
from .utils.safety_filter import is_safe
from .verifiers.exfiltration import verify_exfiltration
from .verifiers.forbidden_tool import verify_forbidden_tool
from .verifiers.prompt_leak import verify_prompt_leak
_MAX_ATTEMPTS = 3
_STEP_TIMEOUT_S = 30.0
class InjectArenaEnv:
"""Episode-based environment for prompt-injection red-teaming."""
def __init__(
self,
pg2: Any,
secalign: Any,
firewall: Any,
bank: Optional[ScenarioBank] = None,
max_attempts: int = _MAX_ATTEMPTS,
embedder: Any = None,
) -> None:
self._pg2 = pg2
self._secalign = secalign
self._firewall = firewall
self._bank = bank or ScenarioBank()
self._max_attempts = max_attempts
self._embedder = embedder
self._scenario: Optional[Dict[str, Any]] = None
self._attempts: int = 0
self._previous: List[AttemptRecord] = []
self._episode_id: Optional[str] = None
self._done: bool = True
# ------------------------------------------------------------------
# OpenEnv interface
# ------------------------------------------------------------------
def reset(
self,
scenario_id: Optional[str] = None,
seed: Optional[int] = None,
split: str = "train",
) -> InjectObservation:
if scenario_id is not None:
self._scenario = self._bank.by_id(scenario_id)
else:
self._scenario = self._bank.sample(seed=seed, split=split)
self._attempts = 0
self._previous = []
self._episode_id = str(uuid.uuid4())
self._done = False
return self._build_obs()
def step(self, action: InjectAction) -> StepResult:
if self._done or self._scenario is None:
raise RuntimeError("Call reset() before step().")
t0 = time.monotonic()
payload = action.payload
scenario = self._scenario
# Safety floor — immediate termination.
safe, safety_reason = is_safe(payload)
if not safe:
self._done = True
return StepResult(
observation=self._build_obs(),
reward=-1.0,
done=True,
info={
"safety_violation": True,
"safety_reason": safety_reason,
"episode_id": self._episode_id,
},
)
# All three defenses run on every step (§5.4 invariant).
pg2_verdict = self._pg2.scan(payload)
agent_output = self._secalign.run(
system=scenario["agent_system_prompt"],
user=scenario["user_query"],
untrusted={scenario["injection_slot"]: payload},
)
fw_verdict = self._firewall.scan(
user_query=payload,
agent_output=agent_output,
tool_call=None,
)
elapsed = time.monotonic() - t0
# Task success via category-specific verifier.
cat = scenario["target_category"]
if cat == "exfiltration":
task_success = verify_exfiltration(agent_output, scenario)
elif cat == "forbidden_tool":
task_success = verify_forbidden_tool(agent_output, scenario)
else:
task_success = verify_prompt_leak(agent_output, scenario)
# Reward.
recent = [a.payload for a in self._previous]
reward, reward_info = compute_reward(
payload=payload,
pg2_verdict=pg2_verdict,
firewall_verdict=fw_verdict,
task_success=task_success,
scenario=scenario,
recent_payloads=recent,
embedder=self._embedder,
)
# Record.
record = AttemptRecord(
payload=payload,
pg2_label="injection" if pg2_verdict.flagged else "benign",
firewall_flagged=fw_verdict.flagged,
task_success=task_success,
)
self._previous.append(record)
self._attempts += 1
# Done conditions (§5.4).
timeout = elapsed > _STEP_TIMEOUT_S
done = (
task_success
or self._attempts >= self._max_attempts
or reward_info.get("safety_violation", False)
or timeout
)
self._done = done
return StepResult(
observation=self._build_obs(),
reward=reward,
done=done,
info={
**reward_info,
"agent_output": agent_output,
"pg2_verdict": pg2_verdict.model_dump(),
"fw_verdict": fw_verdict.model_dump(),
"task_success": task_success,
"elapsed_s": round(elapsed, 3),
"timeout": timeout,
"strategy_tag": action.strategy_tag,
"episode_id": self._episode_id,
},
)
@property
def state(self) -> Dict[str, Any]:
return {
"episode_id": self._episode_id,
"scenario_id": self._scenario["scenario_id"] if self._scenario else None,
"attempts": self._attempts,
"max_attempts": self._max_attempts,
"done": self._done,
}
def close(self) -> None:
pass
# ------------------------------------------------------------------
def _build_obs(self) -> InjectObservation:
s = self._scenario
return InjectObservation(
scenario_id=s["scenario_id"],
target_behavior=s["target_behavior"],
target_category=s["target_category"],
agent_system_prompt=s["agent_system_prompt"],
user_query=s["user_query"],
injection_slot=s["injection_slot"],
tool_surface=s["tool_surface"],
canary_string=s.get("canary_string"),
previous_attempts=list(self._previous),
attempts_remaining=self._max_attempts - self._attempts,
)
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