greydgl--pentestgpt
ab5fbb4d90
* first refactor
* feat: dockerized tool with persistent Claude+Codex login + multi-model benchmark
Run the autonomous CTF/pentest tool in Docker with a one-time, persistent login for
BOTH Claude Code and Codex, and add a multi-model benchmark harness.
Backend (multi-model):
- Add `--backend {claude,codex}` to the CTF pipeline. CodexBackend (pentestgpt/core/
backend.py) wraps unified_agent's Codex backend and translates its events into
AgentMessages, so the same pipeline runs on Claude (opus/sonnet) or Codex
(gpt-5.5/gpt-5.4-mini). Wired through config.backend, pipeline stage construction,
and the CLI (+ PENTESTGPT_CODEX_EFFORT; greppable [CODEX_USAGE] under PENTESTGPT_BENCH=1).
Docker tool (tool-only image; the benchmark stays OUTSIDE the image):
- Extend Dockerfile: Codex CLI (@openai/codex) + openai_codex SDK + unified_agent/
pentestgpt_agent/pentestgpt_legacy packages + gobuster/dirb + socat. Add .dockerignore
(keeps creds/benchmark/workspace out of the build context).
- Persistent dual login (the hard part) — asymmetric by token model:
* Claude: `setup-token` -> token stored in the pentestgpt-claude volume; entrypoint
exports CLAUDE_CODE_OAUTH_TOKEN (setup-token does not write .credentials.json; macOS
host creds live in the Keychain and can't be copied).
* Codex: the container does its OWN `codex login` (NOT seeding -- ChatGPT refresh tokens
are single-use, so a shared/copied login 401s on first refresh). The 127.0.0.1:1455
OAuth callback is forwarded into the container via a socat hop (-p 1455:8455).
* scripts/docker-login.sh is idempotent: checks logins live, logs in only the missing one(s).
- docker-compose codex-config volume (+ pinned names); entrypoint token-export + non-blocking
preflight; scripts/docker-auth-status.sh; Make targets (docker-build/login/auth-status/
run/shell/down/nuke).
- Verified end-to-end: one `make docker-login` -> a fresh container reports claude+codex
logged in with live round-trips; the CTF pipeline (Codex) captured a flag against an
isolated fixture and the pentest pipeline ran cleanly; persists across recreation, no re-login.
Benchmark (multi-model, host-side):
- benchmark/pilot/ harness (run_pilot.py + report.py): builds each xbow challenge, discovers
the loopback port, runs the pipeline across the 4 model combos, judges by the baked
FLAG{sha256(UPPER-dir)}, and renders REPORT.md (infra failures excluded from solve rates).
Includes the partial pilot's results (results.jsonl + REPORT.md).
Docs: docs/docker-dev-plan.md (full plan + implementation status); CLAUDE.md and README
docker quickstart; benchmark/pilot/README.md; design-doc roadmap (docs/redesign).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* fix: fail controller on backend error messages
* fix: allow listing sessions without target
* docs: add docker xbow benchmark report
* fix: infer concrete backend constructor type
* docs: refresh docker benchmark documentation
* feat(benchmark): add pure single-agent baseline + pipeline comparison
Add a "pure single agent" benchmark variant -- one bare `claude -p` /
`codex exec` call per target (no pipeline) -- to quantify what the 3-stage
PentestGPT pipeline buys over an un-orchestrated agent on the xbow targets.
- pentestgpt/prompts/stages.py: ctf_single_agent_{system,task}_prompt -- the
pipeline's shared fragments collapsed into ONE turn, so prompt content is
held constant and the only variable is the multi-stage decomposition.
- benchmark/pilot/run_docker_bench.py: docker-network runner
(--variant single|pipeline). Brings the target up, discovers the container's
internal IP+network (skips DB side-cars/ports), docker-runs the tool image on
that network, and scores the ground-truth flag against the agent's *assistant
text* only (parity with the pipeline's raw streaming). Reads stdout in chunks
to handle >64KB JSON lines. Resumable; --dry-run supported.
- benchmark/pilot/report_comparison.py -> DOCKER_COMPARISON.md: head-to-head
pipeline-vs-single per model on the common non-infra set.
- tests/unit/test_single_agent_prompt.py: prompt-builder coverage.
- docs: README, CLAUDE.md, benchmark README, DOCKER_REPORT updated.
Recorded result (10 medium/hard targets x 4 models, container-to-container,
same baseline image digest 0c4c0f3e..., commit dca0019 image):
Model Pipeline Single
Claude Opus 5/10 7/10 (single +2)
Claude Sonnet 6/10 4/10 (pipeline +2)
Codex gpt-5.5 7/10 7/10 (tie)
Codex gpt-5.4-mini 3/10 4/10 (single +1)
TOTAL 21/40 22/40
Single agent matches the pipeline on solve rate (55% vs 52%) while using
~40% fewer Codex tokens (13.0M vs 21.8M) and solving faster. The pipeline
only clearly helps Claude Sonnet (which times out solo); Opus is better solo.
Full per-challenge grid in DOCKER_COMPARISON.md; raw records in
docker_single_results.jsonl.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* feat(benchmark): add pentestgpt_agent docker harness
* bench: refresh pentestgpt_agent smoke result
* fix(benchmark): make repeat rows variant-aware
* fix(agent): fall back for semantic executor labels
* fix(agent): tolerate executor prose evidence
* fix(benchmark): score accepted framework findings
* bench: append partial framework repeat results
* bench: complete framework repeat sweep
* bench: expose framework executor concurrency
* bench: add extended parallel framework sweep
* checkpoint: preserve working agent and benchmark state
* feat: harden durable agent loop and xbow qualification
* fix: reserve an exploit result turn
* docs: record clean xbow qualification
* build: consume unified-agent from the git wrapper repo
Repoint pentestgpt_agent_new's unified-agent dependency from the local
editable path (../../UnifiedAgentPoC, now renamed and gone) to the pinned
git source PentestGPT-Project/UnifedAgentWrapper@d05d21f. Regenerate uv.lock
and update test_dependency.py to assert the external package is installed
from that VCS URL (not the repo-root vendored copy) at version 0.2.0.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
* refactor: make pentestgpt_agent_new the sole framework
Remove the retired ledger-based pentestgpt_agent package (instructor/executor/
judge) and its orphaned unit + smoke tests. The nested pentestgpt_agent_new
project (Supervisor/Executor over a durable SQLite loop, consuming unified-agent
from the git wrapper) is now the single maintained framework.
Repoint the top-level tooling to it:
- pyproject: drop the pentestgpt-agent console script and pentestgpt_agent from
the wheel packages.
- Makefile: lint/format target parent code only; typecheck/check/ci now run the
nested framework's own gate (ruff, format, mypy, pytest) via test-agent-new /
check-agent-new, so `make check` finally covers it; `make run` delegates to the
pentestgpt-agent-new CLI.
- Dockerfile: stop copying the removed package (kept the build working); note the
framework is not baked into the image yet.
- docker container-health test: import the substrate packages that actually ship.
- CLAUDE.md / AGENT.md: describe the new framework, the git-sourced wrapper, and
the deprioritized benchmark/Docker rewire.
The XBOW `--variant framework` path and docker-bench Makefile targets still point
at the old in-image framework and are left as a pending rewire (benchmarks
deprioritized); the naive `--variant single` path is unaffected.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
* refactor: rename pentestgpt_agent_new -> pentestgpt_agent
The framework reclaims the clean name now that the old ledger-based package is
gone. Rename the nested project folder, its src package, the distribution
(pentestgpt-agent-new -> pentestgpt-agent) and CLI, and every import/reference in
the package, the umbrella Makefile, the Dockerfile, the docker health test, and
CLAUDE.md / AGENT.md. Regenerate uv.lock. The audit CLI stays pentestgpt-agent-audit;
the git-sourced unified-agent dependency is unchanged. `make check` is green
(108 nested tests). The two historical *_REPORT.md files keep the old name as
dated records.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
* chore: extract benchmark harness to sibling xbow-benchmark repo
Move PentestGPT/benchmark/ out to ../xbow-benchmark (its own repo) to keep this
project clean. The harness was decoupled from the framework code (it scores
container output, never imports pentestgpt_agent/unified_agent), so only
operational ties remain and they now live in the sibling repo.
- Remove benchmark/ and the 4 harness unit tests (relocated + repointed there).
- Strip the docker-bench-*/bench-* targets and their config vars from the
Makefile; keep the tool-image lifecycle (docker-build/login/run/...) and add a
help pointer to `make -C ../xbow-benchmark help`.
The sibling repo mounts this checkout read-only (--source-root ../PentestGPT) and
runs the pentestgpt:latest image built here.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
* feat: harden autonomous framework and runtime integration
---------
Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
648 行
21 KiB
Python
648 行
21 KiB
Python
import json
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import sqlite3
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from collections.abc import AsyncIterator
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from dataclasses import replace
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from pathlib import Path
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import pytest
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from unified_agent import (
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AgentEvent,
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CommandRun,
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RunOptions,
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SandboxPolicy,
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TurnCompleted,
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UnifiedAgent,
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)
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from pentestgpt_agent import trial
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from pentestgpt_agent.agents import (
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EXECUTOR_INSTRUCTIONS,
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SUPERVISOR_INSTRUCTIONS,
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Executor,
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Supervisor,
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)
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from pentestgpt_agent.audit import _is_hidden_provider_memory_action, audit_run
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from pentestgpt_agent.memory import MemoryKernel, RunSpec
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from pentestgpt_agent.trace import EpisodeRunner, TraceStore
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from pentestgpt_agent.trial import TrialConfig, run_trial
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class TrialSupervisorBackend:
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name = "scripted"
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def __init__(self) -> None:
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self.calls = 0
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async def stream(self, prompt: str, opts: RunOptions) -> AsyncIterator[AgentEvent]:
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if self.calls == 0:
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output = {
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"base_revision": 0,
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"new_tasks": [
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{
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"id": "capture-flag",
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"kind": "verify",
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"target": "http://target.test",
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"objective": "Capture the benchmark flag.",
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"done_when": "The exact flag is recorded.",
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"basis_ids": [],
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"depends_on": [],
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}
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],
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"next_task_id": "capture-flag",
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"finish": False,
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"finish_basis_ids": [],
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"summary": "Capture the flag directly.",
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}
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else:
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state = json.loads(prompt.split("\n\n", 1)[1])
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output = {
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"base_revision": 2,
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"new_tasks": [],
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"next_task_id": None,
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"finish": True,
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"finish_basis_ids": [state["observations"][-1]["id"]],
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"summary": "The exact benchmark flag was captured.",
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}
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self.calls += 1
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yield CommandRun(command="inspect-planning-workspace", exit_code=0, output="ok")
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yield TurnCompleted(success=True, structured_output=output)
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class TrialExecutorBackend:
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name = "scripted"
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async def stream(self, prompt: str, opts: RunOptions) -> AsyncIterator[AgentEvent]:
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yield CommandRun(command="read-flag", exit_code=0, output="FLAG{trial-oracle}")
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yield TurnCompleted(
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success=True,
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structured_output={
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"task_id": "capture-flag",
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"outcome": "done",
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"summary": "Captured the exact flag.",
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"evidence_excerpt": "FLAG{trial-oracle}",
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},
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)
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class FailureSupervisorBackend:
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name = "scripted"
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async def stream(self, prompt: str, opts: RunOptions) -> AsyncIterator[AgentEvent]:
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yield TurnCompleted(
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success=True,
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structured_output={
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"base_revision": 0,
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"new_tasks": [
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{
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"id": "test-target",
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"kind": "test",
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"target": "http://target.test",
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"objective": "Test the target.",
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"done_when": "The behavior is recorded.",
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"basis_ids": [],
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"depends_on": [],
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}
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],
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"next_task_id": "test-target",
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"finish": False,
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"finish_basis_ids": [],
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"summary": "Test the target.",
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},
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)
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class FailureExecutorBackend:
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name = "scripted"
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async def stream(self, prompt: str, opts: RunOptions) -> AsyncIterator[AgentEvent]:
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yield CommandRun(command="curl http://target.test", exit_code=0, output="partial")
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yield TurnCompleted(
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success=False,
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stop_reason="error_max_turns",
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error="Reached maximum number of turns (2)",
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)
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raise RuntimeError("Command failed with exit code 1")
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class InvalidSupervisorBackend:
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name = "scripted"
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async def stream(self, prompt: str, opts: RunOptions) -> AsyncIterator[AgentEvent]:
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yield TurnCompleted(success=True, structured_output={"invalid": "decision"})
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class MustNotRunBackend:
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name = "scripted"
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async def stream(self, prompt: str, opts: RunOptions) -> AsyncIterator[AgentEvent]:
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raise AssertionError("a completed resumed trial must not invoke a provider")
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yield # pragma: no cover
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def test_claude_provider_memory_is_disabled_for_fresh_episodes() -> None:
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assert trial._provider_environment("claude") == {
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"CLAUDE_CODE_DISABLE_AUTO_MEMORY": "1",
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"CLAUDE_CODE_DISABLE_NONESSENTIAL_TRAFFIC": "1",
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"DISABLE_AUTOUPDATER": "1",
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}
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assert trial._provider_environment("codex") == {}
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def test_audit_recognizes_provider_side_memory_writes() -> None:
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assert _is_hidden_provider_memory_action(
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{
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"type": "tool_call",
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"name": "Write",
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"input": {"file_path": "/home/pentester/.claude/projects/-trial/memory/MEMORY.md"},
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}
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)
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assert not _is_hidden_provider_memory_action(
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{
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"type": "tool_call",
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"name": "Write",
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"input": {"file_path": "/trial/workspaces/run/notes.md"},
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}
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)
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def test_audit_emits_an_incomplete_record_for_an_empty_episode_directory(
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tmp_path: Path,
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) -> None:
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run_dir = tmp_path / "runs" / "incomplete-trial"
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MemoryKernel(run_dir / "state.sqlite3").create_run(
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RunSpec(
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run_id="incomplete-trial",
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goal="Assess the target.",
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allowed_targets=("http://target.test",),
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)
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)
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(run_dir / "traces" / "executor-incomplete").mkdir(parents=True)
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audit = audit_run(run_dir, expected_flag="FLAG{not-present}")
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assert audit["passed"] is False
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assert audit["checks"]["all_episodes_complete"] is False
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assert audit["episodes"] == [
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{
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"episode_id": "executor-incomplete",
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"run_id": None,
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"input_episode_id": None,
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"role": None,
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"state_revision": None,
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"task_id": None,
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"attempt_id": None,
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"opened_at": None,
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"closed_at": None,
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"success": False,
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"duration_ms": None,
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"cost_usd": 0.0,
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"usage": {},
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"structured_output": None,
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"event_counts": {},
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"actions": [],
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"events": [],
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"truncated_tail": False,
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"complete": False,
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"integrity_errors": [
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"missing input.json",
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"missing output.json",
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"missing events.jsonl",
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],
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}
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]
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def test_audit_accounts_for_an_initialization_crash_settled_by_run_transition(
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tmp_path: Path,
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) -> None:
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run_dir = tmp_path / "runs" / "settled-supervisor-crash"
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memory = MemoryKernel(run_dir / "state.sqlite3")
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memory.create_run(
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RunSpec(
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run_id="settled-supervisor-crash",
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goal="Assess the target.",
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allowed_targets=("http://target.test",),
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)
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)
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(run_dir / "traces" / "supervisor-r0").mkdir(parents=True)
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memory.commit_run_failure(
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"settled-supervisor-crash",
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0,
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failure_kind="supervisor_contract",
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failure_message="initialization was interrupted twice",
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)
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audit = audit_run(run_dir, expected_flag="FLAG{not-present}")
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assert audit["checks"]["all_episodes_complete"] is True
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assert audit["checks"]["transition_timeline_complete"] is True
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assert audit["passed"] is False
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def test_audit_emits_partial_events_and_integrity_errors_for_malformed_trace_files(
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tmp_path: Path,
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) -> None:
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run_dir = tmp_path / "runs" / "malformed-trial"
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MemoryKernel(run_dir / "state.sqlite3").create_run(
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RunSpec(
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run_id="malformed-trial",
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goal="Assess the target.",
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allowed_targets=("http://target.test",),
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)
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)
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episode_dir = run_dir / "traces" / "executor-malformed"
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episode_dir.mkdir(parents=True)
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(episode_dir / "input.json").write_text("{", encoding="utf-8")
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(episode_dir / "events.jsonl").write_text(
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'{"sequence":1,"type":"assistant_text","text":"partial"}\n{',
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encoding="utf-8",
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)
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(episode_dir / "output.json").write_text("[", encoding="utf-8")
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audit = audit_run(run_dir, expected_flag="FLAG{not-present}")
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assert audit["passed"] is False
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episode = audit["episodes"][0]
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assert episode["complete"] is False
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assert episode["truncated_tail"] is True
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assert episode["events"] == [{"sequence": 1, "type": "assistant_text", "text": "partial"}]
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assert episode["integrity_errors"] == [
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"malformed input.json",
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"malformed output.json",
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"malformed events.jsonl at line 2",
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]
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@pytest.mark.asyncio
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async def test_trial_writes_a_run_that_the_artifact_auditor_can_verify(
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tmp_path: Path,
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) -> None:
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runs_root = tmp_path / "runs"
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traces = TraceStore(runs_root)
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supervisor = Supervisor(
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EpisodeRunner(
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UnifiedAgent(
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TrialSupervisorBackend(),
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workspace=tmp_path / "supervisor",
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sandbox=SandboxPolicy.FULL_ACCESS,
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instructions=SUPERVISOR_INSTRUCTIONS,
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),
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traces,
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)
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)
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executor = Executor(
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EpisodeRunner(
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UnifiedAgent(
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TrialExecutorBackend(),
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workspace=tmp_path / "executor",
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sandbox=SandboxPolicy.FULL_ACCESS,
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instructions=EXECUTOR_INSTRUCTIONS,
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),
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traces,
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)
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)
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config = TrialConfig(
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run_id="trial-run",
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goal="Capture the benchmark flag.",
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targets=("http://target.test",),
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backend="claude",
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model="claude-opus-4-8",
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runs_root=runs_root,
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workspace_root=tmp_path / "agents",
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effort="xhigh",
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max_decisions=4,
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supervisor_max_turns=2,
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executor_max_turns=2,
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)
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summary = await run_trial(config, supervisor=supervisor, executor=executor)
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audit = audit_run(runs_root / "trial-run", expected_flag="FLAG{trial-oracle}")
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assert summary["status"] == "completed"
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assert summary["model"] == "claude-opus-4-8"
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assert summary["effort"] == "xhigh"
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assert summary["runtime_policy_revision"] == 2
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assert [attempt["status"] for attempt in summary["attempts"]] == ["done"]
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assert [transition["kind"] for transition in summary["transitions"]] == [
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"run_created",
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"plan_committed",
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"attempt_committed",
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"plan_committed",
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]
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assert (runs_root / "trial-run" / "summary.json").exists()
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assert audit["passed"] is True
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assert audit["checks"] == {
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"run_completed": True,
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"oracle_in_canonical_observation": True,
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"no_active_tasks": True,
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"no_active_attempts": True,
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"all_episodes_complete": True,
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"all_observations_grounded": True,
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|
"all_observations_are_direct_quotes": True,
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"all_observation_identities_match": True,
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"all_basis_ids_exist": True,
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"all_basis_producers_are_dependencies": True,
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"all_exploit_bases_current": True,
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"completion_basis_valid": True,
|
|
"transition_timeline_complete": True,
|
|
"all_failed_episodes_settled": True,
|
|
}
|
|
assert audit["schema_version"] == 2
|
|
assert audit["totals"]["supervisor_actions"] == 2
|
|
assert len(audit["episodes"]) == 3
|
|
trial_identity = json.loads(
|
|
(runs_root / "trial-run" / "trial-config.json").read_text(encoding="utf-8")
|
|
)
|
|
assert trial_identity["schema_version"] == 2
|
|
assert trial_identity["supervisor_sandbox"] == "full_access"
|
|
assert trial_identity["executor_sandbox"] == "full_access"
|
|
|
|
executor_episode = next(
|
|
episode
|
|
for episode in (runs_root / "trial-run" / "traces").iterdir()
|
|
if json.loads((episode / "input.json").read_text(encoding="utf-8"))["role"] == "executor"
|
|
)
|
|
events_path = executor_episode / "events.jsonl"
|
|
events = [json.loads(line) for line in events_path.read_text(encoding="utf-8").splitlines()]
|
|
command_receipt = next(event for event in events if event["type"] == "command_run")
|
|
command_receipt["exit_code"] = 255
|
|
events_path.write_text(
|
|
"".join(json.dumps(event) + "\n" for event in events),
|
|
encoding="utf-8",
|
|
)
|
|
nonzero_exit_audit = audit_run(
|
|
runs_root / "trial-run",
|
|
expected_flag="FLAG{trial-oracle}",
|
|
)
|
|
assert nonzero_exit_audit["checks"]["all_observations_grounded"] is True
|
|
assert nonzero_exit_audit["checks"]["all_observations_are_direct_quotes"] is True
|
|
|
|
database = runs_root / "trial-run" / "state.sqlite3"
|
|
with sqlite3.connect(database) as connection:
|
|
connection.execute(
|
|
"UPDATE observations SET statement = ?",
|
|
("FLAG{trial-oracle} with uncaptured suffix",),
|
|
)
|
|
tampered = audit_run(runs_root / "trial-run", expected_flag="FLAG{trial-oracle}")
|
|
assert tampered["checks"]["oracle_in_canonical_observation"] is True
|
|
assert tampered["checks"]["all_observations_are_direct_quotes"] is False
|
|
assert tampered["passed"] is False
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_trial_interface_can_explicitly_resume_a_persisted_run(tmp_path: Path) -> None:
|
|
runs_root = tmp_path / "runs"
|
|
traces = TraceStore(runs_root)
|
|
initial_config = TrialConfig(
|
|
run_id="resumable-trial",
|
|
goal="Capture the benchmark flag.",
|
|
targets=("http://target.test",),
|
|
backend="claude",
|
|
model="claude-opus-4-8",
|
|
runs_root=runs_root,
|
|
workspace_root=tmp_path / "agents",
|
|
max_decisions=4,
|
|
supervisor_max_turns=2,
|
|
executor_max_turns=2,
|
|
)
|
|
initial = await run_trial(
|
|
initial_config,
|
|
supervisor=Supervisor(
|
|
EpisodeRunner(
|
|
UnifiedAgent(
|
|
TrialSupervisorBackend(),
|
|
workspace=tmp_path / "supervisor",
|
|
sandbox=SandboxPolicy.FULL_ACCESS,
|
|
instructions=SUPERVISOR_INSTRUCTIONS,
|
|
),
|
|
traces,
|
|
)
|
|
),
|
|
executor=Executor(
|
|
EpisodeRunner(
|
|
UnifiedAgent(
|
|
TrialExecutorBackend(),
|
|
workspace=tmp_path / "executor",
|
|
sandbox=SandboxPolicy.FULL_ACCESS,
|
|
instructions=EXECUTOR_INSTRUCTIONS,
|
|
),
|
|
traces,
|
|
)
|
|
),
|
|
)
|
|
assert initial["status"] == "completed"
|
|
|
|
resume_config = replace(initial_config, resume=True)
|
|
resumed = await run_trial(
|
|
resume_config,
|
|
supervisor=Supervisor(
|
|
EpisodeRunner(
|
|
UnifiedAgent(
|
|
MustNotRunBackend(),
|
|
workspace=tmp_path / "supervisor-resume",
|
|
sandbox=SandboxPolicy.FULL_ACCESS,
|
|
instructions=SUPERVISOR_INSTRUCTIONS,
|
|
),
|
|
traces,
|
|
)
|
|
),
|
|
executor=Executor(
|
|
EpisodeRunner(
|
|
UnifiedAgent(
|
|
MustNotRunBackend(),
|
|
workspace=tmp_path / "executor-resume",
|
|
sandbox=SandboxPolicy.FULL_ACCESS,
|
|
instructions=EXECUTOR_INSTRUCTIONS,
|
|
),
|
|
traces,
|
|
)
|
|
),
|
|
)
|
|
|
|
assert resumed["status"] == "completed"
|
|
assert resumed["revision"] == initial["revision"]
|
|
assert resumed["episodes"] == initial["episodes"]
|
|
|
|
with pytest.raises(ValueError, match="does not match requested config"):
|
|
await run_trial(replace(resume_config, model="different-model"))
|
|
|
|
with pytest.raises(ValueError, match="does not match requested config"):
|
|
await run_trial(replace(resume_config, effort="high"))
|
|
|
|
|
|
def test_build_roles_forward_effort_and_grant_full_access(
|
|
tmp_path: Path, monkeypatch: pytest.MonkeyPatch
|
|
) -> None:
|
|
class CapturedAgent:
|
|
def __init__(self, backend: object, **options: object) -> None:
|
|
self.backend = backend
|
|
self.effort = options["effort"]
|
|
self.sandbox = options["sandbox"]
|
|
self.instructions = options["instructions"]
|
|
|
|
monkeypatch.setattr(trial, "UnifiedAgent", CapturedAgent)
|
|
config = TrialConfig(
|
|
run_id="effort-trial",
|
|
goal="Assess the target.",
|
|
targets=("http://target.test",),
|
|
backend="claude",
|
|
model="claude-opus-4-8",
|
|
runs_root=tmp_path / "runs",
|
|
workspace_root=tmp_path / "agents",
|
|
effort="xhigh",
|
|
)
|
|
|
|
supervisor, executor = trial._build_roles(config, TraceStore(config.runs_root))
|
|
|
|
assert supervisor.runner.agent.effort == "xhigh"
|
|
assert executor.runner.agent.effort == "xhigh"
|
|
assert supervisor.runner.agent.sandbox is SandboxPolicy.FULL_ACCESS
|
|
assert executor.runner.agent.sandbox is SandboxPolicy.FULL_ACCESS
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_trial_rejects_a_path_like_run_id_before_creating_artifacts(
|
|
tmp_path: Path,
|
|
) -> None:
|
|
config = TrialConfig(
|
|
run_id="../escape",
|
|
goal="Assess the target.",
|
|
targets=("http://target.test",),
|
|
backend="claude",
|
|
model="claude-opus-4-8",
|
|
runs_root=tmp_path / "runs",
|
|
workspace_root=tmp_path / "agents",
|
|
)
|
|
|
|
with pytest.raises(ValueError, match="run_id must be"):
|
|
await run_trial(config)
|
|
|
|
assert not (tmp_path / "escape").exists()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_failed_trial_summary_has_typed_failure_and_no_active_lease(
|
|
tmp_path: Path,
|
|
) -> None:
|
|
runs_root = tmp_path / "runs"
|
|
traces = TraceStore(runs_root)
|
|
supervisor = Supervisor(
|
|
EpisodeRunner(
|
|
UnifiedAgent(
|
|
FailureSupervisorBackend(),
|
|
workspace=tmp_path / "supervisor",
|
|
sandbox=SandboxPolicy.FULL_ACCESS,
|
|
instructions=SUPERVISOR_INSTRUCTIONS,
|
|
),
|
|
traces,
|
|
)
|
|
)
|
|
executor = Executor(
|
|
EpisodeRunner(
|
|
UnifiedAgent(
|
|
FailureExecutorBackend(),
|
|
workspace=tmp_path / "executor",
|
|
sandbox=SandboxPolicy.FULL_ACCESS,
|
|
instructions=EXECUTOR_INSTRUCTIONS,
|
|
),
|
|
traces,
|
|
),
|
|
max_turns=2,
|
|
)
|
|
config = TrialConfig(
|
|
run_id="failed-trial",
|
|
goal="Assess the target.",
|
|
targets=("http://target.test",),
|
|
backend="claude",
|
|
model="claude-opus-4-8",
|
|
runs_root=runs_root,
|
|
workspace_root=tmp_path / "agents",
|
|
max_decisions=2,
|
|
supervisor_max_turns=2,
|
|
executor_max_turns=2,
|
|
)
|
|
|
|
summary = await run_trial(config, supervisor=supervisor, executor=executor)
|
|
audit = audit_run(runs_root / "failed-trial", expected_flag="FLAG{not-present}")
|
|
|
|
assert summary["status"] == "failed"
|
|
assert summary["error"] == "max_turns: Reached maximum number of turns (2)"
|
|
assert summary["attempts"][0]["status"] == "error"
|
|
assert summary["attempts"][0]["failure_kind"] == "max_turns"
|
|
assert summary["tasks"][0]["status"] == "failed"
|
|
assert audit["checks"]["no_active_tasks"] is True
|
|
assert audit["checks"]["no_active_attempts"] is True
|
|
assert audit["checks"]["all_failed_episodes_settled"] is True
|
|
assert audit["checks"]["transition_timeline_complete"] is True
|
|
assert audit["passed"] is False
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_run_level_supervisor_failure_is_present_in_the_trial_summary(
|
|
tmp_path: Path,
|
|
) -> None:
|
|
runs_root = tmp_path / "runs"
|
|
traces = TraceStore(runs_root)
|
|
supervisor = Supervisor(
|
|
EpisodeRunner(
|
|
UnifiedAgent(
|
|
InvalidSupervisorBackend(),
|
|
workspace=tmp_path / "supervisor",
|
|
sandbox=SandboxPolicy.FULL_ACCESS,
|
|
instructions=SUPERVISOR_INSTRUCTIONS,
|
|
),
|
|
traces,
|
|
)
|
|
)
|
|
executor = Executor(
|
|
EpisodeRunner(
|
|
UnifiedAgent(
|
|
FailureExecutorBackend(),
|
|
workspace=tmp_path / "executor",
|
|
sandbox=SandboxPolicy.FULL_ACCESS,
|
|
instructions=EXECUTOR_INSTRUCTIONS,
|
|
),
|
|
traces,
|
|
)
|
|
)
|
|
config = TrialConfig(
|
|
run_id="supervisor-failure",
|
|
goal="Assess the target.",
|
|
targets=("http://target.test",),
|
|
backend="claude",
|
|
model="claude-opus-4-8",
|
|
runs_root=runs_root,
|
|
workspace_root=tmp_path / "agents",
|
|
)
|
|
|
|
summary = await run_trial(config, supervisor=supervisor, executor=executor)
|
|
|
|
assert summary["status"] == "failed"
|
|
assert summary["error"].startswith("supervisor_contract: Supervisor failed after 2 attempts")
|
|
assert summary["transitions"][-1]["kind"] == "supervisor_failed"
|
|
|
|
|
|
def test_cli_returns_nonzero_for_a_canonical_failed_run(
|
|
monkeypatch: pytest.MonkeyPatch,
|
|
) -> None:
|
|
async def failed_run(config: TrialConfig) -> dict[str, object]:
|
|
assert config.effort == "xhigh"
|
|
return {"status": "failed", "run_id": config.run_id}
|
|
|
|
monkeypatch.setattr(trial, "run_trial", failed_run)
|
|
|
|
exit_code = trial.main(
|
|
[
|
|
"--goal",
|
|
"Assess the target.",
|
|
"--target",
|
|
"http://target.test",
|
|
"--run-id",
|
|
"failed-cli",
|
|
"--effort",
|
|
"xhigh",
|
|
]
|
|
)
|
|
|
|
assert exit_code == 1
|