项目文件夹

文件
Gelei Deng ab5fbb4d90 feat: ship the durable multi-model autonomous PentestGPT runtime (#493)
* 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>
2026-07-13 16:49:08 +08:00

232 行
8.4 KiB
Python

"""Claude Code backend via claude-agent-sdk (bundles the Claude Code CLI).
Sandbox policy is mapped onto Claude Code's permission system. Claude Code has
no OS sandbox by default, so READ_ONLY removes write/shell tools entirely
(`dontAsk` denies anything not allow-listed), while Codex can still execute
commands inside its read-only OS sandbox — the honest asymmetry documented in
the README.
"""
from __future__ import annotations
from collections.abc import AsyncIterator, Iterator
from claude_agent_sdk import (
AssistantMessage,
ClaudeAgentOptions,
CLINotFoundError,
ProcessError,
ResultMessage,
StreamEvent,
SystemMessage,
TextBlock,
ThinkingBlock,
ToolResultBlock,
ToolUseBlock,
UserMessage,
query,
)
from ..events import (
AgentEvent,
AssistantText,
RawEvent,
Reasoning,
SessionStarted,
TextDelta,
ToolCall,
ToolResult,
TurnCompleted,
)
from ..types import (
AgentAuthError,
AgentRunError,
BackendUnavailableError,
RunOptions,
SandboxPolicy,
ToolServerError,
UnifiedUsage,
)
READ_TOOLS = ["Read", "Glob", "Grep"]
WRITE_TOOLS = ["Write", "Edit", "NotebookEdit"]
EXEC_TOOLS = ["Bash"]
# statuses the init message may report for an MCP server that is not usable
_BAD_MCP_STATUSES = {"failed", "needs-auth", "needs_auth", "error"}
def build_options(opts: RunOptions) -> ClaudeAgentOptions:
allowed: list[str]
disallowed: list[str] = []
if opts.sandbox is SandboxPolicy.READ_ONLY:
permission_mode = "dontAsk" # deny anything not allow-listed, never prompt
allowed = list(READ_TOOLS)
disallowed = WRITE_TOOLS + EXEC_TOOLS
elif opts.sandbox is SandboxPolicy.WORKSPACE_WRITE:
permission_mode = "acceptEdits"
allowed = READ_TOOLS + WRITE_TOOLS + EXEC_TOOLS
else: # FULL_ACCESS
permission_mode = "bypassPermissions"
allowed = READ_TOOLS + WRITE_TOOLS + EXEC_TOOLS
mcp_servers: dict = {}
if opts.tool_server is not None:
spec = opts.tool_server
mcp_servers[spec.server_name] = {
"type": "stdio",
"command": spec.command[0],
"args": spec.command[1:],
"env": dict(spec.env),
}
allowed.append(f"mcp__{spec.server_name}__*")
return ClaudeAgentOptions(
cwd=str(opts.workspace),
model=opts.model,
permission_mode=permission_mode,
allowed_tools=allowed,
disallowed_tools=disallowed,
mcp_servers=mcp_servers,
# Hermetic: only project-level settings/skills/CLAUDE.md from the
# workspace; no user/local config bleeding into runs.
setting_sources=["project"],
# Always run with Claude Code's native system prompt: passing None
# strips it entirely — including the working-directory env context —
# which makes the model write files outside the workspace. This
# mirrors Codex, where developer_instructions append to (never
# replace) the base prompt.
system_prompt=(
{"type": "preset", "preset": "claude_code", "append": opts.instructions}
if opts.instructions
else {"type": "preset", "preset": "claude_code"}
),
output_format=(
{"type": "json_schema", "schema": opts.output_schema} if opts.output_schema else None
),
effort=opts.effort,
resume=opts.resume,
max_turns=opts.max_turns,
env=dict(opts.extra_env),
include_partial_messages=opts.stream_text,
)
def _stringify_block_content(content) -> str:
if content is None:
return ""
if isinstance(content, str):
return content
parts = []
for item in content:
if isinstance(item, dict):
parts.append(str(item.get("text", item)))
else:
parts.append(str(item))
return "\n".join(parts)
def normalize_message(message, opts: RunOptions) -> Iterator[AgentEvent]:
if isinstance(message, SystemMessage):
if message.subtype == "init":
data = message.data or {}
if opts.tool_server is not None:
for server in data.get("mcp_servers", []):
if (
server.get("name") == opts.tool_server.server_name
and server.get("status") in _BAD_MCP_STATUSES
):
raise ToolServerError(
f"MCP tool server '{server['name']}' failed to connect in "
f"Claude Code (status={server.get('status')!r})"
)
session_id = data.get("session_id")
if session_id:
yield SessionStarted(session_id=session_id)
else:
yield RawEvent(backend="claude", kind=f"system:{message.subtype}", data=message.data)
elif isinstance(message, AssistantMessage):
if message.error == "authentication_failed":
raise AgentAuthError(
"Claude Code is not authenticated: run `claude /login` or set ANTHROPIC_API_KEY"
)
if message.error:
yield RawEvent(
backend="claude", kind=f"assistant_error:{message.error}", data=message.error
)
for block in message.content:
if isinstance(block, TextBlock):
yield AssistantText(text=block.text)
elif isinstance(block, ThinkingBlock):
yield Reasoning(text=block.thinking)
elif isinstance(block, ToolUseBlock):
yield ToolCall(name=block.name, input=block.input, call_id=block.id)
elif isinstance(block, ToolResultBlock):
yield ToolResult(
call_id=block.tool_use_id,
output=_stringify_block_content(block.content),
is_error=bool(block.is_error),
)
elif isinstance(message, UserMessage):
content = message.content
if isinstance(content, list):
for block in content:
if isinstance(block, ToolResultBlock):
yield ToolResult(
call_id=block.tool_use_id,
output=_stringify_block_content(block.content),
is_error=bool(block.is_error),
)
elif isinstance(message, StreamEvent):
if opts.stream_text:
event = message.event or {}
delta = event.get("delta") or {}
if event.get("type") == "content_block_delta" and delta.get("type") == "text_delta":
yield TextDelta(text=delta.get("text", ""))
elif isinstance(message, ResultMessage):
usage = message.usage or {}
success = (not message.is_error) and message.subtype == "success"
errors = getattr(message, "errors", None) or []
yield TurnCompleted(
success=success,
final_text=message.result,
usage=UnifiedUsage(
input_tokens=usage.get("input_tokens", 0) or 0,
cached_input_tokens=usage.get("cache_read_input_tokens", 0) or 0,
output_tokens=usage.get("output_tokens", 0) or 0,
),
cost_usd=message.total_cost_usd,
session_id=message.session_id,
duration_ms=message.duration_ms,
structured_output=message.structured_output,
stop_reason=message.subtype,
error=None if success else ("; ".join(errors) or message.subtype),
)
else:
yield RawEvent(backend="claude", kind=type(message).__name__, data=message)
class ClaudeCodeBackend:
name = "claude"
async def stream(self, prompt: str, opts: RunOptions) -> AsyncIterator[AgentEvent]:
try:
async for message in query(prompt=prompt, options=build_options(opts)):
for event in normalize_message(message, opts):
yield event
except CLINotFoundError as e:
raise BackendUnavailableError(f"Claude Code CLI not found: {e}") from e
except ProcessError as e:
stderr = (e.stderr or "").strip()
lowered = stderr.lower()
if "auth" in lowered or "login" in lowered or "api key" in lowered:
raise AgentAuthError(f"Claude Code process failed (auth): {stderr}") from e
raise AgentRunError(
f"Claude Code process failed (exit {e.exit_code}): {stderr[-2000:]}"
) from e