The image ships 15 tools (jwt_tool, interactsh-client, arjun, dirsearch, gospider, wafw00f, retire, eslint, jshint, js-beautify, JS-Snooper, jsniper.sh, vulnx, ncat, uv) that the always-loaded skills never name with usage guidance — agents could discover them via the environment catalog but had no when/how. Add concise mentions in the natural home for each: jwt_tool in the JWT skill, interactsh-client in the OAST sections of SSRF/XXE/RCE, arjun in IDOR recon, dirsearch as the broad alternate in the ffuf skill, gospider + the JS scrapers in katana, wafw00f next to httpx, retire/eslint/jshint/js-beautify as a new JavaScript-Side Coverage block in the SAST playbook, uv in python, vulnx in the deep scan-mode CVE bullet, ncat in a new RCE Tooling block. Audit also turned up three real breakages along the way: - jwt_tool's shebang resolves to /usr/bin/python3 but its dependencies live in /app/.venv, so every invocation died with ModuleNotFoundError: ratelimit. Replace the bare symlink with a wrapper that execs /app/.venv/bin/python against the real script. - dirsearch's pipx venv ended up with setuptools 82, which dropped pkg_resources — startup failed before parsing args. Pin the inject to setuptools<81. - ESLint's --no-eslintrc flag was removed in v9; the surviving --no-config-lookup covers it. Drop the dead flag from the SAST command block. Also corrected the JS-Snooper / jsniper.sh entry in katana.md — both take a bare domain and run their own JS discovery internally, not the JS URLs Katana already harvested.
3.6 KiB
name, description
| name | description |
|---|---|
| python | Run Python through exec_command in the SDK sandbox. Use the image-baked caido_api module for Caido proxy automation from Python scripts. |
Python In The Sandbox
Use exec_command for Python. There is no separate Strix Python executor.
Prefer writing reusable scripts to /workspace/scratch/<name>.py and
running them with python3 /workspace/scratch/<name>.py. For short
one-off transformations, python3 -c or a small here-document is fine.
The shell parameter on exec_command is for swapping POSIX shells
(bash/zsh/sh), not for picking interpreters. Put the interpreter
invocation in cmd instead: cmd="python3 -c '...'", not
shell=python3, cmd="...". The shell=<interpreter> shortcut breaks
in subtle ways — python3 works only with login=False (because the
SDK adds -l/-i), and other interpreters (node, ruby, perl)
take -e not -c so they fail even with login=False.
Proxy Automation From Python
The sandbox image includes an installed caido_api module. Import it
explicitly when Python code needs Caido traffic or replay access:
from caido_api import (
list_requests,
list_sitemap,
repeat_request,
scope_rules,
view_request,
view_sitemap_entry,
)
All helpers are async. Use them inside asyncio.run(...) or an async
function:
import asyncio
from caido_api import list_requests, view_request
async def main():
posts = await list_requests(
httpql_filter='req.method.eq:"POST" AND req.path.cont:"/api/"',
first=50,
)
candidates = []
for edge in posts.edges:
request_id = edge.node.request.id
body = await view_request(request_id, part="request")
raw = body.request.raw.decode("utf-8", errors="replace")
if "id=" in raw or "user=" in raw:
candidates.append(request_id)
print(f"{len(candidates)} candidates")
print(candidates[:10])
asyncio.run(main())
Available helpers:
list_requests(httpql_filter=, first=50, after=, sort_by=, sort_order=, scope_id=)returns a cursor-paginated Caido SDKConnection.view_request(request_id, part="request")returns a Caido SDK request object with raw request/response bytes.repeat_request(request_id, modifications={...})replays a captured request after modifyingurl,params,headers,body, orcookies.list_sitemap(scope_id=, parent_id=, depth="DIRECT", page=1)walks Caido's request-tree view of the discovered surface. Omitparent_idfor root domains; pass an entry id withdepth="DIRECT"or"ALL"to drill in.view_sitemap_entry(entry_id)returns one entry plus its 30 most recent related requests.scope_rules(action, allowlist=, denylist=, scope_id=, scope_name=)manages Caido scopes.
For one-off arbitrary requests (e.g. probing a fresh endpoint, hitting an
external API), use exec_command with curl / httpx / requests. The
sandbox's HTTP_PROXY env routes all such traffic through Caido
automatically, so it shows up in list_requests and you can use
repeat_request to replay-and-modify any of it.
Workflow
For iterative exploit work, put code in a file:
1. Create or edit `/workspace/scratch/exploit.py` with `apply_patch`.
2. Run it with `exec_command`: `python3 /workspace/scratch/exploit.py`.
3. Edit and rerun until the proof-of-concept is reliable.
Installing extra packages
The sandbox's Python lives in /app/.venv. To add a one-off dependency
for an exploit script, use uv (already in the image and much faster
than pip):
uv pip install --python /app/.venv/bin/python <package>