A previous release had provenance metadata, but this release does not. View details.
1. Positioning
ARGUS does not compete with traditional pentesting tools. It does something they inherently cannot do — test the AI-specific attack surface that none of them were built to find. If you run SAST against your infrastructure, you still need ARGUS against the agents running on top of it. They are complementary, not competing.
2. Quick start
pip install argus-core
One input, auto-routed — the same argus <anything> command engages an MCP server, clones a GitHub repo, npx-launches an MCP package, runs a local script, or opens a labrat fixture:
argus mcp://customer.example/sse # live MCP over SSE
argus github.com/vercel/mcp-handler # clone + dispatch
argus @modelcontextprotocol/server-filesystem # npx-launched stdio MCP
argus ./my_server.py # local file
argus crewai://labrat # in-process crewAI fixture
argus --list-targets # every registered scheme
argus --help # full operational surface
Engagements land in results/; render an offline HTML report with argus --report results/<run>/.
3. What you get in Core
ARGUS Core is the public showcase of the platform. Two agents ship in Core to demonstrate the architecture end-to-end against any registered target type. The full eleven-agent kit, the multi-agent slate runtime, the swarm correlation layer, the management UI, and the deployment infrastructure live in the commercial Enterprise tier — see section 4.
Two offensive agents in Core:
| Agent | Class | MAAC phase | Notes |
|---|---|---|---|
| PI-01 | Prompt Injection Hunter | 2 | Direct, indirect, encoded, and multi-step injection variants at every chat surface the target exposes |
| EP-11 | Environment Pivoting | 8 | Credential-discovery + code-execution chains; pivots from a foothold into ambient cloud / IMDS / process environments |
Both agents run on the same swarm contract (SwarmAgentMixin), so when the
swarm runtime fires they execute in parallel — the public CLI gate runs
them sequentially by default; opt into swarm with ARGUS_SWARM_MODE=1.
Platform foundation (also Core):
- Universal LLM gateway (
argus.shared.client) — single Anthropic-shaped surface dispatches to OpenAI / Anthropic / Gemini with provider failover, process-wide dead-provider blacklist, andARGUS_LLM_CHAINenv-var-driven resilience. Eight production call sites consume it; target frameworks inherit failover viabuild_litellm_kwargs. - Sandboxed engagement — wraps untrusted MCP server subprocesses in
docker runwith--cap-drop ALL,--network none,--read-only,--user 65534,--pids-limit 64. Use withargus -s <target>. - One-input dispatch —
argus <anything>auto-routes MCP URLs, GitHub repos, npm/PyPI packages, local scripts, framework labrat fixtures, and engagement directories to the right factory. - Stateful runtime harness — deterministic multi-turn replay, scenario library, runtime invariants.
- Forensic Wilson bundles — signed, reproducible evidence bundles suitable for VDP submission.
- Smart corpus mutation — offline corpus mutators with optional
live-LLM mutators behind
ARGUS_OFFLINE=0. - Workflow integrations — GitHub Action, pre-commit hook,
FastAPI webhook receiver (optional
webhookextra).
4. Core vs. Enterprise
ARGUS is open-core. Core (this package, MIT) is the public CLI: two-agent showcase, universal target dispatch, sandboxed runtime, LLM gateway, harness primitives. Self-sufficient for operators running their own focused engagements.
Enterprise is the full commercial product — eleven-agent kit
(adds TP-02 MP-03 IS-04 CW-05 XE-06 PE-07 RC-08 SC-09 ME-10 to
the two Core agents), full slate-execution runtime, swarm
correlation layer, three-judge consensus gate, MCTS chain
synthesis, web dashboard, FastAPI execution engine, deployment
infrastructure, and managed engagement delivery.
Enterprise is not currently sold as software. ARGUS Enterprise operates today as a red-team engagement service — OdinGard runs the full eleven-agent kit against customer environments and delivers findings reports. Customer-installable Enterprise is on the roadmap; the engagement service is available now.
5. Migrating from argus-redteam
argus-redteam==0.4.1 is a deprecation shim that pulls
argus-core as a dependency, so existing pip install argus-redteam
commands and requirements.txt pins continue to work with no code
change. Update at your convenience:
- pip install argus-redteam
+ pip install argus-core
The Python import name (import argus) did not change; source code
works identically under either install name.
6. Docs
docs/GETTING_STARTED.md— operator guidedocs/ADDING_A_LABRAT.md— extend ARGUS to a new frameworkdocs/NO_CHEATING.md— the integrity contract every finding must honourdocs/llm-subsystem.md— internal note on the universal LLM gatewayPHASES.md— full build plan + moat mapSECURITY.md— responsible disclosure
7. Engagement service
If you want the full eleven-agent kit run against your AI deployment by the team that built ARGUS:
8. License
Core is MIT — see LICENSE-CORE. The Enterprise tier
under LICENSE-PRO (placeholder today; formal
source-available terms to follow before any Enterprise tier is offered
as installable software) does not ship in this package.
Responsible-disclosure contact: security@sixsenseenterprise.com.
Metadata
Release files for argus-core 0.6.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Loss of provenance
These files do not have provenance metadata, despite files in a prior release including this data.
We recommend further investigation before installing these files. View details.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| argus_core-0.6.1.tar.gz | 522.7 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| argus_core-0.6.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 1.0 MB
Release files / argus_core-0.6.1.tar.gz
Loss of provenance
This file belongs to a release without provenance metadata, despite a prior release including this data.
We recommend further investigation before installing this file. View details.
| Download URL | argus_core-0.6.1.tar.gz |
|---|---|
| Size | 522.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
45041d6cd7ce9c0a2ffcf5d4f8d2d2ebb571e847188a43977c93caabe5f8c259
|
|
BLAKE2b-256 checksum How to use checksums |
770aa95e8d5bfaaf56f0819c6f352834ef9f4d2ccb54424b81dcf0d491299770
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.14.3
|
Release files / argus_core-0.6.1-py3-none-any.whl
Loss of provenance
This file belongs to a release without provenance metadata, despite a prior release including this data.
We recommend further investigation before installing this file. View details.
| Download URL | argus_core-0.6.1-py3-none-any.whl |
|---|---|
| Size | 495.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
fefc2bf4a3a1df5a129ed50f3174522746e0f4e68f1bc8a415d8a71c5d0cd381
|
|
BLAKE2b-256 checksum How to use checksums |
36cd5496edf55f5eb149020d66025e1287c06cfb245c1d6fa144d5bbff7b3d9b
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.14.3
|
Security for argus-core 0.6.1
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
Loss of provenance
A previous release of these files had provenance metadata, but this release does not.
While this could reflect a routine change by the project maintainers, it may also indicate that the release files have been compromised.
Release comparison
- Removed 0.5.0 2 files With provenance
- Added 0.6.1 2 files Without provenance
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.