nccgroup/SteppingStones is a Python-based red team activity hub that consolidates engagement workflows — from BloodHound data to hash cracking — into a single interface for authorized operators.
| Tool | nccgroup/SteppingStones — a red team activity hub from NCC Group for consolidating operator work during engagements |
| Category | Red team operations tooling (Python, Apache-2.0) |
| Primary Use | Centralizing authorized red team activity — including BloodHound-driven enumeration context, hash cracking workflows, and engagement recording — during sanctioned assessments |
| Safe Use | Strictly for authorized penetration tests, red team engagements, and lab environments with written client permission; NCC Group releases it for professional operators working within scope |
| Telemetry Note | As an operator-side hub rather than implanted tooling, its footprint is primarily on red team infrastructure; defenders should focus on detecting the underlying activity it orchestrates, such as BloodHound collection patterns and authentication attempts feeding cracking-hashes workflows |
SteppingStones is a red team activity hub published by nccgroup, the research and consulting arm of NCC Group, and its very positioning tells you a good deal about the problem it targets. Offensive engagements historically fracture across a dozen disconnected utilities: collection output lives in one directory, credential material in another, screenshots and notes in a third, and reconstructing the engagement timeline afterward becomes an archaeology exercise. A hub tool is an attempt to invert that — pulling the artifacts and workflows of an operation into a single working surface. The repository is written in Python, carries an Apache-2.0 license, and sits at roughly 244 stars at the time of this analysis, respectable traction for a specialist operator utility rather than a general-purpose scanner.
The repository's declared topic tags are unusually candid about where the tool's center of gravity lies: bloodhound, cobalt-strike, cracking-hashes, recording, and red-team. Read together, they sketch an architecture that is less about initial access and more about the long middle of an engagement — the phase where an operator has a foothold, is mapping the environment, is triaging credential material, and needs to remember what they did and why. That is a genuinely underserved niche. Post-exploitation frameworks excel at execution but are poor at being a notebook, an evidence locker, and a workflow dashboard simultaneously, and SteppingStones appears to be aimed squarely at that gap.
The bloodhound tag is the most architecturally revealing of the set. BloodHound collects graph data about Active Directory relationships — users, groups, sessions, ACLs — and its JSON output is voluminous and easy to lose track of across multiple collection runs. A hub that ingests or references BloodHound output is positioning itself as the layer where pathfinding results, interesting principals, and chosen attack lines are curated alongside everything else the operator touches. In an authorized assessment, this curation function matters doubly: the analyst needs the graph context at decision time, and the client ultimately needs a defensible narrative of which paths were examined and which were proven.
The cobalt-strike topic indicates that SteppingStones anticipates working alongside commercial adversary simulation infrastructure rather than replacing it. Cobalt Strike remains a fixture of professional red team work (and, regrettably, of criminally abused cracked licenses), so a hub that records or correlates activity around a Cobalt Strike engagement is essentially building the operational memory that the framework itself does not provide. What a hub can add is continuity: tying listener sessions, beacon check-ins, and operator actions into the same timeline as the BloodHound analysis and the credential work. Note the framing — this is about the operator's own engagement infrastructure, which is the legitimate, licensed deployment model, not the pirated variants defenders most often encounter in the wild.
The cracking-hashes tag points at another workflow seam the tool tries to close. Credential material recovered during an assessment — NTLM hashes, Kerberos tickets, cached credentials — typically gets shipped off to whatever cracking rig or wordlist workflow the operator favors, and the results come back as disconnected text that must be manually reconciled with where the material came from. Integrating hash cracking into a hub means provenance survives: the operator can see not only that a hash fell, but from which host and account context it originated, which is exactly the audit trail quality work in an authorized engagement demands. It is also a natural fit for Python, where orchestrating external cracking utilities and parsing their output is straightforward plumbing work.
The recording topic is, in this analyst's read, the most interesting and least common of the five. Engagement recording — capturing what was done, when, by whom, with what result — is the part of red team work that everyone acknowledges is important and almost nobody does well. A hub that treats recording as a first-class concern rather than an afterthought is building toward the compliance and reporting reality of professional engagements: clients and their insurers increasingly expect evidence that testing stayed inside scope, that privileged access was justified, and that artifacts of the test are distinguishable from artifacts of a real intrusion. Tooling that makes this recording automatic lowers the cost of doing it honestly.
Python is a pragmatic choice for this class of tool. The hub does not need to live on target infrastructure or evade anything — it is operator-side, running on the assessment workstation or team server where the red teamers themselves work. That means the selection criteria for the language are ergonomics and library availability, not stealth or footprint, and Python's ecosystem covers every integration the topic list implies: JSON handling for BloodHound output, subprocess and API wrappers for cracking and Cobalt Strike-adjacent tooling, and whatever storage layer backs the recording function. The Apache-2.0 license is permissive and patent-granting, consistent with NCC Group's pattern of releasing internal tooling for community benefit.
What should a professional evaluating SteppingStones watch for? First, trust boundary placement: a hub aggregating BloodHound graphs, credential material, and engagement recordings becomes a high-value concentration of sensitive data on the operator's side, so its storage, access controls, and any network-exposed components deserve scrutiny before pointing production engagement data at it. Second, provenance of the code itself — the NCC Group organizational account provides strong assurance here, as it is an established publisher of offensive-security research tooling, but any deployment should still be pinned to a reviewed commit. Third, integration assumptions: topics like cobalt-strike imply specific versions or deployment models, and mismatches between the hub's expectations and the team's actual stack will surface quickly in practice.
From a defender's perspective, tools like SteppingStones are worth understanding even though they never touch the target network directly. The hub's existence is a reminder that competent adversary teams — whether authorized or hostile — run structured, recorded, auditable operations, and the activity defenders detect (BloodHound-style LDAP enumeration, authentication anomalies feeding credential attacks) is downstream of that structured decision-making. Knowing that operators curate BloodHound paths before acting on them reinforces the defensive value of graph-aware monitoring: detecting the collection phase buys time before the curated path is walked.
The repository's README was empty in the retrieved snapshot, so this analysis is built from the repository's metadata, topic taxonomy, and publisher context rather than feature documentation — readers should treat capability specifics as inferences from those signals and verify against the source directly. Installation and usage detail would need to come from the repository itself; the standard pattern for a Python project of this shape is a git clone of nccgroup/SteppingStones followed by dependency installation per the repository's own packaging files. Within that caveat, SteppingStones represents a credible and thoughtfully scoped entry in the small but growing category of red team operations-support tooling: not another scanner, not another implant, but the connective tissue that makes an authorized engagement legible to both the operator running it and the client receiving the report.
nccgroup/SteppingStones.Educational analysis for authorized security professionals. Use only in controlled, authorized environments.
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