dploot
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Python tool for remotely or locally looting DPAPIDPAPIA Windows OS cryptographic API that encrypts and decrypts secrets tied to a user or machine identity, so applications can store credentials without managing raw keys themselves.-protected secrets (masterkeys, credentials, certificates, browser data) from Windows systems.
dploot wam -u <user> -p <password> -d <domain> <target>
Summary
dploot is an open-source command-line tool that extracts DPAPI-protected secrets—credentials, certificates, browser passwords, vaults, and masterkeys—from Windows systems, and it is free to use. It is a Python rewrite of SharpDPAPI (itself a port of Mimikatz's DPAPI logic), so unlike those tools it runs from a Linux interpreter rather than requiring a Windows or .NET environment, connecting to targets remotely over SMBSMBA network file-sharing protocol developed by Microsoft that lets systems share files, printers, and named pipes over a network; cyber tools target or speak it because it is ubiquitous in Windows environments. or running locally on a compromised host. It is built for red teamers and penetration testers doing lateral movementlateral movementMoving from an initially compromised system or identity to other resources in a network. Attackers often use stolen credentials or trusted connections to expand their access. and credential harvesting during Windows engagements, covering scenarios from local administrator access to offline filesystem review to domain-backup-key abuse. Its README frames it explicitly as a successor to SharpDPAPI and Mimikatz's DPAPI module. Started in 2022 with 13 contributors and 30 commits in the past year, though its last release was over 500 days ago.
Python tool for remotely or locally looting DPAPI-protected secrets (masterkeys, credentials, certificates, browser data) from Windows systems.
How dploot helps
Which users on this network have decryptable saved credentials, browser passwords, or vaults sitting on their machines?
connects over SMB with the supplied credentials, pulls each user's masterkeys and DPAPI blobs, decrypts them in memory, and lists the recovered secrets by user and host
Can domain admin access be turned into every user's DPAPI secrets across the domain?
uses the domain backup key to decrypt any user's masterkeys without needing their password or hash, then loots credentials, certificates, and vaults from every reachable machine
What can be recovered from a disk image or offline copy of a compromised machine without booting it?
reads masterkeys and secrets straight from a mounted filesystem path instead of a live connection, working the same triage logic against files on disk
Which locked or in-use files are blocking a full credential harvest, and can they be read anyway?
works around sharing-violation errors on files held open by other processes, and can kill the owning browser process first so its credential store can still be read
Are there OAuth or Azure tokens cached locally that could let an attacker pivot into cloud accounts?
reads the Token Broker Cache to recover Windows Authentication Manager tokens tied to Azure/OAuth sign-ins
Is a particular masterkey crackable offline, and what would that take?
dumps masterkey hashes in a hashcat/John the Ripper compatible format for offline brute-forcing when the backup key or SYSTEM secrets aren't available
Languages
Command line
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Score card
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Shipping velocity releases a month, last 12 months
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Documentation quality release-notes rubric, 0–100
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Breaking-change discipline how rarely a release breaks users, and notice given
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Maintenance risk quiet time against its own cadence, maintainers
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Innovation & surface new capabilities, API and MCP surface
- Community health
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Contributor trend distinct committers, this year against last
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Maintainer concentration bus factor now against a year ago
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Issue backlog trend issues closed per issue opened, 12 months
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Responsiveness median time to a maintainer’s first reply
Nine scores for dploot, each built from the releases, notes and API history this site tracks — and, on Researcher and Business, where it stands among every measured tool in its category and how that has moved.
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Blank means never measured; nothing here is a filled-in zero.
Peer standings are included with Researcher and Business. See how this tool ranks against its competitors, using data we don't publish anywhere else.
See plans →Each score is 0–100 on a published rubric, derived from data this site already shows. A dimension we cannot measure says so — it is never scored 0 and never enters a rank.
How this is scored
- Shipping velocity — releases a month over the last 12 months, on a log scale where 16 a month scores 100. Needs 3 releases in the window.
- Documentation quality — the release-notes rubric published on the analytics page, unchanged.
- Breaking-change discipline — the share of releases carrying a breaking change (none scores 100, half or more scores 0). Only projects that label breaking changes are measured: a clean record cannot be told from an unlabelled one.
- Maintenance risk — quiet time measured against the tool's own release cadence (quiet longer than 90 days and three typical gaps scores 0), plus the number of active maintainers and whether contributors are growing, where known. Higher is lower risk.
- Innovation & surface — new capabilities in the feature ledger this year, API and MCP operations added, and the share of commits that are features: the mean of whichever we hold.
- Community health (open-source tools only) — each is a direction, not a size: contributors this year against last, the bus factor now against a year ago, and issues closed per issue opened, where steady scores 50, doubled 100 and halved 0; plus the median time to a maintainer's first reply (an hour scores about 100, a month or more 0). A commercial card has no repository and carries none of the four.
- Documented delivery (commercial tools) — when a vendor's documented new capabilities have slowed against its own baseline, that counts against the overall standing as heavily as two low dimensions. Steady delivery, or too little history to judge, leaves the standing alone; it is never a sixth score.
- Open-source tools are scored on repository signals; commercial tools on their published changelog. Ranks compare tools within one category and one profile and need at least five measured peers; the overall standing needs three ranked dimensions. Best-in-breed or consolidator is a shape, not a quality, and is never scored.
Release-note detail over time
See how much detail dploot puts in its release notes, quarter by quarter, and compare it with tracked tools in the same category. This history uses up to ten retained, reviewed notes per tool; sparse or blank older quarters may reflect that limit.
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Releases
3 entries
No entries match these filters.
- April 20251
- July 20241
- March 20241
Project health
Issue, contributor and maintainer activity in zblurx/dploot, 2023-10 – 2026-09, as of 2026-09-25. Twelve-month figures first; the trend lines run the whole window.
- Contributors 4 −1 vs prior 12 months
- Maintainers 2 +2 joined · −1 left, last 12 months
- Bus factor 1 committers behind half the commits
- Community-filed 100% of issues opened, last 12 months
- Median time to close 5.9 days first maintainer reply 3.5 days
- Open backlog 5 of 18 issues ever filed
- Issues opened / month 0 · 0 communitymaintainers
- Open backlog 5
- Contributors / month 2
- Commits / month 2
- Stars 570
- other 100%
Counts from the project's public repository and git history; no individuals are identified. Maintainers are the committers covering 80% of the last year's commits. how we measure this
Libraries its release ships
What its latest release locks, checked against known advisories.None of its release's images build from a lockfile we can read.
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