evil-winrm-py
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evil-winrm-py is a Python-based tool for executing commands on remote Windows machines using the WinRM protocol via an interactive shell.
evil-winrm-py --mcp --mcp-host 127.0.0.1 --mcp-port 8000 evil-winrm-py -i 192.168.1.100 -u operator -p P@ssw0rd -c JEA_Endpoint services runps /path/to/local/script.ps1 evil-winrm-py -k -i dc01.corp.local --debug upload ~/tools/mimikatz.exe C:\Windows\Temp\m.exe loadps /opt/scripts/PowerView.ps1 ewp -i 192.168.1.10 -u Administrator -p 'P@ssw0rd' --user-agent 'Mozilla/5.0 (Windows NT 10.0; Win64; x64)' evil-winrm-py --debug -i <target> -u <username> -p <password>
Summary
evil-winrm-py is an open-source, free command-line tool for executing commands on remote Windows machines over WinRM, run as an interactive shell from a terminal on Windows or Linux. It supports NTLMNTLMA Windows authentication protocol that proves knowledge of a password through a challenge and response. Captured authentication exchanges can be abused in relay attacks when protections are absent., Pass-the-Hash, Certificate, and KerberosKerberosA network authentication protocol that uses tickets issued by a trusted service. Users and services can prove their identities without sending a password to each application. authentication, along with file upload/download, tab completion, and commands like runexe, loaddll, and services for enumerating privilege escalationprivilege escalationGaining permissions beyond those an account or process initially had. It can turn limited access into administrator control or access to another user's resources. targets, making it a fit 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 post-exploitation work on authorized engagements. It is a Python rewrite of the Ruby-based evil-winrm, built to lower that barrier to entry while adding features like Kerberos trace logging and User-Agent spoofing. First committed in 2025, it already has 20 releases and 53 commits from three contributors in the past year, though the most recent release landed 153 days ago.
evil-winrm-py is a Python-based tool for executing commands on remote Windows machines using the WinRM protocol via an interactive shell.
How evil-winrm-py helps
Which non-admin services on a compromised Windows host could be abused to escalate privileges?
lists the running non-system services on the remote machine so an operator can spot misconfigured service binaries or paths worth attacking, without needing a separate enumeration script
How do I get my own post-exploitation logic running on a target without dropping a script to disk first?
reads a local PowerShell script and loads its functions straight into the remote session's memory, keeping the payload out of the target's filesystem
Which credentials will actually get me onto this host — a password, a hash, a cert, or a ticket?
negotiates the session using whichever of NTLM, Pass-the-Hash, certificate, or Kerberos material is supplied, so one shell handles whichever credential an engagement yields
Will my WinRM traffic stand out next to legitimate admin activity on this network?
lets the operator set the client's User-Agent string to match expected traffic instead of the default value that flags the connection as this tool
Why is my Kerberos authentication failing against this target?
turns on detailed Kerberos negotiation tracing so an operator can see where SPN or realm resolution broke down, and warns upfront when no credential cache exists
Can I move files in and out of the session without knowing the exact destination path or fighting shell quoting?
fills in the working directory when a path is omitted and strips stray quotes from dragged-and-dropped paths, so uploads and downloads proceed without manual cleanup
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 evil-winrm-py, 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 evil-winrm-py 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
8 entries
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- September 20261
- March 20261
- September 20251
- August 20252
- July 20251
- June 20252
Project health
Issue, contributor and maintainer activity in adityatelange/evil-winrm-py, 2023-10 – 2026-09, as of 2026-09-25. Twelve-month figures first; the trend lines run the whole window.
- Contributors 3 +2 vs prior 12 months
- Maintainers 1 +0 joined · −0 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 5.1 days first maintainer reply 19 hours
- Open backlog 1 of 16 issues ever filed
- Issues opened / month 0 · 0 communitymaintainers
- Open backlog 1
- Contributors / month 1
- Commits / month 15
- Stars 396
- 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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