peass-ng
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Suite of scripts for Windows, Linux/Unix, and macOS that enumerate local 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. paths and highlight misconfigurations.
Summary
peass-ng is an open-source suite of privilege escalation scripts, run as command-line tools (LinPEAS for Linux/Unix, WinPEAS for Windows), that scan a system for local misconfigurations and enumeration paths an attacker could use to escalate privileges, flagging them in color-coded output for quick triage. It's aimed at penetration testers and red teamers doing post-exploitation work, rather than defenders monitoring systems, since it assumes you already have a foothold and are looking for a way up. Output can be converted to JSON, HTML or PDF for reporting, and options like timeout, retries and a small build suit running it on constrained targets. It fits the same niche as manual privesc checklists and enumeration scripts, but packages the checks as maintained, ready-to-run binaries. First committed in 2019, it now has 153 contributors and a release 18 days ago, so it's actively maintained.
Suite of scripts for Windows, Linux/Unix, and macOS that enumerate local privilege escalation paths and highlight misconfigurations.
How peass-ng helps
Which local misconfigurations on this box could let me escalate to root or SYSTEM?
scans the filesystem, running processes, services, cron jobs, permissions and configuration files for known privesc patterns and prints each finding color-coded by how likely it is to be exploitable
Which credentials or secrets have been left lying around on this machine?
searches config files, history files, memory and common storage locations for passwords, keys and tokens an attacker with a foothold could reuse
Which of the findings on this host actually deserve my attention first?
color-codes each result by exploitability so the red and yellow entries stand out from routine informational output in a long scan
Is this Windows box vulnerable to a known kernel or service exploit I could throw at it?
cross-references the installed patches, services and software versions against known privilege escalation vectors and lists the ones that match
What does this compromised host's privesc exposure look like once I hand the results to a client?
converts the raw scan output into JSON, HTML or PDF so the same findings can be filed as a reproducible report
Languages
Command line
| option | found in | since | description |
|---|
Values are placeholders taken from each option’s declared default. Nothing is executed here — the output shown is a recording of a run that already happened.
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 peass-ng, 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 peass-ng 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.
Checking release-note history…
Releases
Nothing shipped since we started watching. Releases and docs updates land here as they happen.
Project health
Issue, contributor and maintainer activity in carlospolop/PEASS-ng, 2023-10 – 2026-09, as of 2026-09-25. Twelve-month figures first; the trend lines run the whole window.
- Contributors 31 +9 vs prior 12 months
- Maintainers 1 +1 joined · −1 left, last 12 months
- Bus factor 1 committers behind half the commits
- Community-filed not measured of issues opened, last 12 months
- Median time to close not measured issues closed, last 12 months
- Open backlog not measured open issues today
- Issues opened / month not measured
- Open backlog not measured
- Contributors / month 5
- Commits / month 33
- Stars 20,539
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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