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passdetective

v1.0.0 open-source

PassDetective is a command-line tool that scans shell command history for mistakenly written passwords, API keys, and secrets using regular expressions.

Summary

passdetective is an open-source, MIT-licensed command-line tool that scans shell command history for passwords, API keys, and other secrets accidentally typed into a terminal, using regular expressions to flag likely matches. It installs as a Go binary or through Kali Linux and Nix packages, and runs locally against files like ZSH history rather than as a hosted service, which suits developers and pentesters auditing their own machines or hardening a Kali image before an engagement. It sits in the secrets-detection space alongside tools that scan git repositories or filesystems, but focuses narrowly on shell history and packet capturespacket capturesA packet capture, recorded network packets that can be inspected later. Analysts use it to reconstruct communication and investigate protocol behavior or suspicious traffic. rather than source code. In testing it caught a planted AWS key correctly, though it listed the same finding under two overlapping labels. First committed in 2023 with three contributors, it has seen only one commit in the past year despite five tracked releases, so treat it as lightly maintained.

PassDetective is a command-line tool that scans shell command history for mistakenly written passwords, API keys, and secrets using regular expressions.

How passdetective helps

Have I ever typed a live password or API key into a command that got saved to my shell history?

reads the shell history file and runs a set of regular expressions over every line, flagging commands that match known secret patterns like AWS keys or passwords passed inline

Which past commands leaked a credential, and what did they expose?

lists each matching line alongside the label of the secret type it matched, such as an AWS access key ID or a password flag

Are the same leaked credentials being counted more than once in my results?

can list one leaked value under two separate labels when it matches more than one regular expression, so the count of findings can overstate the number of distinct secrets

Did a key I pasted into a command months ago ever get written to disk in plain text?

scans the full contents of the history file rather than only recent entries, so a match surfaces regardless of how long ago the line was typed

Languages

Not documented

Score card

  1. Shipping velocity releases a month, last 12 months
  2. Documentation quality release-notes rubric, 0–100
  3. Breaking-change discipline how rarely a release breaks users, and notice given
  4. Maintenance risk quiet time against its own cadence, maintainers
  5. Innovation & surface new capabilities, API and MCP surface
  6. Community health
  7. Contributor trend distinct committers, this year against last
  8. Maintainer concentration bus factor now against a year ago
  9. Issue backlog trend issues closed per issue opened, 12 months
  10. Responsiveness median time to a maintainer’s first reply

Nine scores for passdetective, 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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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 passdetective 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…

Explore the full chart →

Releases

1 entry

  1. August 20231

    1 entry

    Project health

    Issue, contributor and maintainer activity in aydinnyunus/PassDetective, 2023-10 – 2026-09, as of 2026-09-25. Twelve-month figures first; the trend lines run the whole window.

    1. Contributors 1 +1 vs prior 12 months
    2. Maintainers 0 +0 joined · −0 left, last 12 months
    3. Bus factor 0 committers behind half the commits
    4. Community-filed not measured of issues opened, last 12 months
    5. Median time to close not measured issues closed, last 12 months
    6. Open backlog 0 of 2 issues ever filed
    1. Issues opened / month 0 · 0 communitymaintainers
    2. Open backlog 0
    3. Contributors / month 0
    4. Commits / month 0
    5. Stars 148
    Issue themes, last 12 months not measured

    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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