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arjun

2.2.7 open-source

Arjun is an HTTP Parameter Discovery Suite that finds valid query parameters for URL endpoints using a default dictionary of 25,890 parameter names.

Summary

arjun is an open-source command-line tool that discovers hidden HTTP parameters on URL endpoints by probing them against a dictionary of 25,890 names while keeping request counts low. It is free to use, installed via pipx, and run directly from a terminal against a single URL or a list imported from Burp Suite, a text file, or a raw request file. It suits penetration testers and bug bounty hunters doing web recon, fitting into the parameter-discovery and fuzzing stage of an engagement rather than replacing broader scanners. Options like --casing and --rate-limit let it match an API's naming style or stay under a WAFWAFA reverse proxy that inspects HTTP/HTTPS traffic and blocks requests matching known attack patterns such as SQL injection or XSS, sitting between clients and a web application to filter malicious input before it reaches the server.'s threshold during sensitive work. First committed in 2018 with 26 contributors and 41 tracked releases, it has had no commits in the past year, with its last release 656 days ago.

Arjun is an HTTP Parameter Discovery Suite that finds valid query parameters for URL endpoints using a default dictionary of 25,890 parameter names.

How arjun helps

Which hidden parameters does this endpoint actually accept?

probes the URL with a dictionary of 25,890 parameter names in a small number of chunked requests and reports back the names that produce a distinct response

Does this API expect its parameters in a particular naming style?

matches discovered parameter names to a chosen casing convention so results line up with how the target actually names them, cutting down false negatives from style mismatches

Can I probe this target without tripping its rate limits during a sensitive test?

caps outgoing requests to a set number per second so discovery stays under a WAF or server's threshold instead of firing all chunks at once

Where did this parameter list come from before I start probing?

pulls parameter candidates directly out of a JavaScript response or an imported request before adding them to the dictionary it tests

all 5 features, with the evidence for each →

Languages

Not documented

Features

5 capabilities · 3 backed by code, an API document or a real run

Built from arjun's releases, docs, README and our own runs. “Seen” marks the month we first spotted a release the vendor didn't date. Group names and tags are our labels.

Compare with peers →

  • arjun covers 1 of the 8 vulnerability assessment methods capabilities we track.

What arjun offers you

  • Command-line interface2
Web vulnerability scanning 3 features Vulnerability assessment methods since 2020
Parameter discovery via logic-forcing verified Extracts parameters from HTTP responses and probes endpoints across chunked wordlists to discover hidden or additional parameters. 3 releases · 9 other sources · first seen Dec 2020

Shared capability: Web vulnerability scanning

release

docs

  • Discovers hidden HTTP parameters for URL endpoints using a dictionary of 25,890 parameter names with minimal requests.

we ran it 7 total

  • The tool extracted 4 parameters from the response (password, user_token, username, Login) and began logic-forcing the endpoint across 25,891 total chunks. Aug 2026 · the full run
  • After working through all 103 chunks during logicforcing, the tool reported no parameters were discovered. The run exited with status 0, indicating a clean completion rather than an error. Aug 2026 · the full run
  • The tool extracted 4 parameters from the HTTP response (password, user_token, Login, username) for testing, then worked through all 103 chunks during logicforcing but ultimately reported no… Aug 2026 · the full run
  • The tool extracted 4 parameters from the response (password, Login, username, user_token) for testing, then worked through all 103 chunks of its wordlist. Aug 2026 · the full run
  • The tool extracted 4 parameters from the HTTP response (user_token, Login, password, username) for testing, then worked through all 103 chunks of logic-forced probing. Aug 2026 · the full run
  • The tool extracted 4 parameters from the response (username, password, Login, user_token) for initial analysis, then worked through all 103 chunks during logic-forcing but ultimately reported no… Aug 2026 · the full run

example

  • Discover parameters on a target that redirects requests, preventing Arjun from following the redirect chain. arjun -u "https://example.com/page" --disable-redirects 2.1.5 · Apr 2022 · source
Parameter name casing control verified Allows the user to specify the casing style applied to parameter names when sending requests. 1 release · 2 other sources · first seen Nov 2024

Shared capability: Web vulnerability scanning

release

  • New --casing option enforces a specific casing style on discovered parameters. 2.2.7 · Nov 2024 · source · release history

command line

  • --casing — casing style for params e.g. like_this, likeThis, likethis 2.2.7 · Nov 2024 · command-line history

example

  • Enforce camelCase output when probing an API that uses camelCase parameter names, reducing false negatives from style mismatches. arjun -u https://api.example.com/endpoint --casing camel 2.2.7 · Nov 2024 · source
Parameter value correlation detection shipped Detects parameters that respond specifically to a given payload by probing with specific values, and identifies required parameters for valid responses using heuristic analysis of response content. 3 releases · first seen Sep 2022

Shared capability: Web vulnerability scanning

Also counts toward: Command-line interface

release

  • Adds --detect-value to enable detection of parameters that respond specifically to a given payload (e.g., identifying boolean-based blind injection points by probing with specific values). 2.2.0 · Sep 2022 · source · release history
  • Adds --req-param flag to trigger required parameter detection, allowing the tool to identify parameters that must be present for valid responses. 2.2.0 · Sep 2022 · source · release history
  • Updates heuristic engine to extract semantic content from JSON and text responses, improving context awareness for value-correlated detections. 2.2.0 · Sep 2022 · source · release history
Other / not yet classified 2 features Features we have not matched to a capability yet. A suggested match is marked.
Request rate limiting verified suggested Controls the maximum number of requests sent per second during a run. 1 release · 3 other sources · first seen Dec 2020

Suggested capability: Web vulnerability scanning. This is our guess, not confirmed.

release

  • New --ratelimit option sets an explicit requests-per-second cap during scanning. 2.2.7 · Nov 2024 · source · release history

command line

  • --rate-limit — Max number of requests to be sent out per second (default: 9999) 2.2.5 · Apr 2024 · command-line history

example

  • Throttle discovery to stay under a WAF or target server's request threshold during a sensitive engagement. arjun -u https://target.example.com/search --ratelimit 5 2.2.7 · Nov 2024 · source
  • Set a specific timeout for HTTP requests to handle slow or unresponsive endpoints. arjun -u https://example.com -T 30 2.0-beta · Dec 2020 · source
Concurrency control shipped suggested Controls the number of concurrent requests or parameters sent to avoid overwhelming the target server. 1 release · 1 other source · first seen Dec 2020

Suggested capability: Web vulnerability scanning. This is our guess, not confirmed.

Also counts toward: Command-line interface

release

  • -c option to define number of parameters to be sent at once 2.0-beta · Dec 2020 · source · release history

example

  • Control concurrency to avoid overwhelming the target server during large-scale scanning. arjun -u https://example.com -c 10 2.0-beta · Dec 2020 · source

Lines in monospace are the tool's own words: help text parsed from its source, or an endpoint from its API document. Under release, a line is our summary of a dated release. Under docs, it is quoted from the tool's own documentation or website. Each links back to the source it came from.

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 arjun, 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 arjun 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

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4 entries

  1. November 20241
  2. September 20221
  3. April 20221
  4. December 20201
    Show

    4 entries

    Project health

    Issue, contributor and maintainer activity in s0md3v/Arjun, 2023-10 – 2026-09, as of 2026-09-25. Twelve-month figures first; the trend lines run the whole window.

    1. Contributors 0 −3 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 100% of issues opened, last 12 months
    5. Median time to close not measured issues closed, last 12 months
    6. Open backlog 20 of 158 issues ever filed
    1. Issues opened / month 0 · 0 communitymaintainers
    2. Open backlog 20
    3. Contributors / month 0
    4. Commits / month 0
    5. Stars 6,397
    Issue themes, last 12 months
    • 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

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