# LinkdTime ## URL \ **no tagged releases**; latest commit **2025‑04‑11 (as of May, 2026)** ## Description LinkdTime is a small CLI Python tool that **derives precise timestamps from LinkedIn activity URLs** (posts, comments/replies, profile‑photo/background‑image/company‑logo changes) and can assemble them into a chronological timeline (HTML/TXT). For timestamping, it **decodes the numeric ID embedded in LinkedIn URLs** rather than scraping page HTML, so the time extraction itself works **without network access**; optional flags can **save/download images** for timelines. Outputs are a single timestamp for one URL or an HTML/TXT timeline for a list, with **timezone, date, and clock format configurable**. (see [GitHub](https://github.com/Lucksi/LinkdTime)).
It accepts either:\ • **A single LinkedIn URL** – e.g. `https://www.linkedin.com/feed/update/urn:li:activity:...` or a comment permalink – and prints the precise UTC time the action occurred;\ • **A text file of many URLs** – one per line – and builds a chronological **HTML or TXT timeline**. Use `--save` to embed images as [Base64](https://en.wikipedia.org/wiki/Base64) inside the HTML or `--download` to save originals alongside it. **Example use case** > An analyst harvesting every post- and comment-URL authored by a suspected astroturf network feeds them to LinkdTime. The generated timeline shows that “independent” accounts replied within 90 seconds of each post – a pattern typical of centrally scripted campaigns. [Astroturfing explained](https://en.wikipedia.org/wiki/Astroturfing) ## Typical Workflow ``` # Installation git clone https://github.com/Lucksi/LinkdTime && cd LinkdTime # Run (interactive) python3 main.py # At the prompt, paste ONE of the following: # A) Single URL → print timestamp https://www.linkedin.com/feed/update/urn:li:activity:1234567890123456789/ # B) Build timeline from file (one URL per line) timeline links.txt --autoname --description --timezone GMT+0:00 # Optional (timeline only): # --save # embed images as base64 into HTML # --download # save original images to disk (also controlled by AUTO-DOWNLOAD config) ``` The script [returns ](https://github.com/Lucksi/LinkdTime)either a single timestamp or a full HTML / TXT timeline (optional embedded images or Base64). Investigators can therefore spot coordination patterns, for example, discovering that replies labelled “organic” landed within minutes of each other. The tool prints either one [ISO 8601](https://www.iso.org/iso-8601-date-and-time-format.html) timestamp or writes `timeline.html` / `timeline.txt`. Investigators can visualise coordination, e.g. *five “organic” replies* landing **< 3 min** after a post may indicate **astroturfing** (see definition above). ## Cost * [x] Free * [ ] Partially Free * [ ] Paid Open-source under the GPL-3.0 licence; no paid tier ([GitHub](https://github.com/Lucksi/LinkdTime)). ## Level of difficulty
3
## Requirements * Linux with Python 3 (officially tested; **MacOS & Windows may work but are untested, Jul 2025**). * [Git installed](https://docs.github.com/en/repositories/creating-and-managing-repositories/cloning-a-repository) * Target URLs must be viewable without signing in. LinkdTime does **not** bypass LinkedIn log-in walls. ## Limitations * Untested on Windows or macOS, manual tweaks may be necessary; * Breaks if LinkedIn changes its HTML structure (pure scraping); * Cannot access content behind the login wall or private-visibility posts; * Heavy, rapid queries may trigger LinkedIn's anti-bot defences; use rate-limiting or rotating proxies; * No graphical interface, terminal only. * LinkedIn deploys rate-limits, CAPTCHAs and UA/velocity-based WAF rules against automated scraping. Plan pauses or proxy rotation. See LinkedIn’s own note on [anti-scraping defences](https://www.linkedin.com/blog/member/trust-and-safety/linkedin-safety-series-what-is-scraping). * Timestamp extraction depends on LinkedIn URL patterns and the numeric ID encoding scheme (not HTML scraping). * LinkdTime doesn’t log in; it can’t fetch private content. Image download features only work if the media URL is accessible and may trigger anti-bot controls if used at scale. ## Ethical Considerations * Scraping LinkedIn may violate its [terms of service](https://www.linkedin.com/legal/user-agreement); check your legal context before large-scale use. * LinkdTime extracts only information already **publicly visible**; nevertheless, assembling complete timelines can expose behavioural or work-pattern insights that the subject did not expect to be profiled. ## Guides and articles * “A LinkedIn Activity Date Finder – LinkdTime” – creator’s announcement on LinkedIn (Mar 2025, [LinkedIn](https://www.linkedin.com/posts/lucksi_github-lucksilinkdtime-a-linkedin-activity-activity-7297196149533216770-gXnx?utm_source=chatgpt.com)). * Featured in *OSINT Newsletter 67* – tool showcase with workflow tips (Apr 2025, [X (formerly Twitter)](https://twitter.com/osintnewsletter/status/1910012947725689196?utm_source=chatgpt.com). * Anti-scraping policy – [LinkedIn Safety Series](https://www.linkedin.com/blog/member/trust-and-safety/linkedin-safety-series-what-is-scraping). ## Tool provider • **Developer:** Luca Garofalo (**Lucksi**) – GitHub profile and repository. [GitHub](https://github.com/Lucksi?utm_source=chatgpt.com)\ • **License:** **GPL‑3.0** (see LICENSE in repo). [GitHub](https://github.com/Lucksi/LinkdTime) ## Similar tools | Tool | Strength | Weakness | | ------------------------------------------------------------------------------------------------------------------------------------------------------------------ | ---------------------------------------------- | -------------------------------------- | | [**LinkdTime**](https://github.com/Lucksi/LinkdTime) | Precise timestamps, bulk timeline, open-source | Linux-only; breaks if LinkedIn changes | | [**OSINT-Switzerland LinkedIn script**](https://www.linkedin.com/posts/osint-switzerland_having-recently-learned-the-technique-activity-7296041731815362560-rsk0/) | Exports post IDs fast | No timeline output; limited to posts | | [**Wayback Machine**](https://bellingcat.gitbook.io/toolkit/more/all-tools/internet-archive) | Full historical snapshots | No post times; manual link lookup | ## Advertising Trackers * [ ] This tool has not been checked for advertising trackers yet. * [ ] This tool uses tracking cookies. Use with caution. * [x] This tool does not appear to use tracking cookies. | Page maintainer | | --------------- | | Martin Sona | --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://bellingcat.gitbook.io/toolkit/more/all-tools/linkdtime.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.