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Introduction:
Open-source intelligence (OSINT) has become a cornerstone of modern cybersecurity investigations, threat actor attribution, and digital forensics. The newly released X Bookmarklet by My OSINT Training condenses minutes of manual data gathering into a single click, automatically pulling a Twitter/X profile’s creation date, total username changes, and even banner upload timestamps. While this tool dramatically accelerates investigator workflows, understanding how it works under the hood—and replicating those techniques with verified command-line tools—empowers defenders and analysts to conduct more stealthy, auditable intelligence gathering.
Learning Objectives:
- Deploy and use the X Bookmarklet to instantly extract comprehensive profile metadata from any public Twitter/X account.
- Reproduce the bookmarklet’s extraction capabilities using Linux command-line tools (curl, jq, grep) and Windows PowerShell for scripted OSINT.
- Harden your investigative environment with cloud security configurations to prevent attribution and data leakage during sensitive research.
You Should Know:
- Installing the X Bookmarklet and Capturing Profile Intelligence
The bookmarklet is a piece of JavaScript saved as a browser bookmark. When clicked while viewing a Twitter/X profile page, it scrapes the DOM and background API responses to harvest 10 data points, includingrest_id,screen_name,created_at,updated_username_at,number_of_username_changes, andprofile_banner_upload_ts.
Step-by-step guide:
- Visit `https://tools.myosint.training` and locate the X Bookmarklet link.
- Drag the provided JavaScript link to your bookmarks bar, or right-click and select “Bookmark This Link.”
- Navigate to any public Twitter/X profile (e.g., `https://x.com/example`).
- Click the bookmarklet. A formatted overlay will display all extracted fields, which you can copy as JSON.
- Use browser Developer Tools (F12) → Console to verify the underlying GraphQL queries the bookmarklet interfaces with.
Why it matters: This tool provides rapid historical username change data, which is crucial for tracking account evolution across forums and marketplaces.
- Manual OSINT via Linux: Extracting Twitter User Data with curl & jq
Before automated bookmarklets, analysts used Twitter’s API or scraped public endpoints. Using a Bearer Token from a developer account, you can query the `users/by/username/:username` endpoint to fetchrest_id, then pull full profile details.
Linux commands (requires a valid `$BEARER_TOKEN`):
USERNAME="elonmusk" Get user ID USER_JSON=$(curl -s "https://api.twitter.com/2/users/by/username/$USERNAME" \ -H "Authorization: Bearer $BEARER_TOKEN") USER_ID=$(echo "$USER_JSON" | jq -r '.data.id') Fetch user details (creation date, pinned tweet, etc.) curl -s "https://api.twitter.com/2/users/$USER_ID?user.fields=created_at,profile_image_url,public_metrics" \ -H "Authorization: Bearer $BEARER_TOKEN" | jq .
To fetch banner upload time, use the v1.1 endpoint `users/show.json` which returns profile_banner_url; the upload date is often embedded in the media URL or accessible via HTTP headers:
BANNER_URL=$(curl -s "https://api.twitter.com/1.1/users/show.json?screen_name=$USERNAME" \ -H "Authorization: Bearer $BEARER_TOKEN" | jq -r '.profile_banner_url') curl -sI "$BANNER_URL" | grep -i "last-modified"
3. Windows PowerShell for Agentless OSINT Gathering
On Windows, you can replicate similar scrapes using `Invoke-WebRequest` and parse HTML since many profile data points are embedded in `meta` tags or JSON-LD structs.
PowerShell snippet to grab username, name, creation date from a public page:
$url = "https://twitter.com/example" $response = Invoke-WebRequest -Uri $url -UseBasicParsing Extract embedded JSON-LD $json = ($response.Content -split '<script type="application/ld\+json">')[bash] -split '</script>' | ConvertFrom-Json Write-Host "Name: $($json.author.name)" Write-Host "Identifier: $($json.author.identifier)" Parse creation date from data attributes $createdAt = [bash]::Match($response.Content, 'data-created-at="([^"]+)"').Groups[bash].Value Write-Host "Account Created: $createdAt"
For total username changes, note that Twitter/X shows this only in the “More” menu after login; automated scraping without authentication is limited. The bookmarklet leverages guest tokens to access that data.
4. Hardening Your Cloud Investigation VM
When performing OSINT on sensitive targets, you must isolate the investigative workstation to avoid IP leaks or browser fingerprinting. Deploy a disposable cloud VM with strict firewall rules.
Linux hardening commands (Ubuntu 22.04):
Allow only outbound HTTP/HTTPS for research sudo ufw default deny incoming sudo ufw default allow outgoing sudo ufw allow out 80,443/tcp sudo ufw enable Disable IPv6 to prevent tunnelling leaks sudo sysctl -w net.ipv6.conf.all.disable_ipv6=1 sudo sysctl -w net.ipv6.conf.default.disable_ipv6=1 Use a non-root user with MFA sudo apt install libpam-google-authenticator -y google-authenticator
Windows (Azure VM) hardening:
Set-NetFirewallProfile -Profile Domain,Public,Private -DefaultInboundAction Block Set-NetFirewallProfile -Profile Domain,Public,Private -DefaultOutboundAction Allow New-NetFirewallRule -DisplayName "Block All Inbound" -Direction Inbound -Action Block Enable Windows Defender Exploit Guard Set-MpPreference -EnableNetworkProtection Enabled
- Exploiting Exposed Data: How Attackers Use Profile Metadata for Spear Phishing
The extracted data—especially `account_creation_date` andlast_username_change—can be weaponized. An attacker can craft convincing lures referencing the exact month an account was opened, or impersonate a recently modified handle. A common exploitation technique involves cross-referencing the banner image metadata for physical location clues.
MITRE ATT&CK Technique T1598 (Phishing for Information):
- Query `profile_banner_upload_ts` to learn active hours.
- Use EXIF viewers on banner download (if not stripped) to obtain camera details:
exiftool downloaded_banner.jpg
Mitigation: As a defender, disable direct profile banner access via API settings and regularly audit your public metadata exposure using the bookmarklet’s output. Apply Twitter’s Privacy and Safety settings to limit visibility.
- Building a Custom OSINT Dashboard with the Twitter API
For large-scale investigations, you can pipeline bookmarklet-equivalent data into Elasticsearch. A Python script using Tweepy can collect and compare historical snapshots of target profiles.
import tweepy, json, time
client = tweepy.Client(bearer_token='YOUR_TOKEN')
user = client.get_user(username='target', user_fields=['created_at','profile_image_url'])
data = user.data
print(f"User created: {data['created_at']}")
To log username changes, you'd need the (limited) compliance firehose or scraped history.
Store results in CSV for timeline analysis: echo "timestamp,username_changes" >> osint_log.csv.
- The Certified Dark Intelligence Analyst (CDIA) and Legal Boundaries
The sponsoring course, Certified Dark Intelligence Analyst (CDIA), is closing enrollment on May 3, 2026 (`https://lnkd.in/dwppxH9k`). Such certifications emphasize the ethical use of tools like the X Bookmarklet—understanding that extracting data from public profiles is legal, but combining it with compromised databases or breaching platform ToS is not. Future OSINT professionals will be expected to sign attestations of responsible use, especially with AI-driven aggregation tools on the horizon.
What Undercode Say:
- The X Bookmarklet shatters the manual drag of OSINT, but every investigator should know the underlying API calls to validate its output.
- Combining simple Linux curl chains with jq gives the same results without relying on third-party JavaScript—crucial for air-gapped or high-security environments.
- Public data exposure is irreversible; the username change history reveals repurposed accounts that threat actors often weaponize for credibility.
- Hardening your research VM is not optional; the same techniques used for reconnaissance can be turned against the investigator.
- Tools like this will evolve into real-time AI dashboards that predict account takeover likelihood based on change velocity and profile inconsistencies.
Prediction:
Within two years, AI-powered OSINT platforms will automatically correlate Twitter/X metadata fields with dark web dumps and leaked databases, producing immediate risk scores for brand impersonation and insider threats. This will force platforms to re-architect what data is considered “public,” possibly obfuscating creation timestamps or username change counts to protect users. Meanwhile, law enforcement and threat intel teams will increasingly adopt single-click enrichment scripts embedded directly into their case management systems, making the bookmarklet’s one-click philosophy the standard for frontline cyber investigations.
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