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Instagram OSiNT

NetworkChuck·
5 min read

Based on NetworkChuck's video on YouTube. If you like this content, support the original creators by watching, liking and subscribing to their content.

TL;DR

Oscentgram is a command-line Python OSINT tool that can collect publicly available Instagram data such as stories and profile images without password theft.

Briefing

A command-line OSINT tool called “oscentgram” can pull publicly available information tied to an Instagram account—stories, profile images, hashtags, commenters, and even metadata like emails of people the target follows—without breaking into accounts or stealing passwords. The practical takeaway is that investigators (and curious users) can automate parts of Instagram research using a Python workflow, then review the downloaded artifacts locally.

The walkthrough starts with the ethical boundary: don’t hack accounts without permission, even if the data is publicly accessible. From there, it lays out the setup for running the tool on a Linux environment. Users can either use a free Google Cloud Console instance or run their own Debian-based virtual machine, with Kali Linux demonstrated. The tool is cloned from GitHub, then installed with Python 3 (at least 3.6) and pip3, followed by installing dependencies from a requirements.txt file.

Configuration requires a “dummy” Instagram account. The script uses a username and password stored in local config files (username.conf, pw.conf, and settings.json). After creating a config directory and populating those files, the user runs main.py with the target Instagram username. Once logged in, the tool provides a command set that can download the target’s stories and profile picture, and it can also enumerate related data such as hashtags and people who comment on the target’s posts.

The most striking results come from commands that attempt to enrich the target’s footprint. One command retrieves emails of users followed by the target; the transcript shows examples like Casey Neistat (no email returned) and Peter McKinnon (email returned), plus other accounts with email addresses visible. Another command tries to gather registered addresses for photos associated with the target’s posts. That part is slower and can trigger throttling—an error message asks the user to wait and try again—so the workflow may require patience, rate-limit handling, or switching environments.

When the address-collection command misbehaved, the operator switched to Google Cloud Console and used another account, after which the tool successfully returned locations tied to Instagram posts the target was tagged in. The session emphasizes that the tool works “most of the time,” but reliability can vary depending on rate limits and account behavior.

The closing challenge turns the OSINT skills into a test: viewers are asked to determine where the operator was on September 2, 2018, with the hint that it isn’t on his Instagram account. The intended lesson is that OSINT is often about correlating public traces—photos, tags, and metadata—rather than exploiting vulnerabilities. The transcript also notes that other tools exist, but this one is favored for its command-line workflow and speed when it functions.

Cornell Notes

The transcript demonstrates “oscentgram,” a Python-based OSINT tool that automates collection of publicly available information from an Instagram account. After setting up a Debian-based Linux environment (Kali Linux shown) and installing dependencies, users configure the script with a separate dummy Instagram login. Running main.py with a target username enables downloads of stories and profile images and can return related data such as commenters and hashtags. Some commands attempt to extract emails from accounts the target follows and to collect location/address data tied to posts, though rate limits can cause throttling. The practical value is learning how to turn Instagram’s public footprint into structured, downloadable evidence without password theft.

What is oscentgram, and what kinds of Instagram data does it retrieve?

Oscentgram is a Python OSINT tool run from the command line. After logging in with a dummy Instagram account, it can download the target’s stories and profile picture, and it can list related items such as hashtags and people who comment on the target’s posts. The transcript also shows commands that attempt to extract emails of users followed by the target and to collect registered addresses/locations associated with photos tied to the target’s posts.

Why does the setup require a dummy Instagram account?

The script uses a username and password to authenticate for the data-collection steps. The transcript explicitly recommends using a separate dummy account rather than the operator’s main account, then storing credentials in local config files (username.conf and pw.conf) plus settings.json. This reduces the risk of exposing a personal account while running automated queries.

How does the tool get installed and run on Linux?

The workflow shown is: clone the repository with git clone, ensure Python 3 is installed (at least 3.6; Python 3.9 is installed in the transcript), install pip3, then install dependencies via pip3 install -r requirements.txt. A config directory is created (config), credentials are written into files, and the script is executed with python3 main.py followed by the target Instagram username.

What evidence-enrichment commands appear in the transcript, and what results do they produce?

One command retrieves emails of users followed by the target (shown with examples: Casey Neistat returns no email, while Peter McKinnon returns email; other accounts also show email addresses). Another command attempts to collect registered addresses for target photos, but it can trigger throttling (“please wait a few minutes”). After switching to Google Cloud Console and using another account, the transcript reports success in obtaining locations tied to posts where the target was tagged.

What reliability problem occurs, and how is it handled?

The transcript reports throttling when running the address/location-related command, with an error instructing the user to wait and try again. The operator responds by making more coffee, retrying, and then switching to Google Cloud Console to get the command working. The transcript also notes using another account to proceed when the original approach stayed unreliable.

Review Questions

  1. What steps are required to configure and run oscentgram, and why does the transcript insist on using a dummy Instagram account?
  2. Which oscentgram commands in the transcript produce downloaded media (stories/profile picture) versus enriched data (emails/locations), and what limitations appear for the enriched-data commands?
  3. How did the operator respond when throttling prevented the address/location collection from working reliably?

Key Points

  1. 1

    Oscentgram is a command-line Python OSINT tool that can collect publicly available Instagram data such as stories and profile images without password theft.

  2. 2

    Running the tool requires a Debian-based Linux environment with Python 3 and pip3, plus dependencies installed from requirements.txt.

  3. 3

    Configuration depends on a dummy Instagram account; credentials are stored locally in config files used by the script.

  4. 4

    Executing main.py with a target username enables a command set that can download media and enumerate related account activity like commenters and hashtags.

  5. 5

    Some enrichment commands attempt to extract emails from accounts the target follows, but results vary by account.

  6. 6

    Location/address collection can trigger throttling; retries, account changes, and switching to Google Cloud Console may be needed.

  7. 7

    The transcript ends with an OSINT challenge: determine a specific real-world location tied to a date, using public traces rather than the operator’s Instagram account.

Highlights

Oscentgram can download an Instagram target’s stories and profile picture through automated OSINT commands, storing the results in an output directory.
A command that pulls emails from accounts followed by the target produced mixed results—some accounts returned emails while others did not.
Address/location collection was prone to throttling; switching to Google Cloud Console and using another account helped the operator get location data.
The exercise reframes “Instagram hacking” as OSINT correlation—finding real-world context from public metadata and tags rather than breaking into accounts.

Topics

  • Instagram OSINT
  • oscentgram setup
  • Linux Kali
  • Python automation
  • metadata extraction