40 Crore Cyberattacks on NSE: Technical Analysis of Operation Sindoor
During the peak of Operation Sindoor in May 2025, India’s National Stock Exchange (NSE) reportedly faced nearly 400 million cyberattack attempts in a single day. The number made headlines. But what does “40 crore cyberattacks” actually mean in technical terms?
This post breaks it down — layer by layer, signal vs noise — the way a SOC analyst or defender should interpret it.
The Context: What Was Confirmed
NSE CEO Ashish Chauhan stated that:
- ~40 crore attack attempts were observed during peak geopolitical tension
- Normal daily hostile activity is already ~15–17 crore events
- No trading halt, data breach, or operational impact occurred
This alone tells us something important:
This was not a successful intrusion story. This was a scale and resilience story.
Breaking Down the “Attacks” — What Actually Hit the Infrastructure
Large institutions like stock exchanges don’t get “hacked” in one clean move. They get bombarded continuously. Let’s break down the categories of activity that inflate numbers into the hundreds of millions.
🌐 Network-Layer Activity (L3 / L4)
These events never touch applications or logins. They target network protocols themselves.
High-Rate SYN Floods
What it is: Attackers send massive volumes of TCP connection requests (SYN packets) but never complete the handshake.
Why it matters: Each half-open connection consumes memory and processing power.
Why it’s expected: SYN floods are one of the oldest and loudest denial techniques. Modern firewalls, load balancers, and DDoS scrubbing services detect and neutralize them quickly.
Malformed Packets
What it is: Network packets that violate protocol standards.
Purpose:
- Trigger crashes in poorly written network stacks
- Test for unpatched edge devices
- Confuse shallow packet inspection
Reality: Mostly ineffective against mature infrastructure — but still heavily used in automated scanning.
Volumetric DDoS (Layer 3 / Layer 4)
What it is: Raw traffic volume designed to overwhelm bandwidth or network devices.
- L3: IP-based floods
- L4: TCP/UDP floods
Goal: Exhaust routers, firewalls, or upstream links — not to steal data.
Why exchanges survive it: Redundancy, Anycast routing, traffic shaping, and upstream mitigation.
Reflection / Amplification Noise
What it is: Attackers abuse open internet services (DNS, NTP, etc.) to amplify traffic toward a victim.
How it works:
- Small request sent with spoofed source IP
- Large response sent to the victim
Key point: Much of this traffic doesn’t originate from attackers directly — it’s collateral abuse of misconfigured infrastructure.
🔍 Application & API Probing
This is where attackers start interacting with software logic — not just pipes.
Automated Endpoint Discovery
What it is: Bots probing common paths like:
- /api
- /admin
- /v1
- /health
- /debug
Goal: Find undocumented, legacy, or forgotten interfaces.
Why NSE sees this constantly: Large digital surface + public services = endless probing.
Invalid API Calls
What it is: Requests with broken parameters, missing fields, or unexpected values.
Why attackers do it:
- Test input validation
- Trigger error disclosures
- Identify logic flaws
Parameter Fuzzing
What it is: Automated testing of API inputs using random, extreme, or malformed values.
Why it matters: Historically used to uncover:
- Crashes
- Logic bypasses
- Memory handling bugs
Reality today: Mostly blocked, but still generates massive event counts.
Abuse of Public Market Data Interfaces
What it is: Overuse or misuse of APIs meant for public price or market data.
Impact:
- Service strain
- Increased backend cost
- No data compromise
🔐 Authentication Abuse (Where Real Risk Begins)
Unlike network noise, these attempts try to become legitimate users.
Credential Stuffing
What it is: Replaying username-password pairs from past breaches.
Why it works: Password reuse.
Why it’s noisy: High failure rates, easily rate-limited.
Password Spraying
What it is: Trying one common password across many accounts.
Why it’s dangerous: Fewer failures per account → harder to detect.
Token Replay Attempts
What it is: Reusing stolen session tokens instead of logging in.
Why defenders worry:
- Bypasses passwords
- May bypass MFA
- Looks like valid traffic
Detection requires: Behavioral analytics, not just auth logs.
🤖 Internet Background Radiation (Amplified)
This is the constant global noise of the internet — not targeted hostility.
Botnet Scanning (Masscan-Style)
What it is: High-speed scanning of IP ranges looking for open ports or known services.
Important: Most bots don’t know or care who NSE is.
Opportunistic Exploitation Attempts
What it is: Trying known exploits everywhere, blindly.
Key point: These attacks succeed only when basic hygiene fails.
Final Analyst Verdict
“40 crore attacks” does not mean 40 crore successful intrusions.
It means:
- Massive automation
- Expected internet hostility
- Strong perimeter and response maturity
The uncomfortable truth:
- Most blocked attacks are loud and dumb
- Most damaging attacks are quiet and authenticated
NSE’s systems did what they were designed to do — absorb chaos without blinking.
Stay Alert. Stay Human. Stay Safe.
— ZyberWalls Research Team
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