What is a DDoS attack example?

A DDoS attack, or Distributed Denial of Service attack, is a malicious attempt to disrupt normal traffic of a targeted server, service or network by overwhelming it with a flood of internet traffic. DDoS attacks accomplish this by leveraging multiple compromised computer systems as sources of attack traffic. Victims of DDoS attacks often target web servers of high profile organizations such as financial institutions, ecommerce sites, and government agencies. These attacks are often carried out by botnets – networks of compromised computers controlled by a cybercriminal.

What are the main types of DDoS attacks?

There are several main types of DDoS attacks:

  • Volume-based attacks – This type attempts to saturate the bandwidth of the target with high volumes of traffic. Examples include UDP floods, ICMP floods, and other spoofed-packet floods.
  • Protocol attacks – These attacks send malformated packets to target vulnerabilities in network protocols like TCP or HTTP. Examples are SYN floods, Ping of Death, and more.
  • Application layer attacks – These target web application vulnerabilities by exhausting resources on the target server. Examples include HTTP request floods, Slowloris, etc.
  • Advanced Persistent DDoS (APDoS) – A more sophisticated variant that sends attacks at varying rates and targets to circumvent DDoS protections.

What are the main DDoS attack tools?

Cybercriminals often rely on a range of DDoS tools and botnets to carry out largescale attacks. Some of the main ones include:

  • LOIC – The Low Orbit Ion Cannon is a popular open-source network stress tool often used for DDoS.
  • HOIC – The High Orbit Ion Cannon is an updated version of LOIC that allows controlling many LOIC instances from a master control server.
  • Trin00 – A DDoS botnet tool using a client/server architecture. It infects computers via security flaws and can be controlled remotely by attackers.
  • PhantomNet – A sophisticated botnet capable of launching DDoS attacks via TCP, UDP, or HTTP using encrypted command and control communications.
  • MRQ – A malware DDoS tool that can rapidly spread to vulnerable Windows machines and overwhelm targets with UDP and TCP floods.

What are some major DDoS attacks?

Some of the largest and most disruptive DDoS attacks in history include:

  • Mirai Botnet Attacks (2016) – The Mirai botnet infected over 600,000 IoT devices and took down major sites like Twitter, Spotify, GitHub, and more with massive 620 Gbps DDoS attacks.
  • Spamhaus Attacks (2013) – CyberBunker launched 300 Gbps DDoS attacks on the anti-spam group’s network servers, disrupting services.
  • Dyn Cyberattack (2016) – Unidentified attackers used the Mirai botnet to execute 1.2 Tbps attacks on DNS provider Dyn, causing outages to major sites like Twitter and Netflix.
  • Github Attack (2015) – Github servers were slammed with a massive 1.35 Tbps DDoS that was mitigated with assistance from Akamai Prolexic.
  • DDoSForHire Attacks (2017-2018) – Webstresser.org DDoS-for-hire service enabled over 136,000 attacks on banks, government institutions, and many other organizations.

What are the warning signs of being targeted by a DDoS attack?

Possible signs that your organization may be being targeted by an impending DDoS attack include:

  • Sudden spikes in traffic and activity from unusual locations, sources, or countries.
  • Inability to access your website or network resources.
  • Sluggish network performance, slow page loads, and timeout issues.
  • Failed login attempts and other activity indicating reconnaissance.
  • Suspicious registry edits or network mapping tools being used against you.
  • Increased activity on forums related to hacking or DDoS attacks.
  • Concerning communication or threats indicating an impending attack.

What are common DDoS attack prevention best practices?

Effective ways to improve DDoS attack prevention include:

  • Using DDoS mitigation services to divert and filter attack traffic before it hits your network.
  • Overprovisioning bandwidth and building in redundancy to better withstand large traffic floods.
  • Quickly patching vulnerabilities in Internet-facing systems that could be exploited.
  • Limiting overly permissive protocols like misconfigured NTP and SNMP that amplify DDoS attacks.
  • Blocking traffic from unused IP address ranges to reduce scope for spoofing.
  • Enabling SYN cookies, increasing socket buffers, and taking other steps to handle protocol attack types.
  • Using CDNs and caching to efficiently handle large surges in traffic volumes.

It’s also critical to have DDoS response playbooks in place outlining steps to quickly mitigate ongoing attacks across networking, security, operations, and management.

How can you trace the source of a DDoS attack?

Tracing a DDoS attack back to its source can be challenging, but methods include:

  • Analyzing web server, firewall, and other log files for IP addresses, signatures, and traffic patterns.
  • Working with your ISP to trace attack traffic through upstream providers and backbone networks.
  • Obtaining court orders to get records and trace IPs from the platforms used to launch attacks.
  • Setting traps and honeypots to lure attackers and gather forensic data.
  • Using packet capture tools to inspect packets, extract headers, and trace them upstream.
  • Tracing botnet C&C servers and working with global law enforcement to identify culprits.

However, sophisticated attackers often employ IP spoofing, compromised computers, and multi-stage traffic forwarding to cover their tracks. Cooperating with other network owners can help piece together parts of the attack path.

What are common penalties for DDoS attacks?

Legal penalties for executing illegal DDoS attacks can include:

  • Years of imprisonment under the Computer Fraud and Abuse Act.
  • Damages claims by victims impacted by the attack.
  • In the U.S., up to 10 years imprisonment under anti-hacking laws.
  • Fines and other civil penalties imposed by regulators.
  • More severe criminal charges depending on if sensitive data was also compromised.

DDoS-for-hire operators also increasingly face prosecution. Penalties get much harsher for repeat offenders.

What are important DDoS attack defense steps for enterprises?

Larger enterprises and organizations should take these steps to defend against DDoS attacks:

  1. Deploy intelligent DDoS mitigation solutions capable of absorbing massive attack volumes.
  2. Build in redundancy across networks, data centers, DNS, and other infrastructure.
  3. Tune detection thresholds to identify abnormal traffic spikes rapidly.
  4. Validate capacity to handle cache misses, retries, failures, and other side effects of large floods.
  5. Proactively monitor the global threat landscape and attack tool chatter to anticipate new attack vectors.
  6. Test DDoS response plans via simulations, table-top exercises, and drills.
  7. Maintain relationships with upstream providers, law enforcement, and industry partnerships capable of providing DDoS assistance.

Having both preventative defenses and detailed response plans in place is essential to mitigating risks from today’s powerful DDoS attacks.

How can cloud-based services help stop DDoS attacks?

Cloud-based DDoS protection services provide several advantages for mitigating the impact of DDoS attacks:

  • Absorbing attacks with massive bandwidth across globally distributed networks.
  • Filtering traffic through anycast routing, scrubbing centers, and Edge locations for greater resilience.
  • Scaling on demand to handle sudden traffic spikes.
  • Advanced analytics using machine learning techniques to detect anomalous traffic.
  • Easy integration, automation, and unified policy management across on-prem and cloud infrastructures.

By leveraging the scale and intelligent protections of the cloud, these services can eliminate more attack traffic closer to the source before it reaches your network perimeter.

What role does machine learning play in combating DDoS attacks?

Machine learning has emerged as an important tool for detecting DDoS attacks more quickly and accurately by:

  • Rapidly analyzing traffic patterns to detect anomalies indicative of DDoS floods.
  • Learning baseline traffic profiles for users, devices, and networks to identify abnormal behavior.
  • Adapting to changing attack strategies as algorithms self-train on new samples of malicious traffic.
  • Correlating across many signals – IP reputation, geolocations, rate of requests, etc – to uncover attacks using multiple dimensions of data.
  • Automating rapid, scalable responses tailored to block current attacks.

ML reduces reliance on manual rules and thresholds by training predictive models capable of understanding complex attacks. This enables faster, more adaptive DDoS defenses.

How can web applications be designed to better withstand DDoS attacks?

Steps developers can take to build more DDoS-resilient web applications include:

  • Implementing rate limiting protections against excessive requests from a single IP or subnet.
  • Using caching and CDNs to offload work and minimize resource strain during traffic floods.
  • Designing loosely coupled components that fail gracefully to prevent cascading service failures.
  • Streamlining processes to minimize CPU-intensive transactions requiring heavy processing.
  • Enabling easy scaling of app resources to quickly allocate more capacity under attack.
  • Optimizing expensive database queries, reports, and other functions.
  • Using IP reputation data to block known bad actors.

Building DDoS survivability into apps from initial design through testing and production deployment cycles pays dividends when attacks strike.


As one of the most potent forms of cyber attacks today, DDoS attacks represent a constant threat to organizations across industries. From simple volumetric floods to sophisticated botnet assaults, these attacks aim to overwhelm networks and infrastructure with a tsunami of malicious traffic. By leveraging the latest protective solutions, following security best practices, and building robust incident response plans, companies can become more resilient in withstanding the disruption caused by DDoS attacks.