What are the best practices for testing programming languages against denial of service attacks?

External DoS attacks are orthogonal to programming languages and are usually handled by network layers way before it reaches the application logic. Self-inflicted DoS attacks are a different topic and often orthogonal as well to the language used. For example you can issue a SQL Query of Death in Python or Rust and nothing in the language can prevent you from inflicting self harm. Last but not least, keeping the code that handles the requests lean is also very important. I've seen an API Gateway written in Spring Boot that, under constrained resources, would take O(minutes) to start up. The same simple gateway re-written in Go an Rust would start in sub-seconds and be 20x (Go) to 40x (Rust) more efficient in CPU/RAM usage.

Considero que un ataque de DoS o DDoS, puede ser realizado a cualquier aplicación sin importar su lenguaje, algunos están optimizados para gestionar mejor la carga y el tráfico, en ese aspecto los lenguajes compilados generan un mayor rendimiento que los lenguajes interpretados, sin embargo no debería ser un limitante su uso, ya que existen arquitecturas de seguridad, que permiten gestionar y controlar este tipo de ataques. Dicho esto, si son importantes las pruebas de carga que se puedan realizar a los desarrollos, y mejor aún si las pruebas pueden ser integradas en un proceso de DevSecOps, ya que va a garantizar que nuestros desarrollos cumplen con los criterios mínimos de seguridad e identificar posibles problemas.

In my experience,Select a programming language with built-in security features and robustness against DoS attacks. Languages like Rust, Go, and Java have features that make them less susceptible to certain types of attacks.

To defend against DoS attacks: - Research vulnerabilities in your tech stack. - Implement rate limiting for APIs/endpoints. - Utilize security scanning tools like OWASP ZAP. - Conduct stress tests with tools such as Apache JMeter. - Use static code analysis for vulnerability detection, e.g., SonarQube. - Perform penetration testing against DoS attack methods. - Regularly update and secure application dependencies. - Ensure robust error handling mechanisms. This streamlined approach boosts resilience against DoS attacks by emphasizing continuous updates and awareness of new threats.

Apart from stress testing, practicing SDLC code reviews and secure coding practices to identify and address potential vulnerabilities in the application code including the logic. We cannot compromise security sensitive areas such as taking user inputs, authentication, and authorization, especially with financial transactions

Employ specialized testing tools designed for assessing the resilience of systems against DoS attacks. Tools like Apache JMeter, OWASP ZAP, and Siege can help simulate various types of attacks and measure system performance under stress.

Un conjunto de herramientas de pruebas es muy importante para detectar posibles problemas de rendimiento en las aplicaciones, una buena estrategia de pruebas automatizadas que permitan identificar, cuellos de botella, desperdicio de recursos CPU o RAM y malas implementaciones en los algoritmos, va a garantizar que no seamos víctimas de ataques mal intencionados que puedan afectar la continuidad del negocio. Herramientas como JMeter, Gatling, LoadRunner o NeoLoad ya se han convertido en estándar de la industria, si estas herramientas se las puede vincular a un pipeline de pruebas la confianza en el desarrollo, va a mejorar día a día.

I would suggest implementing protocol breaks and even architecture breaks. Use a different systems architecture for your server infrastructure and client devices for example. And - obvious one - do not skip an API gateway. They are there for a reason. Finally keeping stats on your regular traffic to detect unexpected behaviour can really help as well.

Como había mencionado las arquitecturas de seguridad juegan un papel vital para prevenir ataques DoS o DDoS, primero tener un WAF o CDN en el borde que permita controlar y bloquear todo el tráfico global para enrutarlo lo más filtrado a nuestras aplicaciones, luego implementar un API Gateway y Firewall para contrarrestar posibles solicitudes a servicios que quieran minar los recursos. La seguridad se implementa en líneas de defensa, estas deben ser colocadas de forma estratégica para mitigar los posibles riesgos y prevenir posibles ataques, mientras más crítico es el servicio se van a necesitar más líneas de defensa, por tal motivo es importante analizar bien la arquitectura para evitar que esto impacte en el beneficio de la empresa.

Utilize security best practices in your code, such as input validation, rate limiting, and resource throttling, to mitigate the impact of potential DoS attacks. Implementing proper authentication mechanisms and access controls can also help prevent unauthorized access and abuse.

Set up monitoring systems to detect unusual patterns in traffic or system behavior that may indicate a DoS attack. Analyze system logs and metrics regularly to identify potential vulnerabilities or performance bottlenecks that could be exploited by attackers.

Benchmarking and Metrics for Performance Evaluation: Conduct benchmark tests to measure the performance, scalability, and resource utilization of your application under varying loads. Define key metrics such as response time, throughput, and CPU/memory usage to assess performance benchmarks. Example: In the implementation of our fraud detection system, we conducted load tests using tools like Apache JMeter to simulate high traffic scenarios. By analyzing metrics such as response time and error rates, we could determine the system's resilience to DoS attacks and identify potential performance bottlenecks.

Keep your programming language, frameworks, libraries, and dependencies up to date with the latest security patches and updates. Vulnerabilities in software components can be exploited by attackers to launch DoS attacks, so maintaining a secure codebase is essential for mitigating risks.

Using tools like GitHub's Dependabot and CodeQL scanning tools would certainly contribute to better security as well. Additionally, using such tools would put you in a better defense position in case a vulnerability is ever actively abused and results in claims for damages. Remember that security is one, but covering your bases in terms of liability is two.

Dentro de la arquitectura de seguridad se debe contar con Web Application Firewall de borde para proteger las aplicaciones contras ataques DDOS con capacidades de antibot para proteger además las zonas de la infraestructura y garantizar la calidad dé tráfico ademas de un API Protection al implementar un API Gateway y Firewall para proteger las solicitudes a servicios hacia los recursos. Esta arquitectura debe ser capaz de integrarse a las diferentes nubes donde se encuentran alojadas las aplicaciones y tener la capacidad de integracion con SIEM. Ademas de contar con workers para tomar acciones en tiempo real en caso de ataques.

Additionally, conducting regular security assessments and staying informed about emerging threats can further strengthen the resilience of systems against potential attacks.

Tambien podemos utilizar herramientas y marcos de Python,como Scapy, Nmap, Pytbull y PyLoris, que pueden ayudar a realizar pruebas depenetración y simulación de ataques DoS y DDoS

Who tests programming languages against DOS? Application developers can write logic to dos the system themselves but even in those senerios you shouldn’t be testing programming languages, unless you are building a language.