In today’s technology-centric world, with modern web applications evolving rapidly, it can be hard to believe that legacy systems dating back to the telegraph continue to play a prevalent part in industries such as defense, aviation, maritime communication, and railway signaling. One such foundational technology is Morse code. By some, Morse Code is seen as outdated or useless; however, even in today’s technology-driven landscape, Morse Code is used within specific environments that have strict specifications for reliability, simplicity, and low-bandwidth communication.
If you’ve ever used a Morse code translator online to convert dots and dashes into letters, you’ve already brushed against the outer layer of a much deeper and technically rich domain. But how do we test those systems built using these old communication protocols? How do we secure and test them for reliability, especially when modern testing tools aren’t directly compatible with legacy standards?
This blog post will take a look at an obscure area of software QA: using protocol fuzzers for testing Morse code communication. It will cover why it is important to test Morse code communication, how to change fuzzing for legacy protocols, the main issues you can face, and how modern testing tools can still be applied to these older communication protocols.
Understanding Morse Code in the Modern Context
Morse code was created in the 1830s and 40s by Samuel Morse and Alfred Vail. It served as a method of communicating textual information over long distances by using sequences of dots and dashes that correspond to letters, numbers, and punctuation. The sequences were transmitted via telegraph wires or radio signals. Despite being created a long time ago, Morse code is enduring in the military and emergency services and is considered a low-resource form of communication that is still useful.
Today, Morse code isn’t just a historical curiosity. It continues to be used where:
- Signal clarity in poor conditions is vital.
- Voice communications aren’t usable.
- Backward compatibility is necessary with legacy systems.
However, because of its age and narrow focus, systems that process Morse code rarely undergo modern forms of stress testing or validation. That’s where fuzzing comes in.
What is Protocol Fuzzing?
Protocol fuzzing is a form of automated testing where you send malformed, unexpected, or random inputs to a communication system to uncover bugs, crashes, vulnerabilities, and odd behavior. Fuzzing does not have any assumption about the internals of the system being tested. Instead, fuzzing tests all potential permutations of a system, then looks at what happens.
Imagine pressing random buttons on a vintage radio system in various sequences to see if any of them break the system or reveal unexpected functionalities. That’s fuzzing in a nutshell—but done programmatically, repeatedly, and at scale.
Now apply that to Morse code. What happens when you feed a Morse code parser a sequence that isn’t valid or is ambiguously structured? What if signals come in at unexpected intervals? These are questions protocol fuzzers can help answer.
Why Fuzz Morse Code Systems?
When teams ask the first question, it is typically, “What is the point of testing something that has been stable for so long?”
Security Issues
Most legacy systems are often exempt from regular patching cycles. If it has never been fuzzed, it is possible that the parser is vulnerable to issues such as buffer overflows, crashes from malformed input, or worse, denial-of-service conditions.
Interoperability Assurance
A lot of Morse systems today navigate into the realm of today’s digital infrastructure. Fuzzing allows for validation so that unexpected input won’t interrupt and pass through the components of the system
Error Recovery Testing
If someone accidentally keys in an ambiguous message, can the system recover gracefully? Or does it crash?
Regulatory and Compliance Testing
In sectors like aviation or defense, certification often requires rigorous validation—even for legacy systems. Fuzzing is a way to validate behavior under non-ideal conditions.
Challenges in Fuzzing Legacy Morse Code Protocols
Modern fuzzers are designed with APIs, file parsers, or modern network protocols in mind. When you’re building fuzzers for Morse code systems, modern fuzzers expect us to send JSON or XML to a REST endpoint, not dots and dashes. This presents a few unique challenges.
Non-Binary Signal Encoding
Morse code is not binary in a modern sense. Morse code is temporal. The timing between beeps and the tone duration, as well as pauses, convey meaning. This means fuzzing requires accounting for timing as well as content.
Lack of Standard Parsers
There is no open-source or popular Morse code parsing engine; it is not as widespread as HTML or HTTP. Therefore, every system will depend on how they interpret each edge case differently, making it hard when generalizing fuzzing output.
Interface Complexity
Oftentimes legacy systems have physical interfaces to outputs, i.e., serial ports, audio input, and analog signals, which can make automation a non-negligible task.
Reproducibility
If fuzzing produces a failure due to unusual signal duration or ambiguous pause, reproducing that exact sequence of signals by hand or even programmatically is challenging without precision tools.
Constructing a Fuzzer for Morse Code Systems: A High-Level Overview
Here’s a simplified outline of how one might build a protocol fuzzer specifically for Morse code.
Step 1: Define the Input Space
First, understand valid Morse code: dot (.), dash (-), intra-character gaps, character gaps, and word gaps. Then define the deviations:
- Invalid character combinations (e.g., —…-.-)
- Timing errors
- Overlaps of signals
This input space defines what kind of malformed data the fuzzer will generate.
Step 2: Create Signal Generator
Develop a module that can take arbitrary input sequences and create signals that resemble Morse code created by a human. This includes timing, tones, and spacing.
You can think of this as a ‘malformed Morse translator.’
Step 3: Create Feedback Loop
The fuzzer will have to see how the target system reacts. Does it
- Crash?
- Misinterpret the message?
- Lockup?
- Produce error logs?
This feedback mechanism will guide the differing forms of malformed input the fuzzer will try to generate.
Step 4: Automate and Scale
Test thousands or even millions of test cases and use simulated environments to run these tests first if you can. Use statistical data to identify troubled areas.
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Drawing Parallels: Playwright vs Cypress in the World of Legacy Testing
Let’s switch gears for a moment. You may be familiar with Playwright vs Cypress, a common debate in the web testing space. Playwright has a well earned reputation for its power and flexibility across browsers and languages, while Cypress has a well documented reputation for its simplicity and local debugging speed.
What do these technologies have in common with Morse code fuzzers?
Test Abstraction
Both tools accomplish abstracting away a lot of complexity. Similarly, a well-built Morse fuzzer abstracts signal encoding, allowing testers to focus on the behavior of the system under test.
Observability
Cypress has a strong reputation for real-time observability, and Playwright produces extensive logs of actions and traces. A Morse fuzzer needs the same logs, timestamps, and behaviors captured.
Parallelization
Modern tools often run tests in parallel, and they do so in order to improve efficiency. The same applies to Morse testing—running fuzzed input sequences in multiple simulated channels boosts coverage.
CI/CD Integration
Modern testing tools integrate directly into CI/CD pipelines, and so can a Morse code fuzzer, verifying each firmware or parser change.
Modernizing the Legacy Testing Mindset
Many test teams that use modern frameworks and UIs exclusively focus on modern testing tools and frameworks. But there’s enormous value in adapting these lessons to legacy domains. For instance:
- Employ a test-first approach even with Electric Analog systems.
- Create coverage metrics—how much of the Morse alphabet and timing space have you fuzzed?
- Apply regression testing to store fuzz cases that triggered bugs and run them every cycle.
- Encourage developer empathy, capture how malformed inputs fail, and patterns to gracefully handle them.
The Ethical and Compliance Angle
Fuzzing a legacy system is not just a technical issue; it has ethical and regulatory consequences. Always get permission when you fuzz a system, and especially when the subject system is critical infrastructure. Fuzzing without permission can be interpreted as a cyberattack.
In addition, document your approach in detail so that if your testing results in failure, you will have traceability to what input failed and what you wanted to test.
Looking Ahead: The Future of Protocol Testing
As organizations become more modernized, legacy interface testing is often neglected—often until a reference failure point arrives. Testing systems that are using Morse code might feel like testing a relic of another time, but as long as it is being operated upon, it should have the same expectations of quality assurance as any contemporary current software.
The advent of AI, ML, and automated observability tools has unleashed an opportunity for our fuzzers to be smarter in the sense that these tools learn from their past failures, generate adaptive inputs, and prioritize the critical areas.
Just as Playwright and Cypress represent the future of web testing, we need tools that can represent the future of legacy system validation.
Conclusion
“Legacy” doesn’t mean obsolete—it means “time-tested” but not infallible. Morse code systems, while antiquated, are still in use as part of critical workflows in a number of industries. Ensuring their reliability and resilience through protocol fuzzing isn’t just good QA practice; it’s a necessity.
Creating fuzzers that work for these systems will be less about simply writing code and more about being creative, having patience, and understanding both old and new ways. The principles behind modern testing, such as abstraction, automation, observability, and feedback, are important to engage with here in order to shine a light into the oldest corners of our digital infrastructure.
Ultimately, whether you are a well-seasoned QA engineer or simply just someone who has tinkered on a morse code translator, testing the extremes of the systems which started it all, is uniquely astonishing.
