In today's highly interconnected digital world, exploiting software security vulnerabilities to invade and modify systems is one of the most common methods used by hackers. In order to improve the security of software, security researchers need to constantly explore new vulnerability discovery methods and technologies.
Before showing practical cases, let's first take a look at how vulnerabilities are discovered. There are many methods of vulnerability discovery. The following are the common ones.
01 Reverse engineering
By reverse engineering an existing application or system, you can gain insights into its internal mechanisms and operations. This may include performing static or dynamic analysis, analyzing binaries, parsing protocols, understanding interactions between components, etc. Through reverse engineering, potential security vulnerabilities in the system can be discovered.
02 Static code analysis
Static code analysis is a method of discovering potential vulnerabilities by analyzing the source code or binary code of a compiled program. It can detect common security issues such as logical errors in code, buffer overflows, and null pointer dereferences. Static code analysis can be performed manually or assisted by automated tools.
03 Dynamic analysis
Dynamic analysis is a method of discovering vulnerabilities by running a target system and observing its behavior. It can involve techniques such as manual testing, code injection, monitoring system calls, and more. Dynamic analysis can help detect runtime vulnerabilities, memory errors, security configuration issues, and more.
04 Fuzzing (fuzz testing)
Fuzz testing is an automated vulnerability mining technology that causes potential security issues in the system by inputting incorrect, unexpected or random data into the target system. Through continuous fuzz testing of different input points of an application, protocol, or operating system, potential vulnerabilities in the system can be discovered.
Below, we use a real case of the open source network security fuzz testing tool (SFuzz) to gain an in-depth understanding of the vulnerability discovery process.
The open source network security fuzz testing platform (SFuzz) is a self-developed security detection product based on fuzz testing technology. It includes three functional modules: protocol fuzz testing, Web API fuzz testing, and code fuzz testing. It covers black box and gray box testing technology and is highly efficient. Detect potential security vulnerabilities in various software and hardware systems.
A practical case of vulnerability mining process of a certain manufacturer
Test target
Conduct Modbus TCP protocol fuzz testing on a manufacturer's industrial control equipment to discover potential security vulnerabilities in the equipment.
Testing process
Step 1: Parse the protocol and generate data packets
The model parser of the SFuzz test engine parses the Modbus TCP protocol, generates message data packets (i.e., seed input), and then uses nearly 60 mutation algorithms to randomly extract fields of the messages for mutation, resulting in invalid, unexpected or random results. The data.
Step 2: Monitor data and troubleshoot abnormalities
The data processed by the mutator is sent to the industrial control equipment system through the Modbus TCP protocol communication protocol, and the monitor is used to monitor its behavior and response, such as whether there is a crash, memory leak, system crash or other abnormal situation.
Step 3: Analyze anomalies, classify and evaluate
Analyze anomalies and errors triggered during fuzz testing, including crashes, DoS, vulnerability exposure, etc., and then classify and evaluate these results according to severity and likelihood.
Step 4: Feedback report and make timely repairs
Record the results of fuzz testing in a report and provide it to the device manufacturer or relevant security team. Reports should include discovered vulnerabilities, anomalies, and recommended fixes. Device manufacturers can use reports to fix problems and improve device security.
Testing recommendations
Because fuzz testing is a high-risk testing technology that may cause industrial control equipment failure or system instability. When performing fuzz testing, it is recommended to conduct fuzz testing in a test environment to avoid damage to the production environment or key systems. Also make sure to back up your device and system data to avoid data loss.
The above is a simple case of fuzz testing of industrial control protocols. The actual fuzz testing process may be more complex and detailed, and needs to be adjusted and expanded according to the specific industrial control systems and protocols.
Fuzz testing can effectively dig out security vulnerabilities in software systems, help the development team identify potential security issues in the program, and assist in repair and verification, thereby improving the security and reliability of the application. With the development of technology, fuzz testing has added artificial intelligence and machine learning, and has made significant developments in input generation technology, coverage analysis, intelligent technology, application field expansion, and automation and integration. These advances have made fuzz testing tools more powerful and efficient, playing an important role in discovering vulnerabilities in software and systems.