In overview, methods, computer programs products and devices for securing software are provided. In accordance with the disclosure, a method may comprise attaching a debugger process to a software process. During execution of the software process, operations relevant to the functionality of the code process are carried out within the debugger process. As a result, the debugger process cannot be replaced or subverted without impinging on the functionality of the software process. The software process can therefore be protected from inspection by modified or malicious debugging techniques.

Methods, systems, and devices for authenticating software images are described. A system may include one or more control units that use software images for managing different functions of the system. The system may also include a secure storage device configured to validate or authenticate the software images used by the different control units of the system. A software image of a control unit may be authenticated by generating a first hash associated with a portion of its underlying source code and generating a second hash associated with a corresponding portion of the source code of the copy of the software image stored to the secure storage device. Different patterns of the source code of the software images may be used to generate the hashes. The first hash and second hash may be compared, and the software image may be authenticated based on the hashes matching.

A method for detecting a defect may include extracting, from application code and using a framework support specification corresponding to a framework, a framework interaction between the application code and the framework. The framework interaction specifies an object used by the application code and managed by the framework. The method may further include performing, using the framework interaction, a dynamic analysis of the application code to obtain a heap snapshot, performing, using the heap snapshot and the framework interaction, a static analysis of the application code, and detecting, by the static analysis, the defect.

An example method includes determining, based on a static scan, that a software container image or an intended execution environment of the software container image meets one or more first criteria required to exploit a software vulnerability. Based on the determining, runtime behavior of a software container instantiated from the software container image is monitored. The monitoring including determining whether the software container meets one or more second criteria required to exploit the software vulnerability, wherein the one or more first second criteria differs from the one or more second criteria. Based on the runtime monitoring, a risk score that indicates a magnitude of a risk the software vulnerability poses for the software container is determined, and a notification of the risk score is provided. A system for assessing software containers for vulnerabilities is also disclosed.

Disclosed herein are systems and methods for enabling the automatic detection of executable code from a stream of bytes. In some embodiments, the stream of bytes can be sourced from the hidden areas of files that traditional malware detection solutions ignore. In some embodiments, a machine learning model is trained to detect whether a particular stream of bytes is executable code. Other embodiments described herein disclose systems and methods for automatic feature extraction using a neural network. Given a new file, the systems and methods may preprocess the code to be inputted into a trained neural network. The neural network may be used as a “feature generator” for a malware detection model. Other embodiments herein are directed to systems and methods for identifying, flagging, and/or detecting threat actors which attempt to obtain access to library functions independently.

A system and a method for automatically clustering sandbox analysis reports of similar malware samples. An automated malware analysis process includes receiving from a sandbox server the sandbox analysis reports of the similar malware samples at an application programming interface (API) of the clustering server, clustering similar Uniform Resource Locators (URLs) together and clustering the sandbox analysis reports of events in sandbox reports clusters (1-n) based on the URL clustering, static properties of the malware samples and dynamic properties of the malware samples.

Example methods are provided for virtual machine introspection in which a guest monitoring mode (GMM) module monitors the execution of guest calls by an agent that resides in a virtual machine (VM). The GMM module sets a bit in bit mask that corresponds to a guest call that the agent needs to execute, and inserts an invisible breakpoint in the code of the guest call. If the GMM module detects that despite the setting of the bit in the bit mask, the agent does not complete the execution of the code (due to the invisible breakpoint not being triggered), then the GMM module considers this condition as a potential hijack of the VM by malicious code.

A method and a device for managing a node includes: initiating, by an application program, a first request by calling an interface function, where the first request is used to perform an operation on a feature node in a kernel; searching, based on a keyword of the interface function, a table used for node management for an entry corresponding to the feature node, where the entry includes a node identifier of the feature node and a user handle identifier of the feature node; and performing, by the user program, the operation on the feature node based on the user handle identifier. A program running in user space can be prevented from directly accessing a feature node in kernel space, thereby improving system security.

A secure guest generates an updated image for the secure guest, and computes one or more measurements for the updated image. The secure guest provides the one or more measurements to a trusted execution environment and obtains from the trusted execution environment metadata for the updated image. The metadata is generated based on metadata of the secure guest and obtaining the one or more measurements.

A debugging management platform and an operating method for the same are provided. In the operating method, the debugging management platform operates a debugging agent service for establishing a debugging channel between a software development platform and a test platform. When receiving debugging packets are issued by the software development platform or the test platform, the debugging agent service analyzes the debugging packets and checks if the debugging packets meet an information security standard. The debugging packets are forwarded to the test platform or the software development platform if the debugging packets meet the information security standard. If the debugging packets do not meet the information security standard, the debugging packets are not forwarded, so as to ensure information security of the debugging packets that are forwarded between different environments.