Veracode, Inc.

@stake, Inc.

Christien Rioux

Robert Anthony Layzell

Ryan O'Boyle

John Mcenerney

To facilitate runtime monitoring and analysis of an application without modifying the actual application code, an agent monitors and analyzes an application through detection and evaluation of invocations of an API of a runtime engine provided for execution of the application. The agent registers to receive events which are generated upon invocation of target functions of the runtime engine API based on its load. Once loaded, the agent initially determines the language and language version number of the runtime engine. The agent determines associations of events for which to monitor and corresponding analysis code to execute upon detection of the invocations based on the language and version number information. When the agent detects an event during execution of the application based on invocations of the runtime engine API, the agent can monitor and analyze execution of the application based on execution of analysis code corresponding to the detected event.

Runtime application monitoring without modifying application program code

To support adding functionality to applications at a layer of abstraction above language-specific implementations of AOP, a language for implementing AOP facilitates runtime monitoring and analysis of an application independent of the language of the application. Aspects can be created for applications written in any supported language. Program code underlying implementations of aspects can be executed based on detecting triggering events during execution of the application. Routines written with the AOP language comprise event-based aspect code triggers that indicate an event which may occur during execution of the application and the associated aspect code to be executed. An agent deployed to a runtime engine to monitor the application detects events and evaluates contextual information about the detected events against the aspect triggers to determine if aspect code should be executed to perform further monitoring and analysis of the executing application.

Language-independent application monitoring through aspect-oriented programming

Presently described is a decompilation method of operation and system for parsing executable code, identifying and recursively modeling data flows, identifying and recursively modeling control flow, and iteratively refining these models to provide a complete model at the nanocode level. The nanocode decompiler may be used to determine if flaws, security vulnerabilities, or general quality issues exist in the code. The nanocode decompiler outputs in a standardized, human-readable intermediate representation (IR) designed for automated or scripted analysis and reporting. Reports may take the form of a computer annotated and/or partially human annotated nanocode listing in the above-described IR. Annotations may include plain English statements regarding flaws and pointers to badly constructed data structures, unchecked buffers, malicious embedded code or 'trap doors,' and the like. Annotations may be generated through a scripted analysis process or by means of an expert-enhanced, quasi-autonomous system.

Software analysis framework

Presently described is a decompilation method of operation and system for parsing executable code, identifying and recursively modeling data flows, identifying and recursively modeling control flow, and iteratively refining these models to provide a complete model at the nanocode level. The nanocode decompiler may be used to determine if flaws, security vulnerabilities, or general quality issues exist in the code. The nanocode decompiler outputs in a standardized, human-readable intermediate representation (IR) designed for automated or scripted analysis and reporting. Reports may take the form of a computer annotated and/or partially human annotated nanocode listing in the above-described IR Annotations may include plain English statements regarding flaws and pointers to badly constructed data structures, unchecked buffers, malicious embedded code or 'trap doors,' and the like. Annotations may be generated through a scripted analysis process or by means of an expert-enhanced, quasi-autonomous system.

A system for testing a software application receives one or more object spaces extracted from a development or runtime environment of the software application. The extracted object space includes information about various objects associated with the software application, its dependencies, and/or environment, and some of the objects may be dynamically created and/or modified. The extracted object space does not include any source code. A language dependent extraction component can extract the object space using introspections and/or reflection APIs. The extracted object can be translated into a language-independent format and can be analyzed to identify any vulnerabilities in the software application without access to the source code, compiled binary, and runtime environment of the software application.

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Somerville, MA, United States of America

Christien Rioux