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Ghidra 101
Ghidra 101 is a collection of tutorials and example programs given to summer interns, intended as an initial introduction to using Ghidra and reverse engineering binaries.
Scalable Binary Application Analysis - Enhancing Vulnerability Analyses via Automated Patch Diffing [Poster]
TITANS CCD Open House Poster presenting summer intern work completed on an automated patch diffing pipeline, targeted for reverse engineers and vulnerability researchers.
Firmware Tampering Detection in Heavy-Duty Vehicles through J1939 CAN Analysis
Modern heavy-duty vehicles rely on complex networks of Electronic Control Units (ECUs) that communicate using the J1939 protocol. While this system makes it easier to update and configure vehicle components, it also opens the door to serious cybersecurity risks if not properly secured. This work investigates the potential for firmware tampering through the J1939 communication protocol, which enables ECU configuration and reprogramming over the Controller Area Network (CAN) bus. By monitoring CAN traffic during legitimate maintenance operations and reverse-engineering OEM diagnostic software, we identified common and proprietary J1939 message identifiers, authentication patterns, and vulnerabilities within Unified Diagnostic Services (UDS). These findings demonstrate that inadequate authentication mechanisms can allow malicious actors to alter ECU firmware or disable safety functions, posing severe operational and safety risks. Our analysis contributes to the development of vehicle intrusion detection systems capable of recognizing abnormal reprogramming activity and future firmware fingerprinting methods to verify software integrity across ECUs. This work highlights the importance of standardizing secure firmware authentication across manufacturers to strengthen cyber resilience in heavy-duty vehicle systems.
A graphically oriented specification language for automatic code generation. GRASP/Ada: A Graphical Representation of Algorithms, Structure, and Processes for Ada, phase 1
The first phase of a three-phase effort to develop a new graphically oriented specification language which will facilitate the reverse engineering of Ada source code into graphical representations (GRs) as well as the automatic generation of Ada source code is described. A simplified view of the three phases of Graphical Representations for Algorithms, Structure, and Processes for Ada (GRASP/Ada) with respect to three basic classes of GRs is presented. Phase 1 concentrated on the derivation of an algorithmic diagram, the control structure diagram (CSD) (CRO88a) from Ada source code or Ada PDL. Phase 2 includes the generation of architectural and system level diagrams such as structure charts and data flow diagrams and should result in a requirements specification for a graphically oriented language able to support automatic code generation. Phase 3 will concentrate on the development of a prototype to demonstrate the feasibility of this new specification language.
Software: Where we are and what is required in the future
The current status and future direction of flight critical software are presented in the form of view-graphs. The following subject areas are covered: the programmers environment; Saab Grippen Flight test program; present day tools; analysis tools (reverse engineering); automatic code generators; and future plans.
Integrating aerodynamic surface modeling for computational fluid dynamics with computer aided structural analysis, design, and manufacturing
This presentation will discuss the development of a NASA Geometry Exchange Specification for transferring aerodynamic surface geometry between LeRC systems and grid generation software used for computational fluid dynamics research. The proposed specification is based on a subset of the Initial Graphics Exchange Specification (IGES). The presentation will include discussion of how the NASA-IGES standard will accommodate improved computer aided design inspection methods and reverse engineering techniques currently being developed. The presentation is in viewgraph format.
Investigation and modification of a commercially available tactile sensor suited for robotic applications
Active (dynamic) tactile sensing was explored using a commercially available tactile array sensor. This task requires the redesign of the sensor interface and a full understanding of the old sensor hardware implementation. There were different stages to this research; the first stage involved the reverse engineering of the old tactile sensor. The second stage had to do with the exploration of the characteristics and behavior of the tactile sensor pad. The next stage dealt with the redesign of the sensor interface using the knowledge gained from the previous two stages. Finally, in the last stage, software to control the tactile sensor was developed to aid in the data acquisition process.
Model-based software design
Domain-specific knowledge is required to create specifications, generate code, and understand existing systems. Our approach to automating software design is based on instantiating an application domain model with industry-specific knowledge and then using that model to achieve the operational goals of specification elicitation and verification, reverse engineering, and code generation. Although many different specification models can be created from any particular domain model, each specification model is consistent and correct with respect to the domain model.
Software risk management through independent verification and validation
Software project managers need tools to estimate and track project goals in a continuous fashion before, during, and after development of a system. In addition, they need an ability to compare the current project status with past project profiles to validate management intuition, identify problems, and then direct appropriate resources to the sources of problems. This paper describes a measurement-based approach to calculating the risk inherent in meeting project goals that leverages past project metrics and existing estimation and tracking models. We introduce the IV&V Goal/Questions/Metrics model, explain its use in the software development life cycle, and describe our attempts to validate the model through the reverse engineering of existing projects.
Precision Casting via Advanced Simulation and Manufacturing
A two-year program was conducted to develop and commercially implement selected casting manufacturing technologies to enable significant reductions in the costs of castings, increase the complexity and dimensional accuracy of castings, and reduce the development times for delivery of high quality castings. The industry-led R&D project was cost shared with NASA's Aerospace Industry Technology Program (AITP). The Rocketdyne Division of Boeing North American, Inc. served as the team lead with participation from Lockheed Martin, Ford Motor Company, Howmet Corporation, PCC Airfoils, General Electric, UES, Inc., University of Alabama, Auburn University, Robinson, Inc., Aracor, and NASA-LeRC. The technical effort was organized into four distinct tasks. The accomplishments reported herein. Task 1.0 developed advanced simulation technology for core molding. Ford headed up this task. On this program, a specialized core machine was designed and built. Task 2.0 focused on intelligent process control for precision core molding. Howmet led this effort. The primary focus of these experimental efforts was to characterize the process parameters that have a strong impact on dimensional control issues of injection molded cores during their fabrication. Task 3.0 developed and applied rapid prototyping to produce near net shape castings. Rocketdyne was responsible for this task. CAD files were generated using reverse engineering, rapid prototype patterns were fabricated using SLS and SLA, and castings produced and evaluated. Task 4.0 was aimed at developing technology transfer. Rocketdyne coordinated this task. Casting related technology, explored and evaluated in the first three tasks of this program, was implemented into manufacturing processes.
Structural Anomalies Detected in Ceramic Matrix Composites Using Combined Nondestructive Evaluation and Finite Element Analysis (NDE and FEA)
Most reverse engineering approaches involve imaging or digitizing an object and then creating a computerized reconstruction that can be integrated, in three dimensions, into a particular design environment. The rapid prototyping technique builds high-quality physical prototypes directly from computer-aided design files. This fundamental technique for interpreting and interacting with large data sets is being used here via Velocity2 (an integrated image-processing software, ref. 1) using computed tomography (CT) data to produce a prototype three-dimensional test specimen model for analyses. A study at the NASA Glenn Research Center proposes to use these capabilities to conduct a combined nondestructive evaluation (NDE) and finite element analysis (FEA) to screen pretest and posttest structural anomalies in structural components. A tensile specimen made of silicon nitrite (Si3N4) ceramic matrix composite was considered to evaluate structural durability and deformity. Ceramic matrix composites are being sought as candidate materials to replace nickel-base superalloys for turbine engine applications. They have the unique characteristics of being able to withstand higher operating temperatures and harsh combustion environments. In addition, their low densities relative to metals help reduce component mass (ref. 2). Detailed three-dimensional volume rendering of the tensile test specimen was successfully carried out with Velocity2 (ref. 1) using two-dimensional images that were generated via computed tomography. Subsequent, three-dimensional finite element analyses were performed, and the results obtained were compared with those predicted by NDE-based calculations and experimental tests. It was shown that Velocity2 software can be used to render a three-dimensional object from a series of CT scan images with a minimum level of complexity. The analytical results (ref. 3) show that the high-stress regions correlated well with the damage sites identified by the CT scans and the experimental data. Furthermore, modeling of the voids collected via NDE offered an analytical advantage that resulted in more accurate assessments of the material s structural strength. The top figure shows a CT scan image of the specimen test section illustrating various hidden structural entities in the material and an optical image of the test specimen considered in this study. The bottom figure represents the stress response predicted from the finite element analyses (ref .3 ) for a selected CT slice where it clearly illustrates the correspondence of the high stress risers due to voids in the material with those predicted by the NDE. This study is continuing, and efforts are concentrated on improving the modeling capabilities to imitate the structural anomalies as detected.
Biomimetic robots using EAP as artificial muscles - progress and challenges
Biology offers a great model for emulation in areas ranging from tools, computational algorithms, materials science, mechanisms and information technology. In recent years, the field of biomimetics, namely mimicking biology, has blossomed with significant advances enabling the reverse engineering of many animals' functions and implementation of some of these capabilities.
SEE Rate Estimation: Model Complexity and Data Requirements
Statistical Methods outlined in [Ladbury, TNS20071 can be generalized for Monte Carlo Rate Calculation Methods Two Monte Carlo Approaches: a) Rate based on vendor-supplied (or reverse-engineered) model SEE testing and statistical analysis performed to validate model; b) Rate calculated based on model fit to SEE data Statistical analysis very similar to case for CREME96. Information Theory allows simultaneous consideration of multiple models with different complexities: a) Model with lowest AIC usually has greatest predictive power; b) Model averaging using AIC weights may give better performance if several models have similar good performance; and c) Rates can be bounded for a given confidence level over multiple models, as well as over the parameter space of a model.
Program Synthesizes UML Sequence Diagrams
A computer program called "Rational Sequence" generates Universal Modeling Language (UML) sequence diagrams of a target Java program running on a Java virtual machine (JVM). Rational Sequence thereby performs a reverse engineering function that aids in the design documentation of the target Java program. Whereas previously, the construction of sequence diagrams was a tedious manual process, Rational Sequence generates UML sequence diagrams automatically from the running Java code.
Jet Noise Diagnostics Supporting Statistical Noise Prediction Methods
The primary focus of my presentation is the development of the jet noise prediction code JeNo with most examples coming from the experimental work that drove the theoretical development and validation. JeNo is a statistical jet noise prediction code, based upon the Lilley acoustic analogy. Our approach uses time-average 2-D or 3-D mean and turbulent statistics of the flow as input. The output is source distributions and spectral directivity. NASA has been investing in development of statistical jet noise prediction tools because these seem to fit the middle ground that allows enough flexibility and fidelity for jet noise source diagnostics while having reasonable computational requirements. These tools rely on Reynolds-averaged Navier-Stokes (RANS) computational fluid dynamics (CFD) solutions as input for computing far-field spectral directivity using an acoustic analogy. There are many ways acoustic analogies can be created, each with a series of assumptions and models, many often taken unknowingly. And the resulting prediction can be easily reverse-engineered by altering the models contained within. However, only an approach which is mathematically sound, with assumptions validated and modeled quantities checked against direct measurement will give consistently correct answers. Many quantities are modeled in acoustic analogies precisely because they have been impossible to measure or calculate, making this requirement a difficult task. The NASA team has spent considerable effort identifying all the assumptions and models used to take the Navier-Stokes equations to the point of a statistical calculation via an acoustic analogy very similar to that proposed by Lilley. Assumptions have been identified and experiments have been developed to test these assumptions. In some cases this has resulted in assumptions being changed. Beginning with the CFD used as input to the acoustic analogy, models for turbulence closure used in RANS CFD codes have been explored and compared against measurements of mean and rms velocity statistics over a range of jet speeds and temperatures. Models for flow parameters used in the acoustic analogy, most notably the space-time correlations of velocity, have been compared against direct measurements, and modified to better fit the observed data. These measurements have been extremely challenging for hot, high speed jets, and represent a sizeable investment in instrumentation development. As an intermediate check that the analysis is predicting the physics intended, phased arrays have been employed to measure source distributions for a wide range of jet cases. And finally, careful far-field spectral directivity measurements have been taken for final validation of the prediction code. Examples of each of these experimental efforts will be presented. The main result of these efforts is a noise prediction code, named JeNo, which is in middevelopment. JeNo is able to consistently predict spectral directivity, including aft angle directivity, for subsonic cold jets of most geometries. Current development on JeNo is focused on extending its capability to hot jets, requiring inclusion of a previously neglected second source associated with thermal fluctuations. A secondary result of the intensive experimentation is the archiving of various flow statistics applicable to other acoustic analogies and to development of time-resolved prediction methods. These will be of lasting value as we look ahead at future challenges to the aeroacoustic experimentalist.
Anatomy of a Security Operations Center
Many agencies and corporations are either contemplating or in the process of building a cyber Security Operations Center (SOC). Those Agencies that have established SOCs are most likely working on major revisions or enhancements to existing capabilities. As principle developers of the NASA SOC; this Presenters' goals are to provide the GFIRST community with examples of some of the key building blocks of an Agency scale cyber Security Operations Center. This presentation viII include the inputs and outputs, the facilities or shell, as well as the internal components and the processes necessary to maintain the SOC's subsistence - in other words, the anatomy of a SOC. Details to be presented include the SOC architecture and its key components: Tier 1 Call Center, data entry, and incident triage; Tier 2 monitoring, incident handling and tracking; Tier 3 computer forensics, malware analysis, and reverse engineering; Incident Management System; Threat Management System; SOC Portal; Log Aggregation and Security Incident Management (SIM) systems; flow monitoring; IDS; etc. Specific processes and methodologies discussed include Incident States and associated Work Elements; the Incident Management Workflow Process; Cyber Threat Risk Assessment methodology; and Incident Taxonomy. The Evolution of the Cyber Security Operations Center viII be discussed; starting from reactive, to proactive, and finally to proactive. Finally, the resources necessary to establish an Agency scale SOC as well as the lessons learned in the process of standing up a SOC viII be presented.
Planetary Suit Hip Bearing Model for Predicting Design vs. Performance
Designing a planetary suit is very complex and often requires difficult trade-offs between performance, cost, mass, and system complexity. In order to verifying that new suit designs meet requirements, full prototypes must eventually be built and tested with human subjects. Using computer models early in the design phase of new hardware development can be advantageous, allowing virtual prototyping to take place. Having easily modifiable models of the suit hard sections may reduce the time it takes to make changes to the hardware designs and then to understand their impact on suit and human performance. A virtual design environment gives designers the ability to think outside the box and exhaust design possibilities before building and testing physical prototypes with human subjects. Reductions in prototyping and testing may eventually reduce development costs. This study is an attempt to develop computer models of the hard components of the suit with known physical characteristics, supplemented with human subject performance data. Objectives: The primary objective was to develop an articulating solid model of the Mark III hip bearings to be used for evaluating suit design performance of the hip joint. Methods: Solid models of a planetary prototype (Mark III) suit s hip bearings and brief section were reverse-engineered from the prototype. The performance of the models was then compared by evaluating the mobility performance differences between the nominal hardware configuration and hardware modifications. This was accomplished by gathering data from specific suited tasks. Subjects performed maximum flexion and abduction tasks while in a nominal suit bearing configuration and in three off-nominal configurations. Performance data for the hip were recorded using state-of-the-art motion capture technology. Results: The results demonstrate that solid models of planetary suit hard segments for use as a performance design tool is feasible. From a general trend perspective, the suited performance trends were comparable between the model and the suited subjects. With the three off-nominal bearing configurations compared to the nominal bearing configurations, human subjects showed decreases in hip flexion of 64%, 6%, and 13% and in hip abduction of 59%, 2%, and 20%. Likewise the solid model showed decreases in hip flexion of 58%, 1%, and 25% and in hip abduction of 56%, 0%, and 30%, under the same condition changes from the nominal configuration. Differences seen between the model predictions and the human subject performance data could be attributed to the model lacking dynamic elements and performing kinematic analysis only, the level of fit of the subjects with the suit, the levels of the subject s suit experience.