Undefined Behaviour in C
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Enabling RUST for UEFI Firmware
presented by Enabling RUST for UEFI Firmware UEFI 2020 Virtual Plugfest August 20, 2020 Jiewen Yao & Vincent Zimmer, Intel Corporation www.uefi.org 1 Jiewen Yao • Jiewen Yao is a principal engineer in the Intel Architecture, Graphics, and Software Group. He has been engaged as a firmware developer for over 15 years. He is a member of the UEFI Security sub team, and the TCG PC Client sub working group. www.uefi.org 2 Vincent Zimmer • Vincent Zimmer is a senior principal engineer in the Intel Architecture, Graphics, and Software Group. He has been engaged as a firmware developer for over 25 years and leads the UEFI Security sub team. www.uefi.org 3 Agenda • EDKII Security Summary • RUST Language • Enabling RUST for EDKII • Summary / Call to Action www.uefi.org 4 EDKII Security Summary www.uefi.org 5 BIOS Memory Issue in Hack Conf www.uefi.org 6 BIOS Security Bug Top Issue Open Source Close Source Buffer Overflow/ 50% 38% Integer Overflow SMM 7% 18% Variable 8% 5% Register Lock 3% 10% www.uefi.org 7 Vulnerabilities in C/C++ Source: Trends, challenges, and strategic shifts in the software vulnerability mitigation landscape – Microsoft, Bluehat IL 2019 www.uefi.org 8 Firmware as Software • Many software issues are also firmware issues. – Buffer Overflow – Integer Overflow – Uninitialized Variable • Software mitigation can be used for firmware mitigation. – (See next page) www.uefi.org 9 3 Levels of Prevention Prevention Method EDKII Open Source Example Eliminate Reduce Attack Surface SMI Handler Profile Vulnerability Static Analysis / Dynamic -
Beyond BIOS Developing with the Unified Extensible Firmware Interface
Digital Edition Digital Editions of selected Intel Press books are in addition to and complement the printed books. Click the icon to access information on other essential books for Developers and IT Professionals Visit our website at www.intel.com/intelpress Beyond BIOS Developing with the Unified Extensible Firmware Interface Second Edition Vincent Zimmer Michael Rothman Suresh Marisetty Copyright © 2010 Intel Corporation. All rights reserved. ISBN 13 978-1-934053-29-4 This publication is designed to provide accurate and authoritative information in regard to the subject matter covered. It is sold with the understanding that the publisher is not engaged in professional services. If professional advice or other expert assistance is required, the services of a competent professional person should be sought. Intel Corporation may have patents or pending patent applications, trademarks, copyrights, or other intellectual property rights that relate to the presented subject matter. The furnishing of documents and other materials and information does not provide any license, express or implied, by estoppel or otherwise, to any such patents, trademarks, copyrights, or other intellectual property rights. Intel may make changes to specifications, product descriptions, and plans at any time, without notice. Fictitious names of companies, products, people, characters, and/or data mentioned herein are not intended to represent any real individual, company, product, or event. Intel products are not intended for use in medical, life saving, life sustaining, critical control or safety systems, or in nuclear facility applications. Intel, the Intel logo, Celeron, Intel Centrino, Intel NetBurst, Intel Xeon, Itanium, Pentium, MMX, and VTune are trademarks or registered trademarks of Intel Corporation or its subsidiaries in the United States and other countries. -
Automatic Detection of Uninitialized Variables
Automatic Detection of Uninitialized Variables Thi Viet Nga Nguyen, Fran¸cois Irigoin, Corinne Ancourt, and Fabien Coelho Ecole des Mines de Paris, 77305 Fontainebleau, France {nguyen,irigoin,ancourt,coelho}@cri.ensmp.fr Abstract. One of the most common programming errors is the use of a variable before its definition. This undefined value may produce incorrect results, memory violations, unpredictable behaviors and program failure. To detect this kind of error, two approaches can be used: compile-time analysis and run-time checking. However, compile-time analysis is far from perfect because of complicated data and control flows as well as arrays with non-linear, indirection subscripts, etc. On the other hand, dynamic checking, although supported by hardware and compiler tech- niques, is costly due to heavy code instrumentation while information available at compile-time is not taken into account. This paper presents a combination of an efficient compile-time analysis and a source code instrumentation for run-time checking. All kinds of variables are checked by PIPS, a Fortran research compiler for program analyses, transformation, parallelization and verification. Uninitialized array elements are detected by using imported array region, an efficient inter-procedural array data flow analysis. If exact array regions cannot be computed and compile-time information is not sufficient, array elements are initialized to a special value and their utilization is accompanied by a value test to assert the legality of the access. In comparison to the dynamic instrumentation, our method greatly reduces the number of variables to be initialized and to be checked. Code instrumentation is only needed for some array sections, not for the whole array. -
Undefined Behaviour in the C Language
FAKULTA INFORMATIKY, MASARYKOVA UNIVERZITA Undefined Behaviour in the C Language BAKALÁŘSKÁ PRÁCE Tobiáš Kamenický Brno, květen 2015 Declaration Hereby I declare, that this paper is my original authorial work, which I have worked out by my own. All sources, references, and literature used or excerpted during elaboration of this work are properly cited and listed in complete reference to the due source. Vedoucí práce: RNDr. Adam Rambousek ii Acknowledgements I am very grateful to my supervisor Miroslav Franc for his guidance, invaluable help and feedback throughout the work on this thesis. iii Summary This bachelor’s thesis deals with the concept of undefined behavior and its aspects. It explains some specific undefined behaviors extracted from the C standard and provides each with a detailed description from the view of a programmer and a tester. It summarizes the possibilities to prevent and to test these undefined behaviors. To achieve that, some compilers and tools are introduced and further described. The thesis contains a set of example programs to ease the understanding of the discussed undefined behaviors. Keywords undefined behavior, C, testing, detection, secure coding, analysis tools, standard, programming language iv Table of Contents Declaration ................................................................................................................................ ii Acknowledgements .................................................................................................................. iii Summary ................................................................................................................................. -
Defining the Undefinedness of C
Technical Report: Defining the Undefinedness of C Chucky Ellison Grigore Ros, u University of Illinois {celliso2,grosu}@illinois.edu Abstract naturally capture undefined behavior simply by exclusion, be- This paper investigates undefined behavior in C and offers cause of the complexity of undefined behavior, it takes active a few simple techniques for operationally specifying such work to avoid giving many undefined programs semantics. behavior formally. A semantics-based undefinedness checker In addition, capturing the undefined behavior is at least as for C is developed using these techniques, as well as a test important as capturing the defined behavior, as it represents suite of undefined programs. The tool is evaluated against a source of many subtle program bugs. While a semantics other popular analysis tools, using the new test suite in of defined programs can be used to prove their behavioral addition to a third-party test suite. The semantics-based tool correctness, any results are contingent upon programs actu- performs at least as well or better than the other tools tested. ally being defined—it takes a semantics capturing undefined behavior to decide whether this is the case. 1. Introduction C, together with C++, is the king of undefined behavior—C has over 200 explicitly undefined categories of behavior, and A programming language specification or semantics has dual more that are left implicitly undefined [11]. Many of these duty: to describe the behavior of correct programs and to behaviors can not be detected statically, and as we show later identify incorrect programs. The process of identifying incor- (Section 2.6), detecting them is actually undecidable even rect programs can also be seen as describing which programs dynamically. -
Advanced Practical Programming for Scientists
Advanced practical Programming for Scientists Thorsten Koch Zuse Institute Berlin TU Berlin SS2017 The Zen of Python, by Tim Peters (part 1) ▶︎ Beautiful is better than ugly. ▶︎ Explicit is better than implicit. ▶︎ Simple is better than complex. ▶︎ Complex is better than complicated. ▶︎ Flat is better than nested. ▶︎ Sparse is better than dense. ▶︎ Readability counts. ▶︎ Special cases aren't special enough to break the rules. ▶︎ Although practicality beats purity. ▶︎ Errors should never pass silently. ▶︎ Unless explicitly silenced. ▶︎ In the face of ambiguity, refuse the temptation to guess. Advanced Programming 78 Ex1 again • Remember: store the data and compute the geometric mean on this stored data. • If it is not obvious how to compile your program, add a REAME file or a comment at the beginning • It should run as ex1 filenname • If you need to start something (python, python3, ...) provide an executable script named ex1 which calls your program, e.g. #/bin/bash python3 ex1.py $1 • Compare the number of valid values. If you have a lower number, you are missing something. If you have a higher number, send me the wrong line I am missing. File: ex1-100.dat with 100001235 lines Valid values Loc0: 50004466 with GeoMean: 36.781736 Valid values Loc1: 49994581 with GeoMean: 36.782583 Advanced Programming 79 Exercise 1: File Format (more detail) Each line should consists of • a sequence-number, • a location (1 or 2), and • a floating point value > 0. Empty lines are allowed. Comments can start a ”#”. Anything including and after “#” on a line should be ignored. -
The Art, Science, and Engineering of Fuzzing: a Survey
1 The Art, Science, and Engineering of Fuzzing: A Survey Valentin J.M. Manes,` HyungSeok Han, Choongwoo Han, Sang Kil Cha, Manuel Egele, Edward J. Schwartz, and Maverick Woo Abstract—Among the many software vulnerability discovery techniques available today, fuzzing has remained highly popular due to its conceptual simplicity, its low barrier to deployment, and its vast amount of empirical evidence in discovering real-world software vulnerabilities. At a high level, fuzzing refers to a process of repeatedly running a program with generated inputs that may be syntactically or semantically malformed. While researchers and practitioners alike have invested a large and diverse effort towards improving fuzzing in recent years, this surge of work has also made it difficult to gain a comprehensive and coherent view of fuzzing. To help preserve and bring coherence to the vast literature of fuzzing, this paper presents a unified, general-purpose model of fuzzing together with a taxonomy of the current fuzzing literature. We methodically explore the design decisions at every stage of our model fuzzer by surveying the related literature and innovations in the art, science, and engineering that make modern-day fuzzers effective. Index Terms—software security, automated software testing, fuzzing. ✦ 1 INTRODUCTION Figure 1 on p. 5) and an increasing number of fuzzing Ever since its introduction in the early 1990s [152], fuzzing studies appear at major security conferences (e.g. [225], has remained one of the most widely-deployed techniques [52], [37], [176], [83], [239]). In addition, the blogosphere is to discover software security vulnerabilities. At a high level, filled with many success stories of fuzzing, some of which fuzzing refers to a process of repeatedly running a program also contain what we consider to be gems that warrant a with generated inputs that may be syntactically or seman- permanent place in the literature. -
Precise Null Pointer Analysis Through Global Value Numbering
Precise Null Pointer Analysis Through Global Value Numbering Ankush Das1 and Akash Lal2 1 Carnegie Mellon University, Pittsburgh, PA, USA 2 Microsoft Research, Bangalore, India Abstract. Precise analysis of pointer information plays an important role in many static analysis tools. The precision, however, must be bal- anced against the scalability of the analysis. This paper focusses on improving the precision of standard context and flow insensitive alias analysis algorithms at a low scalability cost. In particular, we present a semantics-preserving program transformation that drastically improves the precision of existing analyses when deciding if a pointer can alias Null. Our program transformation is based on Global Value Number- ing, a scheme inspired from compiler optimization literature. It allows even a flow-insensitive analysis to make use of branch conditions such as checking if a pointer is Null and gain precision. We perform experiments on real-world code and show that the transformation improves precision (in terms of the number of dereferences proved safe) from 86.56% to 98.05%, while incurring a small overhead in the running time. Keywords: Alias Analysis, Global Value Numbering, Static Single As- signment, Null Pointer Analysis 1 Introduction Detecting and eliminating null-pointer exceptions is an important step towards developing reliable systems. Static analysis tools that look for null-pointer ex- ceptions typically employ techniques based on alias analysis to detect possible aliasing between pointers. Two pointer-valued variables are said to alias if they hold the same memory location during runtime. Statically, aliasing can be de- cided in two ways: (a) may-alias [1], where two pointers are said to may-alias if they can point to the same memory location under some possible execution, and (b) must-alias [27], where two pointers are said to must-alias if they always point to the same memory location under all possible executions. -
Patterns in Dynamic Slices to Assist in Automated Debugging
Patterns in Dynamic Slices to Assist in Automated Debugging A thesis submitted to the Graduate School of the University of Cincinnati in partial fulfillment of the requirements for the degree of Master of Science in the Department of Computer Science of the College of Engineering and Applied Science by Joshua W. Burbrink B.S. (Computer Science) University of Cincinnati, Cincinnati, Ohio, USA Thesis Advisor and Committee Chair: Dr. John Franco Abstract The process of manually debugging programs can be difficult and time consuming. The goal of this thesis is to aid developers in debugging their crashed programs by identifying common programming mistakes using information collected during the execution of the crashed program. Specifically, the solution proposed by this thesis calculates a dynamic slice with respect to conditions at the time of the crash and inspects the dynamic slice for characteristics that are only present when certain types of programming errors occur. Common programing mistakes explored by this thesis include: uninitialized heap variables, uninitialized stack variables, dangling pointers, and stack overflow. A prototype, based on the GNU Debugger, was developed to implement the concepts of this thesis and was used to identify common programming mistakes made in a set of example C programs. Experimental results showed that the solutions presented in this thesis performed very well. The prototype was able to identify all occurrences of uninitialized stack variables, uninitialized heap variables, and stack overflow, and only a few instances of dangling pointers were missed. Upon identifying a common programming mistake in the dynamic slice, the prototype was able to produce a high level debug report indicating source code lines relevant to the coding mistake. -
Practical C/C++ Programming Part II
Practical C/C++ programming Part II Wei Feinstein HPC User Services Louisiana State University 7/11/18 Practical C/C++ programming II 1 Topics • Pointers in C • Use in functions • Use in arrays • Use in dynamic memory allocation • Introduction to C++ • Changes from C to C++ • C++ classes and objects • Polymorphism • Templates • Inheritance • Introduction to Standard Template Library (STL) 7/11/18 Practical C/C++ programming II 2 What is a pointer? • A pointer is essentially a variable whose value is the address of another variable. • Pointer “points” to a specific part of the memory. • Important concept in C programming language. Not recommended in C++, yet understanding of pointer is necessary in Object Oriented Programming • How to define pointers? int *i_ptr; /* pointer to an integer */ double *d_ptr; /* pointer to a double */ float *f_ptr; /* pointer to a float */ char *ch_ptr; /* pointer to a character */ int **p_ptr; /* pointer to an integer pointer */ 7/11/18 Practical C/C++ programming II 3 Pointer Operations (a) Define a pointer variable. (b) Assign the address of a variable to a pointer. & /* "address of" operator */ (c) Access the value pointed by the pointer by dereferencing * /* “dereferencing" operator */ Examples: int a = 6; int *ptr; ptr = &a; /* pointer p point to a */ *ptr = 10; /* dereference pointer p reassign a value*/ var_name var_address var_value ptr 0x22aac0 0xXXXX a 0xXXXX 6 7/11/18 Practical C/C++ programming II 4 Pointer Example int b = 17; int *p; /* initialize pointer p */ p = &b; /*pointed addr and value, -
Coverity Static Analysis
Coverity Static Analysis Quickly find and fix Overview critical security and Coverity® gives you the speed, ease of use, accuracy, industry standards compliance, and quality issues as you scalability that you need to develop high-quality, secure applications. Coverity identifies code critical software quality defects and security vulnerabilities in code as it’s written, early in the development process when it’s least costly and easiest to fix. Precise actionable remediation advice and context-specific eLearning help your developers understand how to fix their prioritized issues quickly, without having to become security experts. Coverity Benefits seamlessly integrates automated security testing into your CI/CD pipelines and supports your existing development tools and workflows. Choose where and how to do your • Get improved visibility into development: on-premises or in the cloud with the Polaris Software Integrity Platform™ security risk. Cross-product (SaaS), a highly scalable, cloud-based application security platform. Coverity supports 22 reporting provides a holistic, more languages and over 70 frameworks and templates. complete view of a project’s risk using best-in-class AppSec tools. Coverity includes Rapid Scan, a fast, lightweight static analysis engine optimized • Deployment flexibility. You for cloud-native applications and Infrastructure-as-Code (IaC). Rapid Scan runs decide which set of projects to do automatically, without additional configuration, with every Coverity scan and can also AppSec testing for: on-premises be run as part of full CI builds with conventional scan completion times. Rapid Scan can or in the cloud. also be deployed as a standalone scan engine in Code Sight™ or via the command line • Shift security testing left. -
Declare Property Class Accept Null C
Declare Property Class Accept Null C Woesome and nontechnical Joshuah planned inveterately and pull-outs his frontiers sourly and daftly. Unquiet Bernard fly-by very instructively while Rick remains ectotrophic and chastened. Sometimes stereoscopic Addie unnaturalizes her acorns proportionally, but unlidded Cat invert heinously or orientalizes rancorously. Even experts are accepted types and positional parameters and references, and assigns to. Use HasValue property to check has value is assigned to nullable type sometimes not Static Nullable class is a. Thank you declare more freely, declare property class accept null c is useful to provide only one dispiriting aspect of. Here we're defining a suggest that extracts all non-nullable property keys from plant type. By disabling cookies to accept all? The car variable inside counter Person class shouldn't be declared type grass and. Use JSDoc type. Any class property name, null safe code token stream of properties and corresponds to accept a class! Why death concept of properties came into C The decline because not two reasons If the members of a class are private then select another class in C. JavaScript Properties of variables with null or undefined. Type cup type as should pickle the null value variable the pastry of the variable to which null. CS31 Intro to C Structs and Pointers. Using the New Null Conditional Operator in C 6 InformIT. Your extra bet is to get themselves the good group of initializing all variables when you disabled them. This class that null values can declare variables declared inside an exception handling is nullable context switches a varargs in.