An In-Depth Study with All Rust Cves
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Tesi Final Marco Oliverio.Pdf
i Abstract Advancements in exploitation techniques call for the need of advanced defenses. Modern operating systems have to face new sophisticate attacks that do not rely on any programming mistake, rather they exploit leaking information from computational side effects (side-channel attacks) or hardware glitches (rowhammer attacks). Mitigating these new attacks poses new challanges and involves delicate trade-offs, balancing security on one side and performance, simplicity, and compatibility on the other. In this disseration we explore the attack surface exposed by page fusion, a memory saving optimization in modern operating systems and, after that, a secure page fusion implementation called VUsion is shown. We then propose a complete and compatible software solution to rowhammer attacks called ZebRAM. Lastly, we show OpenCAL, a free and general libray for the implementation of Cellular Automata, that can be used in several security scenarios. iii Acknowledgements I would like to thank my Supervisor prof. Andrea Pugliese for the encouragement and the extremely valuable advice that put me in a fruitful and exciting research direction. A hearty acknowledgment goes to Kaveh Razavi, Cristiano Giuffrida, Herbert Bos and all the VUSec group of the Vrije Universiteit of Amsterdam. I felt at home from day one and I found myself surrounded by brilliant researchers and good friends. v Contents Abstract i Acknowledgements iii Introduction1 1 VUsion3 1.1 Introduction...................................3 1.2 Page Fusion...................................5 1.2.1 Linux Kernel Same-page Merging...................5 1.2.2 Windows Page Fusion.........................7 1.3 Threat Model..................................8 1.4 Known Attack Vectors.............................8 1.4.1 Information Disclosure.........................8 1.4.2 Flip Feng Shui.............................9 1.5 New Attack Vectors.............................. -
Reit) Hydrology \-Th,C),^:::Th
Icru j Institute of 'reit) Hydrology \-Th,c),^:::Th Natural Environment Research Council Environment Research A CouncilNatural • • • • • • • • • SADC-HYCOS • HYDATAv4.0trainingcourse • PRCPretoria,SouthAfrica 28July-6August1998 • • • • • • • • • • Institute of Hydrology Maclean Building Crowmarsh Gifford Wallingford Oxon OXIO 81313 • Tel: 01491 838800 Fax: 01491 692424 • Telex: 849365 HYDROL, G September 1998 • • •••••••••••••••••••••••••••••••••• Summary 111 A key stage in the implementation of the SADC-HYCOS projcct involves establishing a regional database system. Thc database selected was the Institute of Hydrology's HYDATA system. HYDATA is uscd in more than 50 countries worldwide, and is the national database system for surface water data in more than 20 countries, including many of the SADC countries. A ncw Windows version of HYDATA (v4.0) is near release (scheduled January 1999), and provides several improvements over the original DOS-bascd system. It was agreed that HYDATA v4.0 would be provided to each National Hydrological Agency for the SADC- HYCOS project, and that a 2-week training course would be held in Pretoria, South Africa. The first HYDATA v4.0 training course was held at the DWAF training centre in Pretoria between 28 July and 6 August 1998. The course was attended by 16 delegates from 1 I different countries. This report provides a record of the course and the software and training provided. •••••••••••••••••••••••••••••••••• Contents • Page • 1. INTRODUCTION 1 • 1.1Background to SADC-HYCOS 1.2 Background to HYDATA 1.3Background to course 2 2 THE HYDATA TRAINING COURSE 3 • 2.1The HYDATA v4.0 training course 3 • 2.2Visit to DWAF offices 4 • 3. CONCLUSIONS AND FUTURE PLANS 5 • APPENDIX A:RECEIPTS FOR HYDATA v4.0 SOFTWARE 6 • APPENDIX B:PROGRAMME OF VISIT 7 • APPENDIX C:LIST OF TRAINING COURSE PARTICIPANTS 9 • APPENDIX D:LIST OF SOFTWARE BUGS 10 ••••••••••••0-••••••••••••••••••••• • • 1. -
Project Snowflake: Non-Blocking Safe Manual Memory Management in .NET
Project Snowflake: Non-blocking Safe Manual Memory Management in .NET Matthew Parkinson Dimitrios Vytiniotis Kapil Vaswani Manuel Costa Pantazis Deligiannis Microsoft Research Dylan McDermott Aaron Blankstein Jonathan Balkind University of Cambridge Princeton University July 26, 2017 Abstract Garbage collection greatly improves programmer productivity and ensures memory safety. Manual memory management on the other hand often delivers better performance but is typically unsafe and can lead to system crashes or security vulnerabilities. We propose integrating safe manual memory management with garbage collection in the .NET runtime to get the best of both worlds. In our design, programmers can choose between allocating objects in the garbage collected heap or the manual heap. All existing applications run unmodified, and without any performance degradation, using the garbage collected heap. Our programming model for manual memory management is flexible: although objects in the manual heap can have a single owning pointer, we allow deallocation at any program point and concurrent sharing of these objects amongst all the threads in the program. Experimental results from our .NET CoreCLR implementation on real-world applications show substantial performance gains especially in multithreaded scenarios: up to 3x savings in peak working sets and 2x improvements in runtime. 1 Introduction The importance of garbage collection (GC) in modern software cannot be overstated. GC greatly improves programmer productivity because it frees programmers from the burden of thinking about object lifetimes and freeing memory. Even more importantly, GC prevents temporal memory safety errors, i.e., uses of memory after it has been freed, which often lead to security breaches. Modern generational collectors, such as the .NET GC, deliver great throughput through a combination of fast thread-local bump allocation and cheap collection of young objects [63, 18, 61]. -
Ensuring the Spatial and Temporal Memory Safety of C at Runtime
MemSafe: Ensuring the Spatial and Temporal Memory Safety of C at Runtime Matthew S. Simpson, Rajeev K. Barua Department of Electrical & Computer Engineering University of Maryland, College Park College Park, MD 20742-3256, USA fsimpsom, [email protected] Abstract—Memory access violations are a leading source of dereferencing pointers obtained from invalid pointer arith- unreliability in C programs. As evidence of this problem, a vari- metic; and dereferencing uninitialized, NULL or “manufac- ety of methods exist that retrofit C with software checks to detect tured” pointers.1 A temporal error is a violation caused by memory errors at runtime. However, these methods generally suffer from one or more drawbacks including the inability to using a pointer whose referent has been deallocated (e.g. with detect all errors, the use of incompatible metadata, the need for free) and is no longer a valid object. The most well-known manual code modifications, and high runtime overheads. temporal violations include dereferencing “dangling” point- In this paper, we present a compiler analysis and transforma- ers to dynamically allocated memory and freeing a pointer tion for ensuring the memory safety of C called MemSafe. Mem- more than once. Dereferencing pointers to automatically allo- Safe makes several novel contributions that improve upon previ- ous work and lower the cost of safety. These include (1) a method cated memory (stack variables) is also a concern if the address for modeling temporal errors as spatial errors, (2) a compati- of the referent “escapes” and is made available outside the ble metadata representation combining features of object- and function in which it was defined. -
Improving Memory Management Security for C and C++
Improving memory management security for C and C++ Yves Younan, Wouter Joosen, Frank Piessens, Hans Van den Eynden DistriNet, Katholieke Universiteit Leuven, Belgium Abstract Memory managers are an important part of any modern language: they are used to dynamically allocate memory for use in the program. Many managers exist and depending on the operating system and language. However, two major types of managers can be identified: manual memory allocators and garbage collectors. In the case of manual memory allocators, the programmer must manually release memory back to the system when it is no longer needed. Problems can occur when a programmer forgets to release it (memory leaks), releases it twice or keeps using freed memory. These problems are solved in garbage collectors. However, both manual memory allocators and garbage collectors store management information for the memory they manage. Often, this management information is stored where a buffer overflow could allow an attacker to overwrite this information, providing a reliable way to achieve code execution when exploiting these vulnerabilities. In this paper we describe several vulnerabilities for C and C++ and how these could be exploited by modifying the management information of a representative manual memory allocator and a garbage collector. Afterwards, we present an approach that, when applied to memory managers, will protect against these attack vectors. We implemented our approach by modifying an existing widely used memory allocator. Benchmarks show that this implementation has a negligible, sometimes even beneficial, impact on performance. 1 Introduction Security has become an important concern for all computer users. Worms and hackers are a part of every day internet life. -
Memory Tagging and How It Improves C/C++ Memory Safety Kostya Serebryany, Evgenii Stepanov, Aleksey Shlyapnikov, Vlad Tsyrklevich, Dmitry Vyukov Google February 2018
Memory Tagging and how it improves C/C++ memory safety Kostya Serebryany, Evgenii Stepanov, Aleksey Shlyapnikov, Vlad Tsyrklevich, Dmitry Vyukov Google February 2018 Introduction 2 Memory Safety in C/C++ 2 AddressSanitizer 2 Memory Tagging 3 SPARC ADI 4 AArch64 HWASAN 4 Compiler And Run-time Support 5 Overhead 5 RAM 5 CPU 6 Code Size 8 Usage Modes 8 Testing 9 Always-on Bug Detection In Production 9 Sampling In Production 10 Security Hardening 11 Strengths 11 Weaknesses 12 Legacy Code 12 Kernel 12 Uninitialized Memory 13 Possible Improvements 13 Precision Of Buffer Overflow Detection 13 Probability Of Bug Detection 14 Conclusion 14 Introduction Memory safety in C and C++ remains largely unresolved. A technique usually called “memory tagging” may dramatically improve the situation if implemented in hardware with reasonable overhead. This paper describes two existing implementations of memory tagging: one is the full hardware implementation in SPARC; the other is a partially hardware-assisted compiler-based tool for AArch64. We describe the basic idea, evaluate the two implementations, and explain how they improve memory safety. This paper is intended to initiate a wider discussion of memory tagging and to motivate the CPU and OS vendors to add support for it in the near future. Memory Safety in C/C++ C and C++ are well known for their performance and flexibility, but perhaps even more for their extreme memory unsafety. This year we are celebrating the 30th anniversary of the Morris Worm, one of the first known exploitations of a memory safety bug, and the problem is still not solved. -
Memory Management with Explicit Regions by David Edward Gay
Memory Management with Explicit Regions by David Edward Gay Engineering Diploma (Ecole Polytechnique F´ed´erale de Lausanne, Switzerland) 1992 M.S. (University of California, Berkeley) 1997 A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Computer Science in the GRADUATE DIVISION of the UNIVERSITY of CALIFORNIA at BERKELEY Committee in charge: Professor Alex Aiken, Chair Professor Susan L. Graham Professor Gregory L. Fenves Fall 2001 The dissertation of David Edward Gay is approved: Chair Date Date Date University of California at Berkeley Fall 2001 Memory Management with Explicit Regions Copyright 2001 by David Edward Gay 1 Abstract Memory Management with Explicit Regions by David Edward Gay Doctor of Philosophy in Computer Science University of California at Berkeley Professor Alex Aiken, Chair Region-based memory management systems structure memory by grouping objects in regions under program control. Memory is reclaimed by deleting regions, freeing all objects stored therein. Our compiler for C with regions, RC, prevents unsafe region deletions by keeping a count of references to each region. RC's regions have advantages over explicit allocation and deallocation (safety) and traditional garbage collection (better control over memory), and its performance is competitive with both|from 6% slower to 55% faster on a collection of realistic benchmarks. Experience with these benchmarks suggests that modifying many existing programs to use regions is not difficult. An important innovation in RC is the use of type annotations that make the structure of a program's regions more explicit. These annotations also help reduce the overhead of reference counting from a maximum of 25% to a maximum of 12.6% on our benchmarks. -
Buffer Overflows Buffer Overflows
L15: Buffer Overflow CSE351, Spring 2017 Buffer Overflows CSE 351 Spring 2017 Instructor: Ruth Anderson Teaching Assistants: Dylan Johnson Kevin Bi Linxing Preston Jiang Cody Ohlsen Yufang Sun Joshua Curtis L15: Buffer Overflow CSE351, Spring 2017 Administrivia Homework 3, due next Friday May 5 Lab 3 coming soon 2 L15: Buffer Overflow CSE351, Spring 2017 Buffer overflows Address space layout (more details!) Input buffers on the stack Overflowing buffers and injecting code Defenses against buffer overflows 3 L15: Buffer Overflow CSE351, Spring 2017 not drawn to scale Review: General Memory Layout 2N‐1 Stack Stack . Local variables (procedure context) Heap . Dynamically allocated as needed . malloc(), calloc(), new, … Heap Statically allocated Data . Read/write: global variables (Static Data) Static Data . Read‐only: string literals (Literals) Code/Instructions Literals . Executable machine instructions Instructions . Read‐only 0 4 L15: Buffer Overflow CSE351, Spring 2017 not drawn to scale x86‐64 Linux Memory Layout 0x00007FFFFFFFFFFF Stack Stack . Runtime stack has 8 MiB limit Heap Heap . Dynamically allocated as needed . malloc(), calloc(), new, … Statically allocated data (Data) Shared Libraries . Read‐only: string literals . Read/write: global arrays and variables Code / Shared Libraries Heap . Executable machine instructions Data . Read‐only Instructions Hex Address 0x400000 0x000000 5 L15: Buffer Overflow CSE351, Spring 2017 not drawn to scale Memory Allocation Example Stack char big_array[1L<<24]; /* 16 MB */ char huge_array[1L<<31]; /* 2 GB */ int global = 0; Heap int useless() { return 0; } int main() { void *p1, *p2, *p3, *p4; Shared int local = 0; Libraries p1 = malloc(1L << 28); /* 256 MB */ p2 = malloc(1L << 8); /* 256 B */ p3 = malloc(1L << 32); /* 4 GB */ p4 = malloc(1L << 8); /* 256 B */ Heap /* Some print statements .. -
Memory Vulnerability Diagnosis for Binary Program
ITM Web of Conferences 7 03004 , (2016) DOI: 10.1051/itmconf/20160703004 ITA 2016 Memory Vulnerability Diagnosis for Binary Program Feng-Yi TANG, Chao FENG and Chao-Jing TANG College of Electronic Science and Engineering National University of Defense Technology Changsha, China Abstract. Vulnerability diagnosis is important for program security analysis. It is a further step to understand the vulnerability after it is detected, as well as a preparatory step for vulnerability repair or exploitation. This paper mainly analyses the inner theories of major memory vulnerabilities and the threats of them. And then suggests some methods to diagnose several types of memory vulnerabilities for the binary programs, which is a difficult task due to the lack of source code. The diagnosis methods target at buffer overflow, use after free (UAF) and format string vulnerabilities. We carried out some tests on the Linux platform to validate the effectiveness of the diagnosis methods. It is proved that the methods can judge the type of the vulnerability given a binary program. 1 Introduction (or both) the memory area. These headers can contain some information like size, used or not, and etc. Memory vulnerabilities are difficult to detect and diagnose Therefore, we can monitor the allocator so as to especially for those do not crash the program. Due to its determine the base address and the size of the allocation importance, vulnerability diagnosis problem has been areas. Then, check all STORE and LOAD accesses in intensively studied. Researchers have proposed different memory to see which one is outside the allocated area. techniques to diagnose memory vulnerabilities. -
An Evolutionary Study of Linux Memory Management for Fun and Profit Jian Huang, Moinuddin K
An Evolutionary Study of Linux Memory Management for Fun and Profit Jian Huang, Moinuddin K. Qureshi, and Karsten Schwan, Georgia Institute of Technology https://www.usenix.org/conference/atc16/technical-sessions/presentation/huang This paper is included in the Proceedings of the 2016 USENIX Annual Technical Conference (USENIX ATC ’16). June 22–24, 2016 • Denver, CO, USA 978-1-931971-30-0 Open access to the Proceedings of the 2016 USENIX Annual Technical Conference (USENIX ATC ’16) is sponsored by USENIX. An Evolutionary Study of inu emory anagement for Fun and rofit Jian Huang, Moinuddin K. ureshi, Karsten Schwan Georgia Institute of Technology Astract the patches committed over the last five years from 2009 to 2015. The study covers 4587 patches across Linux We present a comprehensive and uantitative study on versions from 2.6.32.1 to 4.0-rc4. We manually label the development of the Linux memory manager. The each patch after carefully checking the patch, its descrip- study examines 4587 committed patches over the last tions, and follow-up discussions posted by developers. five years (2009-2015) since Linux version 2.6.32. In- To further understand patch distribution over memory se- sights derived from this study concern the development mantics, we build a tool called MChecker to identify the process of the virtual memory system, including its patch changes to the key functions in mm. MChecker matches distribution and patterns, and techniues for memory op- the patches with the source code to track the hot func- timizations and semantics. Specifically, we find that tions that have been updated intensively. -
University of California Santa Cruz Learning from Games
UNIVERSITY OF CALIFORNIA SANTA CRUZ LEARNING FROM GAMES FOR GENERATIVE PURPOSES A dissertation submitted in partial satisfaction of the requirements for the degree of DOCTOR OF PHILOSOPHY in COMPUTER SCIENCE by Adam J. Summerville June 2018 The Dissertation of Adam J. Summerville is approved: Professor Michael Mateas, Chair Professor Noah Wardrip-Fruin Professor Santiago Ontañón Dean Tyrus Miller Vice Provost and Dean of Graduate Studies Copyright © by Adam J. Summerville 2018 Table of Contents List of Figures vi List of Tables xiv Abstract xvi Dedication xvii Acknowledgments xviii 1 Introduction 1 1.1 Research Contributions ........................... 5 I Learning From Game 7 2 How Humans Understand Games 8 2.1 Human Annotation Tasks .......................... 17 2.2 Entity Persistence .............................. 17 2.3 Camera Motion ................................ 18 2.4 Room Detection ............................... 21 2.4.1 Teleportation ............................. 23 2.4.2 Traversal ............................... 25 2.5 Animation Cycles ............................... 32 2.6 Mode Dynamics ................................ 34 2.7 Conclusion .................................. 36 3 Mappy – A System for Map Extraction and Annotation via Observa- tion 37 3.1 NES Architecture and Emulation ...................... 41 3.2 Operationalizing Entity Persistence ..................... 43 3.3 Inferring Camera Motion .......................... 49 iii 3.4 Determining Room Transitions ....................... 59 3.4.1 Automatic Mapping ........................ -
Managing Software Development – the Hidden Risk * Dr
Managing Software Development – The Hidden Risk * Dr. Steve Jolly Sensing & Exploration Systems Lockheed Martin Space Systems Company *Based largely on the work: “Is Software Broken?” by Steve Jolly, NASA ASK Magazine, Spring 2009; and the IEEE Fourth International Conference of System of Systems Engineering as “System of Systems in Space 1 Exploration: Is Software Broken?”, Steve Jolly, Albuquerque, New Mexico June 1, 2009 Brief history of spacecraft development • Example of the Mars Exploration Program – Danger – Real-time embedded systems challenge – Fault protection 2 Robotic Mars Exploration 2011 Mars Exploration Program Search: Search: Search: Determine: Characterize: Determine: Aqueous Subsurface Evidence for water Global Extent Subsurface Bio Potential Minerals Ice Found Found of Habitable Ice of Site 3 Found Environments Found In Work Image Credits: NASA/JPL Mars: Easy to Become Infamous … 1. [Unnamed], USSR, 10/10/60, Mars flyby, did not reach Earth orbit 2. [Unnamed], USSR, 10/14/60, Mars flyby, did not reach Earth orbit 3. [Unnamed], USSR, 10/24/62, Mars flyby, achieved Earth orbit only 4. Mars 1, USSR, 11/1/62, Mars flyby, radio failed 5. [Unnamed], USSR, 11/4/62, Mars flyby, achieved Earth orbit only 6. Mariner 3, U.S., 11/5/64, Mars flyby, shroud failed to jettison 7. Mariner 4, U.S. 11/28/64, first successful Mars flyby 7/14/65 8. Zond 2, USSR, 11/30/64, Mars flyby, passed Mars radio failed, no data 9. Mariner 6, U.S., 2/24/69, Mars flyby 7/31/69, returned 75 photos 10. Mariner 7, U.S., 3/27/69, Mars flyby 8/5/69, returned 126 photos 11.