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												  FIPS 140-2 Non-Proprietary Security PolicyKernel Crypto API Cryptographic Module version 1.0 FIPS 140-2 Non-Proprietary Security Policy Version 1.3 Last update: 2020-03-02 Prepared by: atsec information security corporation 9130 Jollyville Road, Suite 260 Austin, TX 78759 www.atsec.com © 2020 Canonical Ltd. / atsec information security This document can be reproduced and distributed only whole and intact, including this copyright notice. Kernel Crypto API Cryptographic Module FIPS 140-2 Non-Proprietary Security Policy Table of Contents 1. Cryptographic Module Specification ..................................................................................................... 5 1.1. Module Overview ..................................................................................................................................... 5 1.2. Modes of Operation ................................................................................................................................. 9 2. Cryptographic Module Ports and Interfaces ........................................................................................ 10 3. Roles, Services and Authentication ..................................................................................................... 11 3.1. Roles .......................................................................................................................................................11 3.2. Services ...................................................................................................................................................11
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												  Red Hat Enterprise Linux 7 7.1 Release NotesRed Hat Enterprise Linux 7 7.1 Release Notes Release Notes for Red Hat Enterprise Linux 7 Red Hat Customer Content Services Red Hat Enterprise Linux 7 7.1 Release Notes Release Notes for Red Hat Enterprise Linux 7 Red Hat Customer Content Services Legal Notice Copyright © 2015 Red Hat, Inc. This document is licensed by Red Hat under the Creative Commons Attribution-ShareAlike 3.0 Unported License. If you distribute this document, or a modified version of it, you must provide attribution to Red Hat, Inc. and provide a link to the original. If the document is modified, all Red Hat trademarks must be removed. Red Hat, as the licensor of this document, waives the right to enforce, and agrees not to assert, Section 4d of CC-BY-SA to the fullest extent permitted by applicable law. Red Hat, Red Hat Enterprise Linux, the Shadowman logo, JBoss, MetaMatrix, Fedora, the Infinity Logo, and RHCE are trademarks of Red Hat, Inc., registered in the United States and other countries. Linux ® is the registered trademark of Linus Torvalds in the United States and other countries. Java ® is a registered trademark of Oracle and/or its affiliates. XFS ® is a trademark of Silicon Graphics International Corp. or its subsidiaries in the United States and/or other countries. MySQL ® is a registered trademark of MySQL AB in the United States, the European Union and other countries. Node.js ® is an official trademark of Joyent. Red Hat Software Collections is not formally related to or endorsed by the official Joyent Node.js open source or commercial project.
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												  The Linux Kernel Module Programming GuideThe Linux Kernel Module Programming Guide Peter Jay Salzman Michael Burian Ori Pomerantz Copyright © 2001 Peter Jay Salzman 2007−05−18 ver 2.6.4 The Linux Kernel Module Programming Guide is a free book; you may reproduce and/or modify it under the terms of the Open Software License, version 1.1. You can obtain a copy of this license at http://opensource.org/licenses/osl.php. This book is distributed in the hope it will be useful, but without any warranty, without even the implied warranty of merchantability or fitness for a particular purpose. The author encourages wide distribution of this book for personal or commercial use, provided the above copyright notice remains intact and the method adheres to the provisions of the Open Software License. In summary, you may copy and distribute this book free of charge or for a profit. No explicit permission is required from the author for reproduction of this book in any medium, physical or electronic. Derivative works and translations of this document must be placed under the Open Software License, and the original copyright notice must remain intact. If you have contributed new material to this book, you must make the material and source code available for your revisions. Please make revisions and updates available directly to the document maintainer, Peter Jay Salzman <[email protected]>. This will allow for the merging of updates and provide consistent revisions to the Linux community. If you publish or distribute this book commercially, donations, royalties, and/or printed copies are greatly appreciated by the author and the Linux Documentation Project (LDP).
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												  RCU Usage in the Linux Kernel: One Decade LaterRCU Usage In the Linux Kernel: One Decade Later Paul E. McKenney Silas Boyd-Wickizer Jonathan Walpole Linux Technology Center MIT CSAIL Computer Science Department IBM Beaverton Portland State University Abstract unique among the commonly used kernels. Understand- ing RCU is now a prerequisite for understanding the Linux Read-copy update (RCU) is a scalable high-performance implementation and its performance. synchronization mechanism implemented in the Linux The success of RCU is, in part, due to its high perfor- kernel. RCU’s novel properties include support for con- mance in the presence of concurrent readers and updaters. current reading and writing, and highly optimized inter- The RCU API facilitates this with two relatively simple CPU synchronization. Since RCU’s introduction into the primitives: readers access data structures within RCU Linux kernel over a decade ago its usage has continued to read-side critical sections, while updaters use RCU syn- expand. Today, most kernel subsystems use RCU. This chronization to wait for all pre-existing RCU read-side paper discusses the requirements that drove the devel- critical sections to complete. When combined, these prim- opment of RCU, the design and API of the Linux RCU itives allow threads to concurrently read data structures, implementation, and how kernel developers apply RCU. even while other threads are updating them. This paper describes the performance requirements that 1 Introduction led to the development of RCU, gives an overview of the RCU API and implementation, and examines how ker- The first Linux kernel to include multiprocessor support nel developers have used RCU to optimize kernel perfor- is not quite 20 years old.
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												  The Xen Port of Kexec / Kdump a Short Introduction and Status ReportThe Xen Port of Kexec / Kdump A short introduction and status report Magnus Damm Simon Horman VA Linux Systems Japan K.K. www.valinux.co.jp/en/ Xen Summit, September 2006 Magnus Damm ([email protected]) Kexec / Kdump Xen Summit, September 2006 1 / 17 Outline Introduction to Kexec What is Kexec? Kexec Examples Kexec Overview Introduction to Kdump What is Kdump? Kdump Kernels The Crash Utility Xen Porting Effort Kexec under Xen Kdump under Xen The Dumpread Tool Partial Dumps Current Status Magnus Damm ([email protected]) Kexec / Kdump Xen Summit, September 2006 2 / 17 Introduction to Kexec Outline Introduction to Kexec What is Kexec? Kexec Examples Kexec Overview Introduction to Kdump What is Kdump? Kdump Kernels The Crash Utility Xen Porting Effort Kexec under Xen Kdump under Xen The Dumpread Tool Partial Dumps Current Status Magnus Damm ([email protected]) Kexec / Kdump Xen Summit, September 2006 3 / 17 Kexec allows you to reboot from Linux into any kernel. as long as the new kernel doesn’t depend on the BIOS for setup. Introduction to Kexec What is Kexec? What is Kexec? “kexec is a system call that implements the ability to shutdown your current kernel, and to start another kernel. It is like a reboot but it is indepedent of the system firmware...” Configuration help text in Linux-2.6.17 Magnus Damm ([email protected]) Kexec / Kdump Xen Summit, September 2006 4 / 17 . as long as the new kernel doesn’t depend on the BIOS for setup. Introduction to Kexec What is Kexec? What is Kexec? “kexec is a system call that implements the ability to shutdown your current kernel, and to start another kernel.
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												  Kernel Boot-Time TracingKernel Boot-time Tracing Linux Plumbers Conference 2019 - Tracing Track Masami Hiramatsu <[email protected]> Linaro, Ltd. Speaker Masami Hiramatsu - Working for Linaro and Linaro members - Tech Lead for a Landing team - Maintainer of Kprobes and related tracing features/tools Why Kernel Boot-time Tracing? Debug and analyze boot time errors and performance issues - Measure performance statistics of kernel boot - Analyze driver init failure - Debug boot up process - Continuously tracing from boot time etc. What We Have There are already many ftrace options on kernel command line ● Setup options (trace_options=) ● Output to printk (tp_printk) ● Enable events (trace_events=) ● Enable tracers (ftrace=) ● Filtering (ftrace_filter=,ftrace_notrace=,ftrace_graph_filter=,ftrace_graph_notrace=) ● Add kprobe events (kprobe_events=) ● And other options (alloc_snapshot, traceoff_on_warning, ...) See Documentation/admin-guide/kernel-parameters.txt Example of Kernel Cmdline Parameters In grub.conf linux /boot/vmlinuz-5.1 root=UUID=5a026bbb-6a58-4c23-9814-5b1c99b82338 ro quiet splash tp_printk trace_options=”sym-addr” trace_clock=global ftrace_dump_on_oops trace_buf_size=1M trace_event=”initcall:*,irq:*,exceptions:*” kprobe_event=”p:kprobes/myevent foofunction $arg1 $arg2;p:kprobes/myevent2 barfunction %ax” What Issues? Size limitation ● kernel cmdline size is small (< 256bytes) ● A half of the cmdline is used for normal boot Only partial features supported ● ftrace has too complex features for single command line ● per-event filters/actions, instances, histograms. Solutions? 1. Use initramfs - Too late for kernel boot time tracing 2. Expand kernel cmdline - It is not easy to write down complex tracing options on bootloader (Single line options is too simple) 3. Reuse structured boot time data (Devicetree) - Well documented, structured data -> V1 & V2 series based on this. Boot-time Trace: V1 and V2 series V1 and V2 series posted at June.
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												  Anatomy of Linux Loadable Kernel Modules a 2.6 Kernel PerspectiveAnatomy of Linux loadable kernel modules A 2.6 kernel perspective Skill Level: Intermediate M. Tim Jones ([email protected]) Consultant Engineer Emulex Corp. 16 Jul 2008 Linux® loadable kernel modules, introduced in version 1.2 of the kernel, are one of the most important innovations in the Linux kernel. They provide a kernel that is both scalable and dynamic. Discover the ideas behind loadable modules, and learn how these independent objects dynamically become part of the Linux kernel. The Linux kernel is what's known as a monolithic kernel, which means that the majority of the operating system functionality is called the kernel and runs in a privileged mode. This differs from a micro-kernel, which runs only basic functionality as the kernel (inter-process communication [IPC], scheduling, basic input/output [I/O], memory management) and pushes other functionality outside the privileged space (drivers, network stack, file systems). You'd think that Linux is then a very static kernel, but in fact it's quite the opposite. Linux can be dynamically altered at run time through the use of Linux kernel modules (LKMs). More in Tim's Anatomy of... series on developerWorks • Anatomy of Linux flash file systems • Anatomy of Security-Enhanced Linux (SELinux) • Anatomy of real-time Linux architectures • Anatomy of the Linux SCSI subsystem • Anatomy of the Linux file system • Anatomy of the Linux networking stack Anatomy of Linux loadable kernel modules © Copyright IBM Corporation 1994, 2008. All rights reserved. Page 1 of 11 developerWorks® ibm.com/developerWorks • Anatomy of the Linux kernel • Anatomy of the Linux slab allocator • Anatomy of Linux synchronization methods • All of Tim's Anatomy of..
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												  The Linux 2.4 Kernel's Startup ProcedureThe Linux 2.4 Kernel’s Startup Procedure William Gatliff 1. Overview This paper describes the Linux 2.4 kernel’s startup process, from the moment the kernel gets control of the host hardware until the kernel is ready to run user processes. Along the way, it covers the programming environment Linux expects at boot time, how peripherals are initialized, and how Linux knows what to do next. 2. The Big Picture Figure 1 is a function call diagram that describes the kernel’s startup procedure. As it shows, kernel initialization proceeds through a number of distinct phases, starting with basic hardware initialization and ending with the kernel’s launching of /bin/init and other user programs. The dashed line in the figure shows that init() is invoked as a kernel thread, not as a function call. Figure 1. The kernel’s startup procedure. Figure 2 is a flowchart that provides an even more generalized picture of the boot process, starting with the bootloader extracting and running the kernel image, and ending with running user programs. Figure 2. The kernel’s startup procedure, in less detail. The following sections describe each of these function calls, including examples taken from the Hitachi SH7750/Sega Dreamcast version of the kernel. 3. In The Beginning... The Linux boot process begins with the kernel’s _stext function, located in arch/<host>/kernel/head.S. This function is called _start in some versions. Interrupts are disabled at this point, and only minimal memory accesses may be possible depending on the capabilities of the host hardware.
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												  LMAX DisruptorDisruptor: High performance alternative to bounded queues for exchanging data between concurrent threads Martin Thompson Dave Farley Michael Barker Patricia Gee Andrew Stewart May-2011 http://code.google.com/p/disruptor/ 1 Abstract LMAX was established to create a very high performance financial exchange. As part of our work to accomplish this goal we have evaluated several approaches to the design of such a system, but as we began to measure these we ran into some fundamental limits with conventional approaches. Many applications depend on queues to exchange data between processing stages. Our performance testing showed that the latency costs, when using queues in this way, were in the same order of magnitude as the cost of IO operations to disk (RAID or SSD based disk system) – dramatically slow. If there are multiple queues in an end-to-end operation, this will add hundreds of microseconds to the overall latency. There is clearly room for optimisation. Further investigation and a focus on the computer science made us realise that the conflation of concerns inherent in conventional approaches, (e.g. queues and processing nodes) leads to contention in multi-threaded implementations, suggesting that there may be a better approach. Thinking about how modern CPUs work, something we like to call “mechanical sympathy”, using good design practices with a strong focus on teasing apart the concerns, we came up with a data structure and a pattern of use that we have called the Disruptor. Testing has shown that the mean latency using the Disruptor for a three-stage pipeline is 3 orders of magnitude lower than an equivalent queue-based approach.
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												  Kdump, a Kexec-Based Kernel Crash Dumping MechanismKdump, A Kexec-based Kernel Crash Dumping Mechanism Vivek Goyal Eric W. Biederman Hariprasad Nellitheertha IBM Linux NetworkX IBM [email protected] [email protected] [email protected] Abstract important consideration for the success of a so- lution has been the reliability and ease of use. Kdump is a crash dumping solution that pro- Kdump is a kexec based kernel crash dump- vides a very reliable dump generation and cap- ing mechanism, which is being perceived as turing mechanism [01]. It is simple, easy to a reliable crash dumping solution for Linux R . configure and provides a great deal of flexibility This paper begins with brief description of what in terms of dump device selection, dump saving kexec is and what it can do in general case, and mechanism, and plugging-in filtering mecha- then details how kexec has been modified to nism. boot a new kernel even in a system crash event. The idea of kdump has been around for Kexec enables booting into a new kernel while quite some time now, and initial patches for preserving the memory contents in a crash sce- kdump implementation were posted to the nario, and kdump uses this feature to capture Linux kernel mailing list last year [03]. Since the kernel crash dump. Physical memory lay- then, kdump has undergone significant design out and processor state are encoded in ELF core changes to ensure improved reliability, en- format, and these headers are stored in a re- hanced ease of use and cleaner interfaces. This served section of memory. Upon a crash, new paper starts with an overview of the kdump de- kernel boots up from reserved memory and pro- sign and development history.
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												  A Thread Synchronization Model for the PREEMPT RT Linux KernelA Thread Synchronization Model for the PREEMPT RT Linux Kernel Daniel B. de Oliveiraa,b,c, R^omulo S. de Oliveirab, Tommaso Cucinottac aRHEL Platform/Real-time Team, Red Hat, Inc., Pisa, Italy. bDepartment of Systems Automation, UFSC, Florian´opolis, Brazil. cRETIS Lab, Scuola Superiore Sant'Anna, Pisa, Italy. Abstract This article proposes an automata-based model for describing and validating sequences of kernel events in Linux PREEMPT RT and how they influence the timeline of threads' execu- tion, comprising preemption control, interrupt handling and control, scheduling and locking. This article also presents an extension of the Linux tracing framework that enables the trac- ing of kernel events to verify the consistency of the kernel execution compared to the event sequences that are legal according to the formal model. This enables cross-checking of a kernel behavior against the formalized one, and in case of inconsistency, it pinpoints possible areas of improvement of the kernel, useful for regression testing. Indeed, we describe in details three problems in the kernel revealed by using the proposed technique, along with a short summary on how we reported and proposed fixes to the Linux kernel community. As an example of the usage of the model, the analysis of the events involved in the activation of the highest priority thread is presented, describing the delays occurred in this operation in the same granularity used by kernel developers. This illustrates how it is possible to take advantage of the model for analyzing the preemption model of Linux. Keywords: Real-time computing, Operating systems, Linux kernel, Automata, Software verification, Synchronization.
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												  Hiding Process Memory Via Anti-Forensic TechniquesDIGITAL FORENSIC RESEARCH CONFERENCE Hiding Process Memory via Anti-Forensic Techniques By: Frank Block (Friedrich-Alexander Universität Erlangen-Nürnberg (FAU) and ERNW Research GmbH) and Ralph Palutke (Friedrich-Alexander Universität Erlangen-Nürnberg) From the proceedings of The Digital Forensic Research Conference DFRWS USA 2020 July 20 - 24, 2020 DFRWS is dedicated to the sharing of knowledge and ideas about digital forensics research. Ever since it organized the first open workshop devoted to digital forensics in 2001, DFRWS continues to bring academics and practitioners together in an informal environment. As a non-profit, volunteer organization, DFRWS sponsors technical working groups, annual conferences and challenges to help drive the direction of research and development. https://dfrws.org Forensic Science International: Digital Investigation 33 (2020) 301012 Contents lists available at ScienceDirect Forensic Science International: Digital Investigation journal homepage: www.elsevier.com/locate/fsidi DFRWS 2020 USA d Proceedings of the Twentieth Annual DFRWS USA Hiding Process Memory Via Anti-Forensic Techniques Ralph Palutke a, **, 1, Frank Block a, b, *, 1, Patrick Reichenberger a, Dominik Stripeika a a Friedrich-Alexander Universitat€ Erlangen-Nürnberg (FAU), Germany b ERNW Research GmbH, Heidelberg, Germany article info abstract Article history: Nowadays, security practitioners typically use memory acquisition or live forensics to detect and analyze sophisticated malware samples. Subsequently, malware authors began to incorporate anti-forensic techniques that subvert the analysis process by hiding malicious memory areas. Those techniques Keywords: typically modify characteristics, such as access permissions, or place malicious data near legitimate one, Memory subversion in order to prevent the memory from being identified by analysis tools while still remaining accessible.