Forensics with Linux 101 Or How to Do Forensics for Free
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Ocaml Standard Library Ocaml V
OCaml Standard Library OCaml v. 3.12.0 | June 7, 2011 | Copyright c 2011 OCamlPro SAS | http://www.ocamlpro.com/ Standard Modules module List module Array Basic Data Types let len = List.length l let t = Array.create len v let t = Array.init len (fun pos -> v_at_pos) Pervasives All basic functions List.iter (fun ele -> ... ) l; let v = t.(pos) String Functions on Strings let l' = List.map(fun ele -> ... ) l t.(pos) <- v; Array Functions on Polymorphic Arrays let l' = List.rev l1 let len = Array.length t List Functions on Polymorphic Lists let acc' = List.fold left (fun acc ele -> ...) acc l let t' = Array.sub t pos len Char Functions on Characters let acc' = List.fold right (fun ele acc -> ...) l acc let t = Array.of_list list Int32 Functions on 32 bits Integers if List.mem ele l then ... let list = Array.to_list t Int64 Functions on 64 bits Integers if List.for all (fun ele -> ele >= 0) l then ... Array.iter (fun v -> ... ) t; Nativeint Functions on Native Integers if List.exists (fun ele -> ele < 0) l then ... let neg = List.find (fun x -> x < 0) ints Array.iteri (fun pos v -> ... ) t; Advanced Data Types let negs = List.find all (fun x -> x < 0) ints let t' = Array.map (fun v -> ... ) t let t' = Array.mapi (fun pos v -> ... ) t Buffer Automatically resizable strings let (negs,pos) = List.partition (fun x -> x < 0) ints let ele = List.nth 2 list let concat = Array.append prefix suffix Complex Complex Numbers Array.sort compare t; Digest MD5 Checksums let head = List.hd list Hashtbl Polymorphic Hash Tables let tail = List.tl list let value = List.assoc key assocs Queue Polymorphic FIFO module Char Stack Polymorphic LIFO if List.mem assoc key assocs then .. -
High Performance Multi-Node File Copies and Checksums for Clustered File Systems∗
High Performance Multi-Node File Copies and Checksums for Clustered File Systems∗ Paul Z. Kolano, Robert B. Ciotti NASA Advanced Supercomputing Division NASA Ames Research Center, M/S 258-6 Moffett Field, CA 94035 U.S.A. {paul.kolano,bob.ciotti}@nasa.gov Abstract To achieve peak performance from such systems, it is Mcp and msum are drop-in replacements for the stan- typically necessary to utilize multiple concurrent read- dard cp and md5sum programs that utilize multiple types ers/writers from multiple systems to overcome various of parallelism and other optimizations to achieve maxi- single-system limitations such as number of processors mum copy and checksum performance on clustered file and network bandwidth. The standard cp and md5sum systems. Multi-threading is used to ensure that nodes are tools of GNU coreutils [11] found on every modern kept as busy as possible. Read/write parallelism allows Unix/Linux system, however, utilize a single execution individual operations of a single copy to be overlapped thread on a single CPU core of a single system, hence using asynchronous I/O. Multi-node cooperation allows cannot take full advantage of the increased performance different nodes to take part in the same copy/checksum. of clustered file system. Split file processing allows multiple threads to operate This paper describes mcp and msum, which are drop- concurrently on the same file. Finally, hash trees allow in replacements for cp and md5sum that utilize multi- inherently serial checksums to be performed in parallel. ple types of parallelism to achieve maximum copy and This paper presents the design of mcp and msum and de- checksum performance on clustered file systems. -
NOMADS User Guide V1.0
NOMADS User Guide V1.0 Table of Contents • Introduction o Explanation of "Online" and "Offline" Data o Obtaining Offline Data o Offline Order Limitations • Distributed Data Access o Functional Overview o Getting Started with OPeNDAP o Desktop Services ("Clients") o OPeNDAP Servers • Quick Start to Retrieve or Plot Data o Getting Started o Using FTP to Retrieve Data o Using HTTP to Retrieve Data o Using wget to Retrieve Data o Using GDS Clients to Plot Data o Using the NOMADS Server to Create Plots • Advanced Data Access Methods o Subsetting Parameters and Levels Using FTP4u o Obtain ASCII Data Using GDS o Scripting Wget in a Time Loop o Mass GRIB Subsetting: Utilizing Partial-file HTTP Transfers • General Data Structure o Organization of Data Directories o Organization of Data Files o Use of Templates in GrADS Data Descriptor Files • MD5 Hash Files o Purpose of MD5 Files o Identifying MD5 Files o Using md5sum on MD5 Files (Linux) o Using gmd5sum on MD5 Files (FreeBSD) o External Links • Miscellaneous Information o Building Dataset Collections o Working with Timeseries Data o Creating Plots with GrADS o Scheduled Downtime Notification Introduction The model data repository at NCEI contains both deep archived (offline) and online model data. We provide a variety of ways to access our weather and climate model data. You can access the online data using traditional access methods (web-based or FTP), or you can use open and distributed access methods promoted under the collaborative approach called the NOAA National Operational Model Archive and Distribution System (NOMADS). On the Data Products page you are presented with a table that contains basic information about each dataset, as well as links to the various services available for each dataset. -
Download Instructions—Portal
Download instructions These instructions are recommended to download big files. How to download and verify files from downloads.gvsig.org • H ow to download files • G NU/Linux Systems • MacO S X Systems • Windows Systems • H ow to validate the downloaded files How to download files The files distributed on this site can be downloaded using different access protocols, the ones currently available are FTP, HTTP and RSYNC. The base URL of the site for the different protocols is: • ftp://gvsig.org/ • http://downloads.gvsig.org/ • r sync://gvsig.org/downloads/ To download files using the first two protocols is recommended to use client programs able to resume partial downloads, as it is usual to have transfer interruptions when downloading big files like DVD images. There are multiple free (and multi platform) programs to download files using different protocols (in our case we are interested in FTP and HTTP), from them we can highlight curl (http://curl.haxx.se/) and wget (http://www.gnu.org/software/wget/) from the command line ones and Free Download Manager from the GUI ones (this one is only for Windows systems). The curl program is included in MacOS X and is available for almost all GNU/Linux distributions. It can be downloaded in source code or in binary form for different operating systems from the project web site. The wget program is also included in almost all GNU/Linux distributions and its source code or binaries of the program for different systems can be downloaded from this page. Next we will explain how to download files from the most usual operating systems using the programs referenced earlier: • G NU/Linux Systems • MacO S X Systems • Windows Systems The use of rsync (available from the URL http://samba.org/rsync/) it is left as an exercise for the reader, we will only said that it is advised to use the --partial option to avoid problems when there transfers are interrupted. -
High-Performance, Multi-Node File Copies and Checksums for Clustered File Systems Stiffness and Damping Coefficient Estimation O
https://ntrs.nasa.gov/search.jsp?R=20120010444 2019-08-30T20:40:58+00:00Z View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by NASA Technical Reports Server entrance pupil points of interest. These field or aperture, depending on the allo- nates of interest are obtained for every are chosen to be the edge of each space, cations. Once this minimum set of coor- plane of the propagation, the data is for- so that these rays produce the bounding dinates on the pupil and field is ob- matted into an xyz file suitable for FRED volume for the beam. The x and y global tained, a new set of rays is generated optical analysis software to import and coordinate data is collected on the sur- between the field plane and aperture create a STEP file of the data. This re- face planes of interest, typically an image plane (or vice-versa). sults in a spiral-like structure that is easily of the field and entrance pupil internal These rays are then evaluated at imported by mechanical CAD users who of the optical system. This x and y coor- planes between the aperture and field, at can then use an automated algorithm to dinate data is then evaluated using a a desired number of steps perceived nec- wrap a skin around it and create a solid convex hull algorithm, which removes essary to build up the bounding volume that represents the beam. any internal points, which are unneces- or cone shape. At each plane, the ray co- This work was done by Joseph Howard and sary to produce the bounding volume of ordinates are again evaluated using the Lenward Seals of Goddard Space Flight Center. -
HPRC Short Course Introduction to Linux
HPRC Short Course Introduction to Linux Texas A&M University High Performance Research Computing – https://hprc.tamu.edu 1 For Assistance… Website: hprc.tamu.edu Email: [email protected] Telephone: (979) 845-0219 Visit us: Henderson Hall, Room 114A Help us, help you -- we need more info •Which Cluster •NetID •Job ID(s) if any •Location of your job files, input/output files •Application used & module(s) loaded if any •Error messages •Steps you have taken, so we can reproduce the problem Texas A&M University High Performance Research Computing – https://hprc.tamu.edu 2 Course Outline 1 Accessing the System Secure shell 2 Directories Our first commands 3 Gedit An easy text editor 4 File Manipulation Copy, rename/move & remove 5 Passing output & Redirection Learning about operators 6 The Linux file system Attributes and permissions 7 Environment Variables & $PATH Storing and retrieving information 8 Basic Shell Scripting Making Linux work for you Texas A&M University High Performance Research Computing – https://hprc.tamu.edu 3 Your Login Password • Both State of Texas law and TAMU regulations prohibit the sharing and/or illegal use of computer passwords and accounts; • Don’t write down passwords; • Don’t choose easy to guess/crack passwords; • Change passwords frequently Texas A&M University High Performance Research Computing – https://hprc.tamu.edu 4 1. Accessing the system • SSH (secure shell) – The only program allowed for remote access; encrypted communication; freely available for Linux/Unix and Mac OS X hosts; • For Microsoft Windows PCs, use MobaXterm • https://hprc.tamu.edu/wiki/HPRC:MobaXterm – You are able to view images and use GUI applications with MobaXterm – or Putty • https://hprc.tamu.edu/wiki/HPRC:Access#Using_PuTTY – You can not view images or use GUI applications with PuTTY Texas A&M University High Performance Research Computing – https://hprc.tamu.edu 5 Using SSH - MobaXterm on Windows https://hprc.tamu.edu/wiki/HPRC:MobaXterm titan.tamu.edu Use titan.tamu.edu as Remote host name. -
A Usability Analysis of the Autopsy Forensic Browser
Proceedings of the Second International Symposium on Human Aspects of Information Security & Assurance (HAISA 2008) A Usability Analysis of the Autopsy Forensic Browser D.J. Bennett and P. Stephens Department of Computing (Academic), Canterbury Christ Church University, Canterbury, United Kingdom e-mail: {david.bennett, paul.stephens}@canterbury.ac.uk Abstract This paper reviews the usability of the Autopsy Forensic Browser. Two expert-based usability review techniques are used: Cognitive Walkthrough and Heuristic Evaluation. The results of the evaluation indicate that there are many areas where usability could be improved and these are classified into areas of eight overlapping areas. Examples from each area are presented, with suggestions as to methods to alleviate them. The paper concludes with a future work proposal to effect the changes suggested and retest the current and the replacement system with a user-based evaluation. Keywords Usability, Human-Computer Interaction, Interface Design, Autopsy Forensic Browser, The Sleuth Kit, Cognitive Walkthrough, Heuristic Evaluation 1. Introduction This paper reviews the usability of the Autopsy Forensic Browser tool. The reasoning for this is to improve future versions of the tool. In many ways forensic analysis tools are no different to any other mission critical software in terms of the need for usability. However, failure in usability in such tools could lead to outcomes which deny liberty to innocent persons, or enable criminals to continue with criminal activity should an investigation fail in some way. 1.1. Forensics and the Autopsy Forensic Browser Gottschalk et al. (2005) define computer forensics as the identification, preservation, investigation, and documentation of computer systems data used in criminal activity. -
GNU Coreutils Cheat Sheet (V1.00) Created by Peteris Krumins ([email protected], -- Good Coders Code, Great Coders Reuse)
GNU Coreutils Cheat Sheet (v1.00) Created by Peteris Krumins ([email protected], www.catonmat.net -- good coders code, great coders reuse) Utility Description Utility Description arch Print machine hardware name nproc Print the number of processors base64 Base64 encode/decode strings or files od Dump files in octal and other formats basename Strip directory and suffix from file names paste Merge lines of files cat Concatenate files and print on the standard output pathchk Check whether file names are valid or portable chcon Change SELinux context of file pinky Lightweight finger chgrp Change group ownership of files pr Convert text files for printing chmod Change permission modes of files printenv Print all or part of environment chown Change user and group ownership of files printf Format and print data chroot Run command or shell with special root directory ptx Permuted index for GNU, with keywords in their context cksum Print CRC checksum and byte counts pwd Print current directory comm Compare two sorted files line by line readlink Display value of a symbolic link cp Copy files realpath Print the resolved file name csplit Split a file into context-determined pieces rm Delete files cut Remove parts of lines of files rmdir Remove directories date Print or set the system date and time runcon Run command with specified security context dd Convert a file while copying it seq Print sequence of numbers to standard output df Summarize free disk space setuidgid Run a command with the UID and GID of a specified user dir Briefly list directory -
Forensic Toolkit (FTK)
Forensic Toolkit (FTK) User Guide | 1 AccessData Legal and Contact Information Document date: January 31, 2018 Legal Information ©2018 AccessData Group, Inc. All rights reserved. No part of this publication may be reproduced, photocopied, stored on a retrieval system, or transmitted without the express written consent of the publisher. AccessData Group, Inc. makes no representations or warranties with respect to the contents or use of this documentation, and specifically disclaims any express or implied warranties of merchantability or fitness for any particular purpose. Further, AccessData Group, Inc. reserves the right to revise this publication and to make changes to its content, at any time, without obligation to notify any person or entity of such revisions or changes. Further, AccessData Group, Inc. makes no representations or warranties with respect to any software, and specifically disclaims any express or implied warranties of merchantability or fitness for any particular purpose. Further, AccessData Group, Inc. reserves the right to make changes to any and all parts of AccessData software, at any time, without any obligation to notify any person or entity of such changes. You may not export or re-export this product in violation of any applicable laws or regulations including, without limitation, U.S. export regulations or the laws of the country in which you reside. AccessData Group, Inc. 588 West 400 South Suite 350 Lindon, UT 84042 USA AccessData Trademarks and Copyright Information The following are either registered trademarks or trademarks of AccessData Group, Inc. All other trademarks are the property of their respective owners. AccessData® AD Summation® Mobile Phone Examiner Plus® AccessData Certified Examiner® (ACE®) Discovery Cracker® MPE+ Velocitor™ AD AccessData™ Distributed Network Attack® Password Recovery Toolkit® AD eDiscovery® DNA® PRTK® AD RTK™ Forensic Toolkit® (FTK®) Registry Viewer® LawDrop® Summation® | 2 A trademark symbol (®, ™, etc.) denotes an AccessData Group, Inc. -
Extending the Sleuth Kit and Its Underlying Model for Pooled Storage File System Forensic Analysis
Extending The Sleuth Kit and its Underlying Model for Pooled Storage File System Forensic Analysis Fraunhofer Institute for Communication, Information Processing and Ergonomics Jan-Niclas Hilgert* [email protected] Martin Lambertz [email protected] Daniel Plohmann [email protected] © Fraunhofer FKIE Digital Forensic Analysis Slide 2 August 8th, 2017 © Cyber Analysis & Defense Department, Fraunhofer FKIE File Systems n Define how data is read from and written to a storage device n Utilize metadata to keep order of the data stored n File systems differ in many aspects EXT2FS HFS NTFS n Extensive background knowledge is required for a forensic analysis n But not always existent Slide 3 August 8th, 2017 © Cyber Analysis & Defense Department, Fraunhofer FKIE File System Forensic Analysis De-Facto Standard Model Physical Storage Media Sectors of Data Device Analysis Volume Volume n Universal model for a file system Analysis forensic analysis n Presented by Brian Carrier in 2005 File System n Consists of four interdependent steps File Analysis n Implemented in The Sleuth Kit Application Analysis Slide 4 August 8th, 2017 © Cyber Analysis & Defense Department, Fraunhofer FKIE File System Forensic Analysis De-Facto Standard Model Physical Storage Media Sectors of Data Device Analysis n Works great on a lot of established file systems Volume Volume Analysis EXT2FS NTFS File System HFS File Analysis n Problem: It hasn’t been reviewed or changed since its publication Application Analysis Slide -
Improving the Efficiency of Big Forensic Data Analysis Using Nosql
Improving the Efficiency of Big Forensic Data Analysis Using NoSQL Md Baitul Al Sadi Hayden Wimmer Lei Chen Kai Wang Department of Information Department of Information Department of Information Department of Computer Technology Technology Technology Science Georgia Southern University Georgia Southern University Georgia Southern University Georgia Southern University Statesboro, GA 30458, USA Statesboro, GA 30458, USA Statesboro, GA 30458, USA Statesboro, GA 30458, USA [email protected] [email protected] [email protected] [email protected] them in NoSQL (Not Only SQL) database. There is a variety of ABSTRACT tools available including Autopsy, EnCase, Foremost, FTK, The rapid growth of Internet of Things (IoT) makes the task for Registry Recon, PTK Forensics, The Sleuth Kit, The Coroner's digital forensic more difficult. At the same time, the data analyzing Toolkit, COFEE etc. to extract data from IoT devices. The technology is also developing in a feasible pace. Where traditional extracted data will be in an unstructured format, hence NoSQL is Structured Query Language (SQL) is not adequate to analyze the the best solution to analyze them. Here the document-oriented data in an unstructured and semi-structured format, Not only database program, MongoDB has been chosen to analyze the data Standard Query Language (NoSQL) unfastens the access to from Internet of Things (IoT). To our best knowledge this is pioneer analyzing the data of all format. The large volume of data of IoTs work in terms of using NoSQL and MongoDB for DF. turns into Big Data which just do not enhance the probability of attaining of evidence of an incident but make the investigation 2 BACKGROUND process more complex. -
Digital Forensics Tutorials – Analyzing a Disk Image in Kali Autopsy
Digital Forensics Tutorials – Analyzing a Disk Image in Kali Autopsy Explanation Section About Disk Analysis Once the proper steps have been taken to secure and verify the disk image, the actual contents of the image must be analyzed for suspicious or incriminating evidence. When looking at the contents of an image, it is necessary to not only look at the clearly visible contents such as folders on the desktop and images in user files, but the image must also be checked for hidden, encrypted, or deleted files. It is always better to assume that a suspect may have known that they were to be investigated and took steps to hide, delete, or otherwise make it difficult to find the information they had been storing on their USB or computer. About Kali Linux Sleuth Kit and Autopsy Autopsy and Sleuth Kit are open source digital investigation tools that run on Windows, Linux, OS X, and other Unix systems. Autopsy is the custom front-end application of Sleuth Kit. They can be used to analyze disk images and perform in-depth analysis of file systems (such as NTFS, FAT, Ext3) and several volume system types. Examiners and analysts can use the Autopsy graphical interface or the Sleuth Kit command line tools to conduct an investigation. In this case, we will be launching the Autopsy graphical interface via the Sleuth Kit command line. Autopsy/Sleuth Kit allow for an examiner to open a .dd or other type of disk image file, hash the file, and search for files and other information contained within the file.