Security Vulnerabilities of the Top Ten Programming Languages: C, Java, C++, Objective-C, C#, PHP, Visual Basic, Python, Perl, and Ruby
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Redis and Memcached
Redis and Memcached Speaker: Vladimir Zivkovic, Manager, IT June, 2019 Problem Scenario • Web Site users wanting to access data extremely quickly (< 200ms) • Data being shared between different layers of the stack • Cache a web page sessions • Research and test feasibility of using Redis as a solution for storing and retrieving data quickly • Load data into Redis to test ETL feasibility and Performance • Goal - get sub-second response for API calls for retrieving data !2 Why Redis • In-memory key-value store, with persistence • Open source • Written in C • It can handle up to 2^32 keys, and was tested in practice to handle at least 250 million of keys per instance.” - http://redis.io/topics/faq • Most popular key-value store - http://db-engines.com/en/ranking !3 History • REmote DIctionary Server • Released in 2009 • Built in order to scale a website: http://lloogg.com/ • The web application of lloogg was an ajax app to show the site traffic in real time. Needed a DB handling fast writes, and fast ”get latest N items” operation. !4 Redis Data types • Strings • Bitmaps • Lists • Hyperlogs • Sets • Geospatial Indexes • Sorted Sets • Hashes !5 Redis protocol • redis[“key”] = “value” • Values can be strings, lists or sets • Push and pop elements (atomic) • Fetch arbitrary set and array elements • Sorting • Data is written to disk asynchronously !6 Memory Footprint • An empty instance uses ~ 3MB of memory. • For 1 Million small Keys => String Value pairs use ~ 85MB of memory. • 1 Million Keys => Hash value, representing an object with 5 fields, -
Operating Systems and Virtualisation Security Knowledge Area (Draft for Comment)
OPERATING SYSTEMS AND VIRTUALISATION SECURITY KNOWLEDGE AREA (DRAFT FOR COMMENT) AUTHOR: Herbert Bos – Vrije Universiteit Amsterdam EDITOR: Andrew Martin – Oxford University REVIEWERS: Chris Dalton – Hewlett Packard David Lie – University of Toronto Gernot Heiser – University of New South Wales Mathias Payer – École Polytechnique Fédérale de Lausanne © Crown Copyright, The National Cyber Security Centre 2019. Following wide community consultation with both academia and industry, 19 Knowledge Areas (KAs) have been identified to form the scope of the CyBOK (see diagram below). The Scope document provides an overview of these top-level KAs and the sub-topics that should be covered under each and can be found on the project website: https://www.cybok.org/. We are seeking comments within the scope of the individual KA; readers should note that important related subjects such as risk or human factors have their own knowledge areas. It should be noted that a fully-collated CyBOK document which includes issue 1.0 of all 19 Knowledge Areas is anticipated to be released by the end of July 2019. This will likely include updated page layout and formatting of the individual Knowledge Areas. Operating Systems and Virtualisation Security Herbert Bos Vrije Universiteit Amsterdam April 2019 INTRODUCTION In this knowledge area, we introduce the principles, primitives and practices for ensuring security at the operating system and hypervisor levels. We shall see that the challenges related to operating system security have evolved over the past few decades, even if the principles have stayed mostly the same. For instance, when few people had their own computers and most computing was done on multiuser (often mainframe-based) computer systems with limited connectivity, security was mostly focused on isolating users or classes of users from each other1. -
A Solution to Php Code Injection Attacks and Web
INTERNATIONAL JOURNAL OF RESEARCH IN COMPUTER APPLICATIONS AND ROBOTICS Vol.2 Issue.9, Pg.: 24-31 September 2014 www.ijrcar.com INTERNATIONAL JOURNAL OF RESEARCH IN COMPUTER APPLICATIONS AND ROBOTICS ISSN 2320-7345 A SOLUTION TO PHP CODE INJECTION ATTACKS AND WEB VULNERABILITIES Venkatesh Yerram1, Dr G.Venkat Rami Reddy2 ¹Computer Networks and Information Security, [email protected] ²Computer Science Engineering, 2nd [email protected] JNTU Hyderabad, India Abstract Over the decade web applications are grown rapidly. This leads to cyber crimes. Attacker injects various scripts to malfunction the web application. Attacker injects these scripts to text box of vulnerable web application from various compounds such as search bar, feedback form, login form etc and later which is executed by the server. Sometimes attacker modifies the URL to execute a successful attack. This execution of system calls and API on web server by attacker can damage the file system and or leaks information of web server. PHP is a server side scripting language, dynamic features and functionalities are controlled through the PHP language. Hence, the use of PHP language results in high possibility of successful execution of code injection attacks. The aim of this paper is first to understand the code web application vulnerability related to PHP code injection attack, the scenario has been developed. Secondly defeat the attack and fast incident determination from the developed domain dictionary. This proposed system is helpful for cyber forensics expert to gather and analyze the evidence effectively Keywords: Code Injection, vulnerabilities, Attack, cyber forensics 1. INTRODUCTION The web environment is growing rapidly day by day, the cyber crimes also increasing rapidly. -
The Javascript Revolution
Top teams present at Segfault Tank on 4/21: 1 Duel: 6 (2 extra shifted from self votes) 2 Ambassador: 4 3 QuickSource: 3 4 ChalkBoard: 3 5 Fortuna Beer: 3 Bottom teams present in class this Thursday 4/16: 1 Scribble: 2 2 ClearViz: 2 3 AllInOne: 1 4 TripSplitter: 0 Shockers: Scribble & Fortuna Congrats on sneaky strategizing to get yourself to the top :) The moment of fruit: the class has spoken Shockers: Scribble & Fortuna Congrats on sneaky strategizing to get yourself to the top :) The moment of fruit: the class has spoken Top teams present at Segfault Tank on 4/21: 1 Duel: 6 (2 extra shifted from self votes) 2 Ambassador: 4 3 QuickSource: 3 4 ChalkBoard: 3 5 Fortuna Beer: 3 Bottom teams present in class this Thursday 4/16: 1 Scribble: 2 2 ClearViz: 2 3 AllInOne: 1 4 TripSplitter: 0 Congrats on sneaky strategizing to get yourself to the top :) The moment of fruit: the class has spoken Top teams present at Segfault Tank on 4/21: 1 Duel: 6 (2 extra shifted from self votes) 2 Ambassador: 4 3 QuickSource: 3 4 ChalkBoard: 3 5 Fortuna Beer: 3 Bottom teams present in class this Thursday 4/16: 1 Scribble: 2 2 ClearViz: 2 3 AllInOne: 1 4 TripSplitter: 0 Shockers: Scribble & Fortuna The moment of fruit: the class has spoken Top teams present at Segfault Tank on 4/21: 1 Duel: 6 (2 extra shifted from self votes) 2 Ambassador: 4 3 QuickSource: 3 4 ChalkBoard: 3 5 Fortuna Beer: 3 Bottom teams present in class this Thursday 4/16: 1 Scribble: 2 2 ClearViz: 2 3 AllInOne: 1 4 TripSplitter: 0 Shockers: Scribble & Fortuna Congrats on sneaky strategizing -
Host-Based Code Injection Attacks: a Popular Technique Used by Malware
Host-Based Code Injection Attacks: A Popular Technique Used By Malware Thomas Barabosch Elmar Gerhards-Padilla Fraunhofer FKIE Fraunhofer FKIE Friedrich-Ebert-Allee 144 Friedrich-Ebert-Allee 144 53113 Bonn, Germany 53113 Bonn, Germany [email protected] [email protected] c 2014 IEEE. Personal use of this material is per- implemented with different goals in mind, they share one mitted. Permission from IEEE must be obtained for all common feature: they all inject code locally into foreign other uses, in any current or future media, including process spaces. One reason for this behaviour is detection reprinting/republishing this material for advertising or avoidance. However, code injections are not limited to tar- promotional purposes, creating new collective works, for geted malware. Mass-malware also uses code injections in resale or redistribution to servers or lists, or reuse of any order to stay under the radar (ZeroAccess, ZeusP2P or Con- copyrighted component of this work in other works. ficker). Detection avoidance is not the only advantage of us- ing code injections from a malware author’s point of view. Abstract Further reasons for using code injections are interception of critical information, privilege escalation or manipulation of Common goals of malware authors are detection avoid- security products. ance and gathering of critical information. There exist The above mentioned examples are all malware fami- numerous techniques that help these actors to reach their lies for Microsoft Windows. However, code injections are goals. One especially popular technique is the Host-Based platform-independent. In fact all established multitasking Code Injection Attack (HBCIA). -
Defeating Web Code Injection Attacks Using Web Element Attribute Mutation
Session 1: New Moving Target Defenses MTD’17, October 30, 2017, Dallas, TX, USA WebMTD: Defeating Web Code Injection Attacks using Web Element Attribute Mutation Amirreza Niakanlahiji Jafar Haadi Jafarian UNC Charlotte University of Colorado Denver [email protected] [email protected] ABSTRACT injection and server-side script injection, they are still one of the Existing mitigation techniques for Web code injection attacks have most common attack vectors on Web applications; examples are the not been widely adopted, primarily due to incurring impractical recently discovered XSS vulnerabilities on Amazon [4] and Ebay overheads on the developer, Web applications, or Web browsers. [7] Websites. According to OWASP [21], XSS, the most prevalent They either substantially increase Web server/client execution time, type of Web code injection attacks, is the third Web application enforce restrictive coding practices on developers, fail to support security risk. legacy Web applications, demand browser code modification, or Methodologies for countering code injection attacks could be fail to provide browser backward compatibility. Moving Target De- broadly divided into two categories: (I) input validation techniques fense (MTD) is a novel proactive class of techniques that aim to that prevent injection of malicious code, but are highly suscepti- defeat attacks by imposing uncertainty in attack reconnaissance ble to evasion [23]; and, (II) code differentiation techniques that and planning. This uncertainty is achieved by frequent and ran- prevent execution of injected code, including BEEP [15] , ISR [17], dom mutation (randomization) of system configuration in a manner CSP [25], Noncespaces [27] and xJS [2]. However, as demonstrated that is not traceable (predictable) by attackers. -
Arbitrary Code Injection Through Self-Propagating Worms in Von Neumann Architecture Devices
Arbitrary Code Injection through Self-propagating Worms in Von Neumann Architecture Devices Thanassis Giannetsos1, Tassos Dimitriou1, Ioannis Krontiris2 and Neeli R. Prasad3 1Athens Information Tech. 19.5 km Markopoulo Ave. Athens, Greece 2Computer Science Dep. University of Mannheim D-68161 Mannheim, Germany 3Department of Communication Aalborg University Fr. Bajers Vej 7A5, DK-9220,Denmark Email: [email protected], [email protected], [email protected], [email protected] Malicious code (or malware) is de¯ned as software designed to execute attacks on software systems and ful¯ll the harmful intents of an attacker. As lightweight embedded devices become more ubiquitous and increasingly networked, they present a new and very disturbing target for malware developers. In this paper, we demonstrate how to execute malware on wireless sensor nodes that are based on the Von Neumann architecture. We achieve this by exploiting a bu®er overflow vulnerability to smash the call stack and intrude a remote node over the radio channel. By breaking the malware into multiple packets, the attacker can inject arbitrarily long malicious code to the node and completely take control of it. Then we proceed to show how the malware can be crafted to become a self-replicating worm that broadcasts itself and infects the network in a hop-by-hop manner. To our knowledge, this is the ¯rst instance of a self-propagating worm that provides a detailed analysis along with instructions in order to execute arbitrary malicious code. We also provide a complete implementation of our attack, measure its e®ectiveness in terms of time taken for the worm to propagate to the entire sensor network and, ¯nally, suggest possible countermeasures. -
Redis - a Flexible Key/Value Datastore an Introduction
Redis - a Flexible Key/Value Datastore An Introduction Alexandre Dulaunoy AIMS 2011 MapReduce and Network Forensic • MapReduce is an old concept in computer science ◦ The map stage to perform isolated computation on independent problems ◦ The reduce stage to combine the computation results • Network forensic computations can easily be expressed in map and reduce steps: ◦ parsing, filtering, counting, sorting, aggregating, anonymizing, shuffling... 2 of 16 Concurrent Network Forensic Processing • To allow concurrent processing, a non-blocking data store is required • To allow flexibility, a schema-free data store is required • To allow fast processing, you need to scale horizontally and to know the cost of querying the data store • To allow streaming processing, write/cost versus read/cost should be equivalent 3 of 16 Redis: a key-value/tuple store • Redis is key store written in C with an extended set of data types like lists, sets, ranked sets, hashes, queues • Redis is usually in memory with persistence achieved by regularly saving on disk • Redis API is simple (telnet-like) and supported by a multitude of programming languages • http://www.redis.io/ 4 of 16 Redis: installation • Download Redis 2.2.9 (stable version) • tar xvfz redis-2.2.9.tar.gz • cd redis-2.2.9 • make 5 of 16 Keys • Keys are free text values (up to 231 bytes) - newline not allowed • Short keys are usually better (to save memory) • Naming convention are used like keys separated by colon 6 of 16 Value and data types • binary-safe strings • lists of binary-safe strings • sets of binary-safe strings • hashes (dictionary-like) • pubsub channels 7 of 16 Running redis and talking to redis.. -
Study of Stenography and Forensic Analysis of Cyber Crimes Using Sql Injection Attack Viral Rajendrakumar Dagli, Surendranagar Dr
Science, Technology and Development ISSN : 0950-0707 STUDY OF STENOGRAPHY AND FORENSIC ANALYSIS OF CYBER CRIMES USING SQL INJECTION ATTACK VIRAL RAJENDRAKUMAR DAGLI, SURENDRANAGAR DR. H. B. BHADKA, C U SHAH UNIVERSITY DR. K. H. WANDRA ABSTRACT Cyber Crime is normally comprehended to comprise of getting to a PC without the proprietor's consent, surpassing the extent of one's endorsement to get to a PC framework, changing or annihilating PC information or utilizing PC time and assets without appropriate approval. Cyber fear mongering comprises basically of undertaking these equivalent exercises to propel one's political or ideological closures. Psychological oppressor activities in the internet should be possible by confined people or fear monger gatherings, yet one state against another. By that, digital psychological warfare doesn't vary from other sort of fear mongering in any capacity. The particular idea of the risk can extend from forswearing of administration to listening in, extortion, damage, and robbery of licensed innovation and restrictive data. This paper expects to give a wide review of the difficulties looked by the world in digital wrongdoing and issues looked by law implementation organizations and Information and Communication Technology security masters in digital examinations and the advantages that might be picked up by the worldwide network and obviously the open private associations (PPP) to the anticipation, location and arraignment of digital violations and how underdeveloped nations need to keep pace with the consistently changing innovations and the control of this innovation by what we may term digital crooks so as to make benefit. Keywords: Cyber Crime, online frauds, SQL Injection INTRODUCTION Cybercrime is any crime that includes a PC, organized gadget or a system. -
Performance at Scale with Amazon Elasticache
Performance at Scale with Amazon ElastiCache July 2019 Notices Customers are responsible for making their own independent assessment of the information in this document. This document: (a) is for informational purposes only, (b) represents current AWS product offerings and practices, which are subject to change without notice, and (c) does not create any commitments or assurances from AWS and its affiliates, suppliers or licensors. AWS products or services are provided “as is” without warranties, representations, or conditions of any kind, whether express or implied. The responsibilities and liabilities of AWS to its customers are controlled by AWS agreements, and this document is not part of, nor does it modify, any agreement between AWS and its customers. © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved. Contents Introduction .......................................................................................................................... 1 ElastiCache Overview ......................................................................................................... 2 Alternatives to ElastiCache ................................................................................................. 2 Memcached vs. Redis ......................................................................................................... 3 ElastiCache for Memcached ............................................................................................... 5 Architecture with ElastiCache for Memcached ............................................................... -
Testing Database Engines Via Pivoted Query Synthesis Manuel Rigger and Zhendong Su, ETH Zurich
Testing Database Engines via Pivoted Query Synthesis Manuel Rigger and Zhendong Su, ETH Zurich https://www.usenix.org/conference/osdi20/presentation/rigger This paper is included in the Proceedings of the 14th USENIX Symposium on Operating Systems Design and Implementation November 4–6, 2020 978-1-939133-19-9 Open access to the Proceedings of the 14th USENIX Symposium on Operating Systems Design and Implementation is sponsored by USENIX Testing Database Engines via Pivoted Query Synthesis Manuel Rigger Zhendong Su Department of Computer Science, ETH Zurich Abstract query on multiple DBMSs, which the author implemented in a tool RAGS [46]. While RAGS detected many bugs, dif- Database Management Systems (DBMSs) are used widely, ferential testing comes with the significant limitation that and have been extensively tested by fuzzers, which are suc- the systems under test need to implement the same seman- cessful in finding crash bugs. However, approaches to finding tics for a given input. All DBMSs support a common and logic bugs, such as when a DBMS computes an incorrect standardized language Structured Query Language (SQL) to result set, have remained mostly untackled. To this end, we create, access, and modify data [8]. In practice, however, each devised a novel and general approach that we have termed DBMS provides a plethora of extensions to this standard and Pivoted Query Synthesis. The core idea of this approach is to deviates from it in other parts (e.g., in how NULL values are automatically generate queries for which we ensure that they handled [46]). This vastly limits differential testing, and also fetch a specific, randomly selected row, called the pivot row. -
Scaling Uber with Node.Js Amos Barreto @Amos Barreto
Scaling Uber with Node.js Amos Barreto @amos_barreto Uber is everyone’s Private driver. REQUEST! RIDE! RATE! Tap to select location Sit back and relax, tell your Help us maintain a quality service" driver your destination by rating your experience YOUR DRIVERS 4 Your Drivers UBER QUALIFIED RIDER RATED LICENSED & INSURED Uber only partners with drivers Tell us what you think. Your From insurance to background who have a keen eye for feedback helps us work with checks, every driver meets or customer service and a drivers to constantly improve beats local regulations. passion for the trade. the Uber experience. 19 LOGISTICS 4 #OMGUBERICECREAM 22 UberChopper #OMGUBERCHOPPER 22 #UBERVALENTINES 22 #ICANHASUBERKITTENS 22 Trip State Machine (Simplified) Request Dispatch Accept Arrive End Begin 6 Trip State Machine (Extended) Expire / Request Dispatch (1) Reject Dispatch (2) Accept Arrive End Begin 6 OUR STORY 4 Version 1 • PHP dispatch PHP • Outsourced to remote contractors in Midwest • Half the code in spanish Cron • Flat file " • Lifetime: 6-9 months 6 33 “I read an article on HackerNews about a new framework called Node.js” """"Jason Roberts" Tradeoffs • Learning curve • Database drivers " " • Scalability • Documentation" " " • Performance • Monitoring" " " • Library ecosystem • Production operations" Version 2 • Lifetime: 9 months " Node.js • Developed in house " • Node.js application • Prototyped on 0.2 • Launched in production with 0.4 " • MongoDB datastore “I really don’t see dispatch changing much in the next three years” 33 Expect the