Proceedings of Bsdcon ’03
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Oracle Solaris 11.4 Security Target, V1.3
Oracle Solaris 11.4 Security Target Version 1.3 February 2021 Document prepared by www.lightshipsec.com Oracle Security Target Document History Version Date Author Description 1.0 09 Nov 2020 G Nickel Update TOE version 1.1 19 Nov 2020 G Nickel Update IDR version 1.2 25 Jan 2021 L Turner Update TLS and SSH. 1.3 8 Feb 2021 L Turner Finalize for certification. Page 2 of 40 Oracle Security Target Table of Contents 1 Introduction ........................................................................................................................... 5 1.1 Overview ........................................................................................................................ 5 1.2 Identification ................................................................................................................... 5 1.3 Conformance Claims ...................................................................................................... 5 1.4 Terminology ................................................................................................................... 6 2 TOE Description .................................................................................................................... 9 2.1 Type ............................................................................................................................... 9 2.2 Usage ............................................................................................................................. 9 2.3 Logical Scope ................................................................................................................ -
Pf3e Index.Pdf
INDEX Note: Pages numbers followed by f, n, priority-based queues, 136–145 or t indicate figures, notes, and tables, match rule for queue assignment, respectively. 137–138 overview, 134–135 Symbols performance improvement, 136–137 # (hash mark), 13, 15 queuing for servers in DMZ, ! (logical NOT) operator, 42 142–144 setting up, 135–136 A on FreeBSD, 135–136 on NetBSD, 136 Acar, Can Erkin, 173 on OpenBSD, 135 ACK (acknowledgment) packets transitioning to priority and class-based bandwidth allocation, queuing system, 131–133 139–140 anchors, 35–36 HFSC algorithm, 124, 126, 142 authpf program, 61, 63 priority queues, 132, 137–138 listing current contents of, 92 two-priority configuration, loading rules into, 92 120–121, 120n1 manipulating contents, 92 adaptive.end value, 188 relayd daemon, 74 adaptive firewalls, 97–99 restructuring rule set with, 91–94 adaptive.start value, 188 tagging to help policy routing, 93 advbase parameter, 153–154 ancontrol command, 46n1 advskew parameter, 153–154, 158–159 antispoof tool, 27, 193–195, 194f aggressive value, 192 ARP balancing, 151, 157–158 ALTQ (alternate queuing) framework, atomic rule set load, 21 9, 133–145, 133n2 authpf program, 59–63, 60 basic concepts, 134 basic authenticating gateways, class-based bandwidth allocation, 60–62 139–140 public networks, 62–63 overview, 135 queue definition, 139–140 tying queues into rule set, 140 B handling unwanted traffic, 144–145 bandwidth operating system-based queue actual available, 142–143 assignments, 145 class-based allocation of, 139–140 overloading to -
Cryptanalysis of the Random Number Generator of the Windows Operating System
Cryptanalysis of the Random Number Generator of the Windows Operating System Leo Dorrendorf School of Engineering and Computer Science The Hebrew University of Jerusalem 91904 Jerusalem, Israel [email protected] Zvi Gutterman Benny Pinkas¤ School of Engineering and Computer Science Department of Computer Science The Hebrew University of Jerusalem University of Haifa 91904 Jerusalem, Israel 31905 Haifa, Israel [email protected] [email protected] November 4, 2007 Abstract The pseudo-random number generator (PRNG) used by the Windows operating system is the most commonly used PRNG. The pseudo-randomness of the output of this generator is crucial for the security of almost any application running in Windows. Nevertheless, its exact algorithm was never published. We examined the binary code of a distribution of Windows 2000, which is still the second most popular operating system after Windows XP. (This investigation was done without any help from Microsoft.) We reconstructed, for the ¯rst time, the algorithm used by the pseudo- random number generator (namely, the function CryptGenRandom). We analyzed the security of the algorithm and found a non-trivial attack: given the internal state of the generator, the previous state can be computed in O(223) work (this is an attack on the forward-security of the generator, an O(1) attack on backward security is trivial). The attack on forward-security demonstrates that the design of the generator is flawed, since it is well known how to prevent such attacks. We also analyzed the way in which the generator is run by the operating system, and found that it ampli¯es the e®ect of the attacks: The generator is run in user mode rather than in kernel mode, and therefore it is easy to access its state even without administrator privileges. -
Implementing Ipv6: Experiences at KAME Project
Implementing IPv6: experiences at KAME project Jun-ichiro Hagino, IIJ research laboratory itojun@{iijlab.net,kame.net} Outline What is IPv6, and why IPv6 (brief summary) What is KAME project Some technical insights observed at KAME Implmentation status What are the TODOs, issues from both specification/implementation What is IPv6? Expansion of address space - 32bit -> 128bit 32bit: 4.3 billion nodes maximum not sufficient, blocking new IP-based applications from appearing 128bit: 3.4 x 10^38 nodes maximum Make new technologies mandatory IPv4: designed in 1970’s IPv6: designed in 1990’s autoconfiguration, multicast, security, ... Why? - IPv4 address space is filled up, NAT is killing us all When? - Already there, so you should How? - (next slide) How to operate IPv6? IPv6 is "IP with bigger address space", almost no difference with IPv4 bigger address space makes a huge difference Base spec NAT-free 128bit address, simpler base header, extensible header format Enables many future application deployment and uses Routing - OSPFv3, RIPng, BGP4+ QoS - diffserv, RSVP (separate effort from IPv6 itself) more friendly than IPv4 Mobility - mobile-ip6 No foreign agent necessary Security - IPsec (separate effort from IPv6 itself) A "fully conformant IPv6 implementation" must have IPsec code Autoconfiguration stateless autoconf, DHCPv6 Multicast - PIM, MLD (= IGMP) Applications - HTTP, FTP, VoIP, whatever you do with IPv4 New applications would appear when IPv6 hits the critical mass Problem we had in 1995... IPv6 specification is out, but there’s -
Vulnerabilities of the Linux Random Number Generator
Black Hat 2006 Open to Attack Vulnerabilities of the Linux Random Number Generator Zvi Gutterman Chief Technology Officer with Benny Pinkas Tzachy Reinman Zvi Gutterman CTO, Safend Previously a chief architect in the IP infrastructure group for ECTEL (NASDAQ:ECTX) and an officer in the Israeli Defense Forces (IDF) Elite Intelligence unit. Master's and Bachelor's degrees in Computer Science from the Israeli Institute of Technology. Ph.D. candidate at the Hebrew University of Jerusalem, focusing on security, network protocols, and software engineering. - Proprietary & Confidential - Safend Safend is a leading provider of innovative endpoint security solutions that protect against corporate data leakage and penetration via physical and wireless ports. Safend Auditor and Safend Protector deliver complete visibility and granular control over all enterprise endpoints. Safend's robust, ultra- secure solutions are intuitive to manage, almost impossible to circumvent, and guarantee connectivity and productivity, without sacrificing security. For more information, visit www.safend.com. - Proprietary & Confidential - Pseudo-Random-Number-Generator (PRNG) Elementary and critical component in many cryptographic protocols Usually: “… Alice picks key K at random …” In practice looks like random.nextBytes(bytes); session_id = digest.digest(bytes); • Which is equal to session_id = md5(get next 16 random bytes) - Proprietary & Confidential - If the PRNG is predictable the cryptosystem is not secure Demonstrated in - Netscape SSL [GoldbergWagner 96] http://www.cs.berkeley.edu/~daw/papers/ddj-netscape.html Apache session-id’s [GuttermanMalkhi 05] http://www.gutterman.net/publications/2005/02/hold_your_sessions_an_attack_o.html - Proprietary & Confidential - General PRNG Scheme 0 0 01 Stateseed 110 100010 Properties: 1. Pseudo-randomness Output bits are indistinguishable from uniform random stream 2. -
Analysis of Entropy Usage in Random Number Generators
DEGREE PROJECT IN THE FIELD OF TECHNOLOGY ENGINEERING PHYSICS AND THE MAIN FIELD OF STUDY COMPUTER SCIENCE AND ENGINEERING, SECOND CYCLE, 30 CREDITS STOCKHOLM, SWEDEN 2017 Analysis of Entropy Usage in Random Number Generators KTH ROYAL INSTITUTE OF TECHNOLOGY SCHOOL OF COMPUTER SCIENCE AND COMMUNICATION Analysis of Entropy Usage in Random Number Generators JOEL GÄRTNER Master in Computer Science Date: September 16, 2017 Supervisor: Douglas Wikström Examiner: Johan Håstad Principal: Omegapoint Swedish title: Analys av entropianvändning i slumptalsgeneratorer School of Computer Science and Communication i Abstract Cryptographically secure random number generators usually require an outside seed to be initialized. Other solutions instead use a continuous entropy stream to ensure that the internal state of the generator always remains unpredictable. This thesis analyses four such generators with entropy inputs. Furthermore, different ways to estimate entropy is presented and a new method useful for the generator analy- sis is developed. The developed entropy estimator performs well in tests and is used to analyse en- tropy gathered from the different generators. Furthermore, all the analysed generators exhibit some seemingly unintentional behaviour, but most should still be safe for use. ii Sammanfattning Kryptografiskt säkra slumptalsgeneratorer behöver ofta initialiseras med ett oförutsägbart frö. En annan lösning är att istället konstant ge slumptalsgeneratorer entropi. Detta gör det möjligt att garantera att det interna tillståndet i generatorn hålls oförutsägbart. I den här rapporten analyseras fyra sådana generatorer som matas med entropi. Dess- utom presenteras olika sätt att skatta entropi och en ny skattningsmetod utvecklas för att användas till analysen av generatorerna. Den framtagna metoden för entropiskattning lyckas bra i tester och används för att analysera entropin i de olika generatorerna. -
Trusted Platform Module ST33TPHF20SPI FIPS 140-2 Security Policy Level 2
STMICROELECTRONICS Trusted Platform Module ST33TPHF20SPI ST33HTPH2E28AAF0 / ST33HTPH2E32AAF0 / ST33HTPH2E28AAF1 / ST33HTPH2E32AAF1 ST33HTPH2028AAF3 / ST33HTPH2032AAF3 FIPS 140-2 Security Policy Level 2 Firmware revision: 49.00 / 4A.00 HW version: ST33HTPH revision A Date: 2017/07/19 Document Version: 01-11 NON-PROPRIETARY DOCUMENT FIPS 140-2 SECURITY POLICY NON-PROPRIETARY DOCUMENT Page 1 of 43 Table of Contents 1 MODULE DESCRIPTION .................................................................................................................... 3 1.1 DEFINITION ..................................................................................................................................... 3 1.2 MODULE IDENTIFICATION ................................................................................................................. 3 1.2.1 AAF0 / AAF1 ......................................................................................................................... 3 1.2.2 AAF3 ..................................................................................................................................... 4 1.3 PINOUT DESCRIPTION ...................................................................................................................... 6 1.4 BLOCK DIAGRAMS ........................................................................................................................... 8 1.4.1 HW block diagram ............................................................................................................... -
Implement an Ipv6 Router Using KAME Under Freebsd
在 FreeBSD 下利用 KAME 實做一個 IPv6 路由器 Implement An IPv6 Router Using KAME under FreeBSD 梁家瑋 Liang Jia-Wei 高雄師範大學資訊教育所 [email protected] KAME 計劃是日本的一些公司團隊所共同 ABSTRACT 參與的一個計劃,而這個軟件主要是提供 BSD(包括 FreeBSD、NetBSD 等)作業系統一些 With IPv4(Internet Protocol version 4) , it has 額外的功能,包括了 IPv6、IPSec 以及一些網路 been found the address space provided can’t sustain the growing number hosts connected to the 流量控制應用管理的功能。在此篇論文我們最 Internet. IPv6(Internet Protocol version 6) has 主要的目的是利用 KAME 來實作一個 Router, been designed to resolve scalability issues of the 透過這台 Router,可以使 IPv4 網路與 IPv6 網路 Internet address space. There are a lot of 串聯起來,我們只需要一台 PC 來安裝 FreeBSD advantages in using IPv6. For example, it’s not 並且應用 KAME 來達成,這對於過渡時期還沒 necessary for NAT(Network Address Transmission) 有獨立 IPv6 機器的機構來說是很有幫助的。 server , and the number of IP address is enough. In this way , it’s more convenient to deliver IP 關鍵字: IPv6, FreeBSD,轉換機制,KAME。 addresses to mobile devices , such as notebook , PDA , cell phone , etc. Nowadays , enterprises , 1. Introduction schools , people use computer network in IPv4. It is important for the IPv4/IPv6 transition Nowadays,more and more electric mechanisms.There are various translation equipments need IP address to support internet strategies can be broadly divided into dual stack , access , such as notebooks , cell phones, PDAs. tunneling and translation , and they will be IPv6 will solve the problem of IP address shortage. mentioned later. IPv6 is a new version of IP which is designed to be an evolutionary step from IPv4. It is a natural KAME Project is a joint effort to create increment to IPv4. -
Dev/Random and FIPS
/dev/random and Your FIPS 140-2 Validation Can Be Friends Yes, Really Valerie Fenwick Manager, Solaris Cryptographic Technologies team Oracle May 19, 2016 Photo by CGP Grey, http://www.cgpgrey.com/ Creative Commons Copyright © 2016, Oracle and/or its affiliates. All rights reserved. Not All /dev/random Implementations Are Alike • Your mileage may vary – Even across OS versions – Solaris 7‘s /dev/random is nothing like Solaris 11’s – Which look nothing like /dev/random in Linux, OpenBSD, MacOS, etc – Windows gets you a whole ‘nother ball of wax… • No common ancestry – Other than concept Copyright © 2016, Oracle and/or its affiliates. All rights reserved 3 /dev/random vs /dev/urandom • On most OSes, /dev/urandom is a PRNG (Pseudo-Random Number Generator) – In some, so is their /dev/random • Traditionally, /dev/urandom will never block – /dev/random will block • For fun, on some OSes /dev/urandom is a link to /dev/random Copyright © 2016, Oracle and/or its affiliates. All rights reserved 4 FreeBSD: /dev/random • /dev/urandom is a link to /dev/random • Only blocks until seeded • Based on Fortuna Copyright © 2016, Oracle and/or its affiliates. All rights reserved 5 OpenBSD: /dev/random • Called /dev/arandom • Does not block • Formerly based on ARCFOUR – Now based on ChaCha20 – C API still named arc4random() Copyright © 2016, Oracle and/or its affiliates. All rights reserved 6 MacOS: /dev/random • /dev/urandom is a link to /dev/random • 160-bit Yarrow PRNG, uses SHA1 and 3DES Copyright © 2016, Oracle and/or its affiliates. All rights reserved 7 Linux: /dev/random • Blocks when entropy is depleted • Has a separate non-blocking /dev/urandom Copyright © 2016, Oracle and/or its affiliates. -
Linux Random Number Generator
Not-So-Random Numbers in Virtualized Linux and the Whirlwind RNG Adam Everspaugh, Yan Zhai, Robert Jellinek, Thomas Ristenpart, Michael Swift Department of Computer Sciences University of Wisconsin-Madison {ace, yanzhai, jellinek, rist, swift}@cs.wisc.edu Abstract—Virtualized environments are widely thought to user-level cryptographic processes such as Apache TLS can cause problems for software-based random number generators suffer a catastrophic loss of security when run in a VM that (RNGs), due to use of virtual machine (VM) snapshots as is resumed multiple times from the same snapshot. Left as an well as fewer and believed-to-be lower quality entropy sources. Despite this, we are unaware of any published analysis of the open question in that work is whether reset vulnerabilities security of critical RNGs when running in VMs. We fill this also affect system RNGs. Finally, common folklore states gap, using measurements of Linux’s RNG systems (without the that software entropy sources are inherently worse on virtu- aid of hardware RNGs, the most common use case today) on alized platforms due to frequent lack of keyboard and mouse, Xen, VMware, and Amazon EC2. Despite CPU cycle counters interrupt coalescing by VM managers, and more. Despite providing a significant source of entropy, various deficiencies in the design of the Linux RNG makes its first output vulnerable all this, to date there have been no published measurement during VM boots and, more critically, makes it suffer from studies evaluating the security of Linux (or another common catastrophic reset vulnerabilities. We show cases in which the system RNG) in modern virtualized environments. -
BSD Intro Lecture
Short history • Based on: http://www.levenez.com/unix/ • 1978 – BSD (Barkeley software distribution) Based on unix system developed by Bell. • 1991 – 386BSD – BSD port to Intel (Based on 4.3BSD). • 1991 – Linux based on Minix. • 1993 – FreeBSD and NetBSD Based on 386BSD. • 1995 - OpenBSD splits from NetBSD. • 2001 – Apple’s Darwin, based on FreeBSD. • Latest releases: 5.3, 4.11. • The most popular of the *BSDs. • Historically aimed for maximum. performance on X86. Now supports most of the popular hardware platforms. • Biggest installations: Yahoo servers, ftp.cdrom.com, www.netcraft.com. • “Of course it runs NetBSD” • Last version: NetBSD 2.0. • Aims for supporting as many architectures possible. • Portable design. • 40 supported architectures. • www.openbsd.org • Current version: OpenBSD 3.6. • “Try to be the #1 most secure operating system“. • “Secure by default”. • Based on Canada – is not restricted by US export laws. • developer.apple.com/darwin/projects/darwin/ • The operating system behind Apple’s MAC OS X. • Based on FreeBSD. • Apple’s cool GUI, on top of a reliable Open source unix. • Runs on PowerPC based Macintosh. • Version for X86 is also available. Licensing Issues • Linux – GPL Must publish your source code if your code is based on a GPLd software. • *BSD - BSD license. • Do what ever you want, just give us credit. • Poul Henning Kamp - Beerware license Do what ever you want, just buy me beer when we meet. FreeBSD – The people behind • FreeBSD Core Team – The board of directors. • FreeBSD Committers – The programmers. • Release Engineering Teams • Documentation engineering team • Port management team. • Donations Team. FreeBSD – The people behind cont’ • Technical Review Board. -
Analysis of the Linux Random Number Generator
Analysis of the Linux Random Number Generator Zvi Gutterman Benny Pinkas Safend and The Hebrew University of Jerusalem University of Haifa Tzachy Reinman The Hebrew University of Jerusalem March 6, 2006 Abstract Linux is the most popular open source project. The Linux random number generator is part of the kernel of all Linux distributions and is based on generating randomness from entropy of operating system events. The output of this generator is used for almost every security protocol, including TLS/SSL key generation, choosing TCP sequence numbers, and file system and email encryption. Although the generator is part of an open source project, its source code (about 2500 lines of code) is poorly documented, and patched with hundreds of code patches. We used dynamic and static reverse engineering to learn the operation of this generator. This paper presents a description of the underlying algorithms and exposes several security vulnerabilities. In particular, we show an attack on the forward security of the generator which enables an adversary who exposes the state of the generator to compute previous states and outputs. In addition we present a few cryptographic flaws in the design of the generator, as well as measurements of the actual entropy collected by it, and a critical analysis of the use of the generator in Linux distributions on disk-less devices. 1 Introduction Randomness is a crucial resource for cryptography, and random number generators are therefore critical building blocks of almost all cryptographic systems. The security analysis of almost any system assumes a source of random bits, whose output can be used, for example, for the purpose of choosing keys or choosing random nonces.