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DOSUG 2015 - Assimilation Overview

Alan Robertson
September 01, 2015

DOSUG 2015 - Assimilation Overview

http://assimilationsystems.com/events/dosug-assimilation-overview-2015/
The statistics on system management are alarming – 30% of all break-ins come through systems people have lost track of, 90% of all organizations have failures of services they aren’t monitoring, 80% of all organizations are unable to keep their systems in compliance after getting them there initially, and 30% admit that they rarely start monitoring until after they have a problem, 30% of all systems are doing nothing useful, and admins of larger sites often don’t know the inter-dependencies between systems, services, and switches.

The Assimilation System Management Suite helps IT organizations manage and reduce complexity and transform security compliance from high drama to teachable moments.

More specifically, we accomplish this by creating a detailed graph database and driving audits, monitoring, and security policies from it in a way that scales like nothing else, and providing detailed data of what changed and what happened, and each piece relates to the other to help determine the root cause of an outage.

We find configurations that are inconsistent with security best practices within a few minutes of them being created. This allows rational, adult discussions to take place while everyone still remembers what was done, and why it was done – promoting learning and dramatically lowering stress compared to the typical way finding these issues by an auditor, or an intruder.

This talk will give a demo, and will cover the usage, architecture, and future of the Assimilation project.

Alan Robertson

September 01, 2015
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Transcript

  1. Security Best Practices As Code
    Security Best Practices As Code
    #AssimProj @OSSAlanR
    http://assimproj.org/
    Alan Robertson
    Assimilation Systems Limited
    http://assimilationsystems.com

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    Biography
    Biography

    35+ years in IT/development – 10 years in
    system management (SysAdmin)

    Founded Linux-HA project - led 1998-2007 –
    aka “Heartbeat” - now called Pacemaker

    Founded Assimilation Project in 2010

    Founded Assimilation Systems Limited in 2013

    Alumnus of Bell Labs, SuSE, IBM

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    Disturbing Trends...
    Disturbing Trends...

    30% of all break-ins come through “lost” systems (Verizon)

    90% have had failures of unmonitored services (Turnbull)

    80% are unable to keep systems in compliance (Verizon)

    30% start monitoring only after a problem (Turnbull)

    30% of all systems are doing nothing useful (Koomey)

    Larger site admins often don’t know dependencies

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    Assimilation Project Evolution
    Assimilation Project Evolution

    Inspired by 2 million core computer
    (cyclops64)

    Concerns for extreme scale

    Topology aware monitoring

    Topology discovery w/out security issues
    =►Discovery of everything!

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    A 7-dimensional overview
    A 7-dimensional overview
    1.System Management Suite Overview
    2.Basic Technology
    3.Discovery and Monitoring Demo
    4.Best Practice Analyses
    5.“Toy” Best Practice Demo
    6.Current Status
    7.What You Need To Do!

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    Why
    Why the Assimilation System
    the Assimilation System
    Management Suite?
    Management Suite?

    Provides insight and details through a graph-model CMDB

    Helps you understand and automate your environment
    – Reduce Errors
    – Speed up problem resolution

    Reduces Manual Documentation

    CMDB-driven configuration => near-zero configuration

    Automates Monitoring

    Enhances Security

    Designed for Extreme Scale

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    What's in the Suite?
    What's in the Suite?

    Graph CMDB

    Exception Monitoring

    Security Discovery

    Network Connections

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  8. Complexity
    Complexity
    “Complexity is the enemy of reliability”

    Complexity likely your single biggest
    problem
    – Near-zero configuration reduces complexity
    – Tight service integration reduces complexity
    – Accurate detailed view improves complexity
    management

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    Highly Scalable Discovery-Driven
    Highly Scalable Discovery-Driven
    Automation
    Automation
    Continuous Discovery drives everything

    Continuous extensible discovery (CMDB)
    – systems, switches, services, dependencies – zero
    network footprint discovery process

    Extensible exception monitoring
    – more than 100K systems

    Discovery Drives Best Practice Analyses
    – Initially concentrating on security

    All data goes into central graph CMDB

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    This all sounds unreasonable...
    This all sounds unreasonable...

    Huge scalability without complexity?

    Discovery without pings or port scans?
    Really?

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    S
    Simple Scalability
    imple Scalability
    I can explain how we scale so your
    grandmother would understand...
    istockphoto
    ©bowdenimages

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    Massive Scalability –
    Massive Scalability – or
    or
    “I see dead servers in
    “I see dead servers in O
    O(1) time”
    (1) time”

    Adding systems does not increase the monitoring work on any system

    Each server monitors 2 (or 4) neighbors

    Each server monitors and discovers its own services

    Ring repair and alerting is O(n) – but a very small amount of work
    Current Implementation

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    Minimizing Network Footprint
    Minimizing Network Footprint
    (in our roadmap)
    (in our roadmap)

    Support diagnosing switch issues

    Minimize network traffic

    Ideal for multi-site arrangements

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    Service Monitoring based on HA
    Service Monitoring based on HA
    Technologies
    Technologies

    Well-proven architecture:
    – reliable “no news is good news”

    Implements Open Cluster Framework
    standard (LSB and others – Nagios coming!)

    Each system monitors own services

    Can also start, stop, migrate services

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    How does discovery work?
    How does discovery work?
    Nanoprobe scripts perform discovery

    Each discovers one kind of information

    Can take arguments from environment

    Output JSON
    CMA stores Discovery Information

    JSON stored in Neo4j database

    CMA discovery plugins => graph nodes and relationships

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    OS discovery JSON Snippet
    OS discovery JSON Snippet
    { "nodename": "alanr-1225B",
    "operating-system": "GNU/Linux",
    "machine": "x86_64",
    "processor": "x86_64",
    "hardware-platform": "x86_64",
    "kernel-name": "Linux",
    "kernel-release": "3.8.0-31-generic",
    "kernel-version": "#46-Ubuntu SMP ...",
    "Distributor ID": "Ubuntu",
    "Description": "Ubuntu 13.04",
    "Release": "13.04",
    "Codename": "raring" }

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    "sshd": {
    "exe": "/usr/sbin/sshd",
    "cmdline": [ "/usr/sbin/sshd", "-D" ],
    "uid": "root",
    "gid": "root",
    "cwd": "/",
    "listenaddrs": {
    "0.0.0.0:22": {
    "proto": "tcp",
    "addr": "0.0.0.0",
    "port": 22 },
    sshd
    sshd Service
    Service JSON Snippet
    JSON Snippet
    (from netstat and /proc)
    (from netstat and /proc)

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    "ssh": {
    "exe": "/usr/sbin/ssh",
    "cmdline": [ "ssh", "servidor" ],
    "uid": "alanr",
    "gid": "alanr",
    "cwd": "/home/alanr/monitor/src",
    "clientaddrs": {
    "10.10.10.5:22": {
    "proto": "tcp",
    "addr": "10.10.10.5",
    "port": 22 },
    ssh
    ssh Client
    Client JSON Snippet
    JSON Snippet
    (from netstat and /proc)
    (from netstat and /proc)

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    Service Dependency Graph
    Service Dependency Graph

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    Switch Discovery Graph
    Switch Discovery Graph
    from LLDP (or CDP)
    from LLDP (or CDP)

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    Why a graph database? (Neo4j)
    Why a graph database? (Neo4j)

    Humans describe systems as graphs

    Dependency & Discovery information: graph

    Speed of graph traversals depends on size of
    subgraph, not total graph size

    Root cause queries  graph traversals –
    notoriously slow in relational databases

    Visualization is Natural

    Schema-less design: good for constantly changing
    heterogeneous environment

    Graph Model === Object Model

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    A Few Canned Queries
    A Few Canned Queries
    allipports get all port/ip/service/hosts
    allswitchports get switch connections
    crashed get crashed servers
    shutdown get gracefully shutdown servers
    downservices get nonworking services
    findip get system owning IP
    findmac get system owning MAC
    unknownips get unknown IP addresses
    unmonitored get unmonitored services

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    B
    Best Practice Analyses
    est Practice Analyses
    This is next major capability

    Triggered by Discovery Updates
    – Analysis occurs within seconds of change
    – No change => No analysis

    We can analyze anything discovered

    Expect to create alerts and reports

    SIEM integration

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    Sample Security Best Practices
    Sample Security Best Practices

    Inappropriate services (telnet, etc)

    Settings in /proc/sys/

    Security Patch Coverage
    – OS vendor (RedHat, SuSE, Canonical, etc)
    – Application (Oracle, IBM, WordPress, etc)

    Other OS settings

    Common Application Settings

    Looking at best practices
    FYI: Sharing information (collaborating?) with Lynis project

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    Other Sample Security Features
    Other Sample Security Features

    Discovery of “forgotten” IP addresses

    Monitoring of Open Ports and Services

    Collection of network-facing app checksums

    Nmon profiling of new MAC addresses

    Checksum outliers analysis

    Security Best Practice Analyses

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    IT Best Practices Project
    IT Best Practices Project
    ITBestPractices.info

    IT-Bestpractices GitHub project

    Working on Linux Foundation Sponsorship

    Apache 2 License (or similar)

    Initial Sources
    – DISA STIGs
    – Lynis project
    – Individual contributions

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    IT Best Practices Goals
    IT Best Practices Goals

    Make Best Practice rules available in JSON
    – Curate mechanically-verifiable practices
    – Human-readable descriptions of issues and
    remedies
    – Multiple language support
    – Not limited to security best practices
    – Eventually available through a web server

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    Sample short description
    Sample short description
    The system must limit the ability of processes to
    have simultaneous write and execute access to
    memory.

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    Sample long description
    Sample long description
    ExecShield uses the segmentation feature on all
    x86 systems to prevent execution in memory
    higher than a certain address. It writes an address
    as a limit in the code segment descriptor, to control
    where code can be executed, on a per-process
    basis. When the kernel places a process's memory
    regions such as the stack and heap higher than
    this address, the hardware prevents execution in
    that address range.

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    Sample Security Rule check
    Sample Security Rule check
    The status of the "kernel.exec-shield" kernel parameter can
    be queried by running the following command:
    $ sysctl kernel.exec-shield
    $ grep kernel.exec-shield /etc/sysctl.conf
    The output of the command should indicate a value of "1". If
    this value is not the default value, investigate how it could
    have been adjusted at runtime, and verify it is not set
    improperly in "/etc/sysctl.conf".
    If the correct value is not returned, this is a finding.

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    Assimilation /proc/sys Rule
    Assimilation /proc/sys Rule
    Disallow executing code on writable pages
    “nist_V-38597”:
    {“rule”: “EQ($kernel.exec-shield, 1)”,
    “category”: “security”
    }

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    Assimilation Networking Rule
    Assimilation Networking Rule
    Buffer bloat prevention
    “itbp-0001”:
    {“rule”: “IN($kernel.core.default_qdisc,
    fq_codel, codel)”,
    “category”: “networking”
    }

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    D
    Discovery / Monitoring / Best
    iscovery / Monitoring / Best
    Practices Demo
    Practices Demo

    Demonstrate basic capabilities
    – Discovery-driven monitoring configuration
    – Discovery-driven 'tripwire-like' checksums
    – Monitoring – failures / successes
    – Host down notification
    – Best Practices

    No configuration was supplied
    – everything comes from discovery
    http://assimilationsystems.com/90_second_demo/

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    Best Practices Demo
    Best Practices Demo

    Demo is of code in our source tree

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    Current Status
    Current Status

    1.0 (Independence Day) release out 4 July 2015

    Security is our next major emphasis

    Great unit and system tests

    Strongly encrypted communication

    Quite a few discovery methods written

    Extensible Automated Discovery Triggers

    Discovery => Automatic Monitoring + Network-Facing Checksums

    Compatible with Nagios remote monitoring agent API

    REST + Command Line Queries

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    Get Involved!
    Get Involved!

    Trials! Early Adopters!

    Contributors
    – Testers, Continuous Integration
    – Best practice experts
    – Designers
    – Developers (C, Python, Shell, PowerShell, JavaScript)
    – Porters (esp Windows)
    – Promoters, Publicists, Packagers, etc.

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    Resistance Is Futile!
    Resistance Is Futile!
    These slides: bit.ly/DOSUG0915
    Mailing List: bit.ly/AssimML
    @OSSAlanR
    #assimilation on irc.freenode.net
    Project Web Site: assimproj.org
    Company Web Site: assimilationsystems.com
    Download: assimilationsystems.com/download

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    Risk Management/Mitigation
    Risk Management/Mitigation

    Intrusions

    Vulnerable Software

    Licensed Software

    Audit Risk

    Outages

    System management

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    Monitoring Pros and Cons
    Monitoring Pros and Cons
    Pros
    Simple & Scalable
    Uniform work distribution
    No single point of failure
    Distinguishes switch vs
    host failure
    Easy on LAN, WAN
    Multi-tenant approach
    Cons
    Active agents
    Potential slowness
    at power-on

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    Sixth Dimension:
    Sixth Dimension:
    Graph Schema
    Graph Schema
    Two Schema subgraphs

    Client / server
    dependency

    Switch interconnect

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  41. First Dimension
    First Dimension:
    :
    Problems Addressed
    Problems Addressed

    Discovering and maintaining documentation
    (CMDB) using continuous discovery
    – Services, Systems, Dependencies, Switches, Interconnects,
    Configuration

    Monitoring and alerting: services, systems and
    compliance

    Managing compliance

    Mitigating risk

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    Why Discovery? (DevOps)
    Why Discovery? (DevOps)

    Documentation: incomplete, incorrect

    Dependencies: unknown

    Planning: Needs accurate data

    Best Practices: Verification needs data

    ITIL CMDB (Configuration Management
    Data Base)
    Our Discovery: continuous, low-profile

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    Second Dimension:
    Second Dimension:
    Unique Powerful Features
    Unique Powerful Features
    1. Continuous Discovery
    2. Discovery: Zero network footprint
    3. Centralized graph database
    4. We know everything that changes
    5. Discover and update dependency information
    6. Discovery and monitoring tightly integrated –
    discovery drives automation

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    (even more) Features...
    (even more) Features...
    7. Discovery and monitoring easily extensible
    8. Naturally scalable to > 100K systems
    9. Minimal network load
    10.Server failures distinguishable from switch failures
    11.Best practice and vulnerability alerts
    12.Multi-tenant support

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    Third Dimension:
    Third Dimension:
    Fully distributed work
    Fully distributed work
    Two philosophical underpinnings
    1. Monitoring and Discovery are fully distributed
    2. Reliable “no news is good news”
    Only responses to changes are centralized

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    Sample /proc/sys Rules
    Sample /proc/sys Rules
    “BPC-00002-1”:
    {“rule”: “OR(EQ($kernel.core_uses_pid, 1),
    NE($kernel.core_pattern, ""))”
    “url”: “https://trello.com/c/6LOXeyDD” },
    “BPC-00003-1”: {“rule”: “EQ($kernel.ctrl-alt-del, 0)”,
    “url”: “https://trello.com/c/aUmn4WFg”},
    “BPC-00006-1”: {“rule”: “EQ($kernel.sysrq, 0)”,
    “url”: “https://trello.com/c/QSovxhup” },

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