2016 BSidesLV OWASP Assimilation talk

IT shops have trouble reliably doing the basics well:
- 30% of all break-ins come through systems not in inventory
- 30% of servers are doing nothing useful
- getting systems hardened is difficult
- 70% of people who get into compliance with PCI-DSS aren’t in compliance a year later
- remediation of known serious patches happens slowly if at all
- 90% of all sites have suffered from outages of services which aren’t monitored
- keeping a suite of helpful tools correctly configured over time is time-consuming and expensive

Then of course, there’s the problem of demonstrating to upper management that you’re actually making progress against a formidable task. These are the problems the OWASP Assimilation project addresses.

It compares security configuration against best practices, keeps network-facing checksums up to date, provides attack surface visualization, alerts on many kinds of events, and also improves availability through monitoring systems and services.

This talk gave an overview of the project and a live demo.
Video from this talk can be found here: http://assimilationsystems.com/videos/2016-bsides-las-vegas-automating-security-owasp-assimilation-project/

Transcript

1. Automating Security with the OWASP
   Automating Security with the OWASP
   Assimilation Project
   Assimilation Project
   #AssimProj @OSSAlanR
   Alan Robertson
   Assimilation Systems Limited
   owasp.org/index.php/OWASP_Assimilation_Project
   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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   Security questions
   Security questions
   ●
   Do you think good security staff is easily available?
   ●
   Do you think security is going to get better soon?
   ●
   Do you think you have enough staff for security to keep up
   with changes at DevOps / Agile rates?
   

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   Disturbing Trends...
   Disturbing Trends...
   30% of break-ins come through “lost” systems (Verizon)
   90% have had failures of unmonitored services (Turnbull)
   71% are unable to stay in compliance (Verizon)
   30% only start monitoring only after a problem (Turnbull)
   30% of systems doing nothing useful (Koomey)
   

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   OWASP Assimilation Use Cases
   OWASP Assimilation Use Cases
   ●
   Tracking IP and MAC addresses
   ●
   Continuous validation of configuration against compliance rules
   ●
   Tracking software versions
   – (OS packages, GEMs, pip packages, etc)
   ●
   Tracking checksums of network-facing files
   ●
   Tracking services offered - ports, binaries, arguments, etc
   ●
   Tracking security configuration, permissions
   ●
   Monitoring status of servers and services (working correctly?)
   ●
   Scoring of security issues with triage tools
   ●
   Includes Docker containers
   ●
   Alerting on changes in configuration or status (any of the above)
   ●
   Near-zero configuration
   ●
   No pings or port scans
   

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6. Highly S
   Highly Scalable Discovery-Driven
   calable Discovery-Driven
   Automation
   Automation
   Continuous Discovery drives everything
   ●
   Continuous extensible discovery (CMDB)
   – systems, switches, services, dependencies, system settings
   ●
   zero network footprint discovery process (using agents)
   ●
   Discovery eliminates most configuration
   ●
   Discovery Drives Best Practice Security Analyses
   ●
   All data goes into central graph CMDB (Config Mgmt Data Base)
   ●
   System naturally scales to ≈ 100K servers
   

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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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   Simple Scalability
   Simple Scalability
   I can explain how we scale so your
   grandmother would understand...
   

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   Assimilation Architecture
   Assimilation Architecture
   ●
   Central Collective Management Authority (CMA)
   – written in Python
   – directs and delegates most work to nanoprobes – does nothing as much as possible
   – Doing nothing scales really well – should scale into the 100K system range
   – Near-zero configuration – discovery drives everything
   ●
   Fully distributed “nanoprobe” agents
   – Simple, lightweight, policy-free – directions come from CMA
   – Written in 'C'
   – Run scripts for monitoring or discovery
   – Send/receive heartbeats
   – Listen for ARP, LLDP, CDP packets
   ●
   Neo4j graph database
   

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    Assimilation Analysis / Reports
    Assimilation Analysis / Reports
    ●
    Comparison (“auditing”) against best practice hardening
    rules – default rules from IT Best Practices Project
    ●
    Risk scoring – for triage and mitigation management
    ●
    Unknown IP Addresses
    ●
    Automatic service monitoring
    ●
    Unmonitored services
    ●
    Triage related risk scores
    

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    B
    Best Practice (hardening) Analyses
    est Practice (hardening) Analyses
    ●
    Triggered by Discovery Updates
    – Analysis occurs within seconds of change
    – No change => No analysis
    ●
    We can analyze anything discovered
    ●
    You can easily discover anything you want
    ●
    Alerts and Reports available
    

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    Future Security Work
    Future Security Work
    ●
    Coordinate with vendor security updates
    – “Listen” to vendor security update announcements
    – Update scores when vulnerable packages found, fixed
    ●
    Do interesting things with checksums
    – Whitelists
    – Blacklists
    – “Minority Report” – 99 copies the same, one different...
    ●
    More discovery (firewall rules, etc)
    ●
    Integrate with SIEMs
    ●
    Add RBAC filtering
    ●
    What else should we be doing?
    

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    Demo
    Demo
    Everything is discovered – nothing is configured manually
    ●
    What needs hardening
    ●
    How to Triage your hardening issues
    ●
    How to Demonstrate and Track Progress
    ●
    How to keep them in compliance (hardened)
    ●
    Visualizing Your Attack Surface
    ●
    Who has what package+version
    – Docker package discovery too!
    

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    Summary of what’s cool...
    Summary of what’s cool...
    ●
    System knows more about your environment than you do
    ●
    Can discover anything you’d like to know
    ●
    Discovery keeps everything up to date (quasi-real-time)
    ●
    Best practice auditing/hardening check is continuous
    ●
    Scoring system helps manage mitigation process
    ●
    System has near-zero configuration
    ●
    Discovery includes Docker containers
    ●
    System also monitors servers, services
    ●
    Event API supports immediate notification of changes
    ●
    System scales unusually well
    

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    Where to find this Information online?
    Where to find this Information online?
    http://assimilationsystems.com/category/getting-started/
    1. 15 Minutes To Better Security
    2. An Hour To Better Security
    3. A Half-Day To Better Security
    Where to See Similar Demos
    ●
    http://assimilationsystems.com/category/videos/
    ●
    http://assimilationsystems.com/sample-demo-output/
    

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    Get Involved!
    Get Involved!
    ●
    Get Assimilated!
    ●
    Contribute!
    – Users – give it a try
    – Security best practice experts
    – Testers, System Management, Continuous Integration
    – 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/BsidesLV16
    Mailing List: bit.ly/AssimML
    @OSSAlanR
    #assimilation on irc.freenode.net
    Project Web Site: assimproj.org
    https://www.owasp.org/index.php/OWASP_Assimilation_Project
    Company Web Site: assimilationsystems.com
    Download: assimilationsystems.com/download
    

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    Current discovery scripts
    Current discovery scripts
    ●
    auditd_conf - discovers settings in /etc/auditd.conf
    ●
    checksums - discovers checksums of network-facing binaries, libraries and JARs
    ●
    commands - discovers what commands are installed in standard directories
    ●
    cpu - discovers CPU information
    ●
    docker - discovers Docker instances and attributes
    ●
    fileattrs - discovers file attributes (permissions) of whatever files its asked to check out
    ●
    findmnt - mount table related discovery
    ●
    login_defs - /etc/login.defs discovery
    ●
    mdadm - Linux RAID configuration
    ●
    monitoringagents - discovery of installed monitoring agents
    ●
    netconfig - network configuration - similar to ifconfig
    ●
    nsswitch - discovery of /etc/nsswitch
    ●
    os – discovery information - basically uname -a
    ●
    packages - discovery of all installed RPM, DEB, pip (python), Ruby GEMs and node.js NPM packages
    ●
    pam - discovery of PAM configuration
    ●
    partitions - Discovery of partition information
    ●
    proc_sys - Discovery of Linux /proc/sys settings - basically everything
    ●
    sshd - Discovery of sshd settings
    ●
    sudoers - Discovery of /etc/sudoers settings
    ●
    tcpdiscovery - Discovery of services used and services provided (there were two slides on this subject)
    ●
    ulimit - root's default ulimit settings
    ●
    vagrant - Discovery of vagrant VMs and settings
    

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19. Switch Discovery Graph from
    Switch Discovery Graph from
    LLDP / CDP
    LLDP / 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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    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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22. "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 Service JSON Snippet
    sshd Service JSON Snippet
    (from netstat and /proc)
    (from netstat and /proc)
    

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23. "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 Client JSON Snippet
    ssh Client JSON Snippet
    (from netstat and /proc)
    (from netstat and /proc)
    

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    Service Monitoring based on HA Technologies
    Service Monitoring based on HA 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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    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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    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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28. 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 roadmap)
    (in roadmap)
    ●
    Support diagnosing switch issues
    ●
    Minimize network traffic
    ●
    Ideal for multi-site arrangements
    

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