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Click to edit Master text styles
Second level
Third level
Fourth level
Fifth level
root
East
West
North
1st Qtr
20.4
30.6
45.9
2nd Qtr
27.4
38.6
46.9
3rd Qtr
90.0
34.6
45.0
4th Qtr
20.4
31.6
43.9
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How to make the pain go away
Adam Shostack
adam@InformedSecurity.com
Overview
Why patch?
Why is patching so painful?
What can make it easier?
Thinking about risk management
How can we get out of the rat race?
Why Patch?
Vendors issue patches to correct bugs
Performance/Reliability
Security is a subset of reliability
End users apply patches to fix problems
Preventative/Reaction models
Security Patches
Vendors release code
All code has bugs
People find bugs
Sometimes they tell the vendor
Vendor triages, and may release a fix
Some want to install it to forestall problems
Where we are
Why patch?
Why is patching so painful?
What makes it easier?
Thinking about risk management
How can we get out of the rat race?
Why is patching painful?
Patch notification
Inventory & Roll-out
Mobile
Low bandwidth
Lies and Excuses!
Inventory
Deploy
Analyze
Maturity
Deployment
Unicenter
Tivoli
ZenWorks (etc)
State of Software Tools
The Real Problems
Patches are beta software
Intense pressure to roll out beta software
Poor data about patches
Conflict between IT & IT Security
Patches which can’t roll back
Uptime vs. Security
IT is rated on measured uptime
Every admin knows patching can break things, require reboots
Security is rated on break-ins
Need to deploy patches to prevent
Huge fights come from different priorities.
Where We Are
Why patch?
Why is patching so painful?
What makes it easier?
Thinking about risk management
How can we get out of the rat race?
Reconciling The Views
Patch risk falls with time
Exploit risk grows with time
Can we put numbers on them?
Can we engage in a risk trade-off?
Timing the Application of Security Patches for Optimal Uptime
Timing the Application...
Presented at the USENIX 16th Systems Administration Conference (LISA 2002)
http://www.homeport.org/~adam/time-to-patch-usenix-lisa02.pdf
(Don’t copy down the URL: Google finds my homepage, that’s bullet #7)
Where We Are
Why patch?
Why is patching so painful?
What makes it easier?
Thinking about risk management
How can we get out of the rat race?
Risk Management
You can do this at home!
Easy math leads to useful results
Cost to deploy, cost to fix problems (security or broken patch)
Goal is to move away from argument and worry
Consider Security Risk, Patch Risk, Business Impact
Security Issues
Patch criticality
Software Vendor
CERT metrics (ADDED: CVSS)
CNN
Mitigating controls
Firewalls
Configurations
Patch Issues
How big is the patch?
How many issues does it fix?
Can it be backed out?
Does it require a reboot?
Testing (internal, external, web & lists)
Business Issues
What’s the business function of the system?
Is there an impending deadline?
What’s your MTTR?
(Mean Time To Repair)
Making it concrete
Know your cost to deploy a patch
Know your cost of downtime
Estimate the risk of attack
Some sample numbers
1,000 node network with manual patching by $100 techies, at 1 hour/node:
$100,000 to deploy a patch
So what do you do if:
Attack that would cost you $1,000,000
Attack that would cost you $105,000
Attack that would cost you $25,000
The $105,000 question
Expected 5% ROI on cash
Didn’t specify time
Alternate activities?
Cost of capital/ROI?
Why patch?
Why is patching so painful?
What makes it easier?
Thinking about risk management
How can we get out of the rat race?
Better Patch Mgmt SW
Research and risk data
Workflow
Testing support
Risk Management support
More Managable Deployments
Use security software (Okena, Immunix, Sana, etc) to stop classes of attack
Use software to deploy and manage systems
Work to increase MTBF, decrease MTTR
More Secure Software
The core problem is that security is not a buying criteria
Make it one
Bug (and software) Development
How To Move?
It’s actually worse than that
That’s a graph for a single program
You deploy lots of programs
How To Get There
Better software tools
Internal, external
Better Deployment tools
Security
Operations
Where The Tools Fit
Static Checkers
Work with source code
Lots of different languages
Results generally easier to fix
They’re associated with lines of code
High false positive rates
Find “sins of commission” like strcat()
Fast
Free Static checkers
RATS
ITS4
Flawfinder
Static Checkers: Slicers
Compiler-like technology to see what variable could be touched where
Perl’s taint mode
Clever techniques to deal with pointers
Can be perfect on small code (20kloc)
Much research
Static Checkers: Parsers
Analyze variables and typing because C doesn’t
Can deal with integer issues well
Slower
SPLINT is a free example
Static Checkers: Compilers
Compile code, and analyze on the way
Code is not always compiled to your processor
Target a VM that has security features
MOPS
Dawson Engler’s group @ Stanford
GCC -Wall is not complete
Dynamic Checkers
Work on binary code
Never wonder if the optimizer was too clever
Find “Sins of Omission” like SQL injection
Slow! (Can be hours or days)
Dynamic Tools: Fuzzers
Fuzz, Spike, libwhisker
Mangleme http fuzzer
http://lcamtuf.coredump.cx/soft/mangleme.tgz
Feed noise to the target see if it breaks
And you’re surprised this is slow?
Dynamic: Attack Simulation
“Second Gen fuzzers”
Attack tool libraries
CORE Impact, Metasploit
Require skilled driver
Nikto
Less powerful, easy to use
Dynamic Tools: Decompilers
Turn byte code/machine code into something resembling C
Useful for closed source apps you need
Need to analyze the decompiled source
Dynamic: Binary Differs
Not a dynamic tool as much as a static tool for machine code
Best for finding why a patch happened
Attack/exploit creation
Vendor verification:
Is this patch effective?
Are they being upfront about what’s in it?
Language Selection
Some languages seem to be more prone to security flaws
C, PHP
We may not have found the classes of flaws in Java, C#
New classes keep showing up (integer underflows, etc)
Things Hard to Measure
Security design goodness
Attack surface
nmap not enough
port 25 seems to have a large surface
port 137 does too.
Adding Resilience to Code
How to
deploy
operate
Buggy code more securely
Free UNIX techniques
chroot/jail
Unprivileged daemon accounts
Painful if you need fast code on port 80
Free security enhanced OSes:
OpenBSD, SELinux
Techniques
Harden the system:
Control Attack surface
Limit effect of an attack
Can entail high operational cost for questionable benefit
Need to evaluate what happens
More advanced tools
OS hardening tools
Immunix subdomain
Sana kernel enhancements
Application hardening
Stackguard & company
(Recompile vs kernel modules)
Issues with Hardening Tools
How to measure their effectiveness
Configuration effort
Costs (percieved and real)
Cash up front
Speed
Supportability + Vendor finger pointing
Network Intrusion Prevention
Throwing Ducks at Baloons
Paper by Ptacek and Newsham, 1998
Showed how to evade IDSs, IPSs
The Covert Channel problem
Firewalls Move (back) Up
Application Firewalls vs packet filters
Inspection
Snort Inline
Process Resilience Tools
How to fail gracefully
detect, respond, improve
Measuring your process
Architecture and Forensics
An ounce of prevention
Selling Your Boss
Or, Security folks are from Mars, businesspeople are from Wheaton
How You Buy Software
Functionality, supportability, price
Can you get security in there?
The above can be used for that
Sample Scoring
0-1 point for a good language
0-1 point for documented use of tools to check code
0-1 point for unprivileged, chroot install
0-1 point for logging
0-1 point for local analysis
Deployment Budgets
Cash for wires, hubs, power, air
Where does security fit?
What’s the real cost of a failure?
(Hint, its not $1m, unless you’re a large bank)
Deployment Business Cases
Cost of operations with and without tool X
Cost of special events:
Patching
Breakins
Worms
Frequency of special events
Summary
We’ll always have patches to deploy
We can build rational decision processes
We can use better tools
We can push vendors to sell better SW
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