Transcript Remote Virtual Machine Monitor Detection Jason Franklin, Mark Luk, Jonathan McCune, Arvind Seshadri, Adrian Perrig, Leendert van Doorn.

Remote Virtual Machine Monitor
Detection
Jason Franklin, Mark Luk, Jonathan
McCune, Arvind Seshadri, Adrian Perrig,
Leendert van Doorn
Remote Virtual Machine Monitor Detection
Are you virtual?
`
External
Verifier
Remote
Machine
 Problem Statement
• Determine if a remote machine is virtual or real
 Challenges
• VMM provides an accurate abstraction of the underlying hardware
• VMM controls execution of code and may return arbitrary values
VMM Detection and Botnets (1/2)
 Scenario 1
• Bots may install a stealthy virtual machine based
rootkit (VMBR) to avoid detection by traditional
malware scanners
• Stealthy rootkits prevent administered machines
from removing bots
• You run an AV, update, patch, yet never locate/remove
the bot
• Detecting VMMs allows us to detect bots
VMM Detection and Botnets (2/2)
 Scenario 2
• Bots may check for the existence of a VMM in
order to prevent dynamic analysis
• “Detecting the sandbox”
• Real threat & mentioned several times yesterday
• Agobot uses a heuristic to check for VMWare
• Studying VMM detection helps us understand
how to enable VMM-based dynamic analysis
State of the Art in VMM Detection
 Check for software-implementation artifacts
• Redpill checks the location of the IDT (different
location under VMWare)
• VMWare’s Back checks for VMWare I/O port
 Other approaches
• Make restrictive assumptions
• Easy to thwart
• Require benchmarking
Our Goals
 Develop a VMM detection algorithm:
• VMM implementation independent
• Accurate
• Practical/relies on few assumptions
 Leverage fundamental differences between
virtual and real machines
VMM Model
 Popek and Goldberg ’74 formally defined the
properties a control program must satisfy to
be deemed a VMM
• Efficiency Property
• Resource Control Property
• Equivalence Property
• Program execution in a virtual environment must be
indistinguishable from execution in a real environment
Indistinguishable? Oh no!
 If a program executes indistinguishably,
we can’t detect a virtual execution
environment
 Don’t worry! There are exceptions to the
equivalence property
• Timing dependency exception
• Certain sequences of instructions may take longer
to execute
• Resource availability exception
Does the timing dependency
exception necessarily exist?
 Empirically, yes.
• Programs executing in a VMM experience VMM
overhead
 In theory, yes.
• Intuition is that VMM must maintain control of
executing code by interposing on the operations
or rewrite the binary
Exploiting the timing dependency
exception to detect a VMM
 Algorithm:
Given:
• Real machine R with configuration C e.g., C={Pentium IV,
2.0GHz}
• Remote machine M with configuration C
• Program P with control-modifying instructions
1: Time the execution of P on R and store the value in r
2: Time the execution of P on M and store the value in m
3: IF m > r + k THEN M is virtual [note: k is the detection constant]
4: ELSE M is real
Tasks Remaining
 Achieve accurate high-integrity execution
timing
 Construct program P with externally
noticeable VMM overhead
 Determine configuration of remote machine
 Determine detection constant k
Accurate High-Integrity Execution Timing
 Can’t trust the integrity of the timing measurements
returned by the VMM
 Use an external source of time (e.g., remote machine,
watch, etc…)
Constructing P with VMM Overhead
 P is a sequence of sensitive (potentially
control modifying) instructions that requires
VMM interposition
 P is designed to invoke VMM overhead
 Design decisions in developing P include:
• Sensitive instruction selection
• Number of instructions
Selecting Sensitive Instructions
R/W cr3
R/W cr2
R/W cr0
cli
Number of Instructions in P
 Assume we have complete configuration
information for remote machine M
 Easy to determine the number of instructions
required to overcome experimental noise
• Variance in execution time
• Variance in network latency
Complete Configuration Information
Fastest VMM = FV(x)
Real Machine = RM(x)
 Given an estimate of the noise N in the environment
(i.e., 10 ms variation in network latency)
 Select x s.t. FV(x) – RM(x) >> N
Incomplete Configuration Information
 Unreasonable to assume complete
configuration information is available for a
remote machine
 Use “hardware discovery” heuristic
• Intuition: certain properties of the underlying
hardware are difficult to mask through the VMM
and are unique to a particular architecture
• Discovering these hardware artifacts gives us
partial configuration information about a remote
machine
Incomplete Configuration Information
 Given a subset C’ of the complete configuration information C
• C = {Pentium IV, 2.0 GHz} and C’ = {Pentium IV}
 Bound the execution time of P on the fastest and slowest
machines that satisfy C’
• Works because P is CPU bound
• We can time the execution of P on a x GHz machine and then
use the ratio of the fastest and slowest machines to bound the
execution times
Hardware Discovery on the Pentium IV
 P4 has a unique trace cache which “shines” through the VMM
 With sequences of register-to-register arithmetic instructions
without data hazards populate the trace cache of the Intel
Pentium IV, a CPI of 1/3 is attainable
 Once an instruction sequence exceeds the trace cache’s size
of 12KB, the CPI becomes 1
Remote Trace Cache Discovery
 11264 instructions fit in the trace cache
 11328 instructions exceeds the size of the trace cache
 A considerable jump in overhead occurs when the trace
cache overflows
Putting it All Together
 Remotely timed overhead from reading and writing x86 Control
Register 3 multiple times consecutively
 Despite not being included in our analysis, remote detection works
against a machine running Xen with hardware virtualization support
(HVM Xen)
• We conclude that hardware virtualization support is not sufficient
to prevent VMM detection
Detection Algorithm Limitations
 VMM could tamper with execution of detection code
• Countermeasure: Leverage software-based attestation
(Pioneer)
 VMM could prevent communication to external timer
• Countermeasure: Containment policy-based detection
 Receive incorrect response from hardware
discovery heuristic
 VMM may be incorporated with OS
• Malware can still own the lowest layer
• Virtual-machine-based rootkits are a threat today
Conclusion
 Developed a remote VMM detection algorithm
• Attempts to be independent of VMM software
implementation details
• Practical/relies on fewer assumptions than previous
schemes
• Accurate, configurable, and effective over the
Internet
 Hardware virtualization support is not sufficient
to mask differences between real and virtual
environments