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Analyzing Kernel Security
and
Approaches for Improving It
Milan Rajpara
IT Systems and Network Security

Gujarat Technological University

C DAC

Ahmedabad

Pune
Agenda
• Kernel Introduction
• Necessity for Kernel Security

• Kernel breach
• Analyzing Kernel Security
• Improving Approaches

• Future Work

Milan Rajpara

October 8, 2013

2
What is Kernel ?
• A computer program that manages
input/output requests from software
and translates them into data
processing instructions for the
central processing unit and other
electronic components of a
computer. [Wikipedia]
• The kernel is a fundamental part of a
modern computer's operating
system.
• OS rests on a outer ring, and
application above that.
Fig: Privilege rings for the x86 available in protected mode
[Source: Wikipedia]

Milan Rajpara

October 8, 2013

3
Necessity for Kernel Security
• Kernel, a vary basic (core) part of the Operating Systems
• Single vulnerability will be exposes large number of systems

• Increasing of Cloud Usage with Virtual Systems
• Smartphones now is in every hand

Milan Rajpara

October 8, 2013

4
We talk on ..
• Kernels for General Purpose Operating System
• Some Linux flavor gives Server Optimized Kernel
• Ex. Ubuntu older then 12.04, were gave this option. Since 12.04, linux-image-server is merged into linuximage-generic, there is no difference between Generic and Server kernel. [4]

• Windows do not disclose.

• Kernels which Constructed in C language
• Almost kernels are in C

• Improvement for Monolithic kernels
• All work performed in Virtual environment
• The Xen, and VMware used

Milan Rajpara

October 8, 2013

5
How Kernel Affected ?
• By Kernel level rootkits
• Manipulating pointers
• Manipulating data

• Direct Kernel Object Manipulation (DKOM)

• By Boot-kits
• Via hooking techniques
• Direct Hardware or Firmware injection

Milan Rajpara

October 8, 2013

6
Effect of this Attacks
• Escalate a process’ privileges by overwriting the process’ credentials
• Hide itself by illicitly removing data structures identifying their presence from
loaded drivers
• Eliding task structures for the processes from the kernel’s process accounting list
• Alter the overall behavior of OS without injecting any malicious code into the
kernel address space, by just pointer manipulating.

Milan Rajpara

October 8, 2013

7
How to analyze the Kernel Security
• Find the most critical objects of the kernel, without prior knowledge of the OS
kernel data layout in memory
• Identifying OS Kernel Objects for Run-time Security Analysis
• Sort-out objects which are vulnerable to hijack
• Do Kernel Data Disambiguation
• This will make the system easy to analyze

Milan Rajpara

October 8, 2013

8
Most critical objects in Kernel
• Windows and Linux, the core kernel part are mostly written in C
• 40% inter-data structure relations are Pointer based

• 35% of these are Generic Pointers
• Pointers which defines at run time, no initial value or data type is associated

• 28% kernel data structure are well known objects

Milan Rajpara

October 8, 2013

9
Generic Pointer Problem
• It is the weak link in kernel security
• Use of void pointers *, assists hackers to point somewhere else

• Use of NULL pointers (to implements linklist), helps hackers to hide / change
runtime objects.
• Use of Casting in C
• Enables the hackers to exploit data structure layout in physical memory

Milan Rajpara

October 8, 2013

10
To Find Critical Objects
1. Memory Mapping techniques
• Travers address space from global variables via pointer dereferencing until reaching
running object.
• according to a predefined kernel data definition for each kernel version.

2. Value Invariant Approaches
• Use the value invariants of certain fields or of a whole data structure as a signature to
scan the memory for matching running instances. Ex. DeepScanner, DIMSIM

• Drawbacks of this approaches
- Not very accurate
- Require a predefined definition of the kernel data layout
- Not effective when memory mapping and object reachability information is not available.
- High performance overhead
Milan Rajpara

October 8, 2013

11
To Find Critical Objects
3. DIGGER

[1]

• Uncover all system runtime objects without any prior knowledge of the OS kernel
data layout in memory.

• First it performs offline and constructs type-graph (which is used to enable
systematic memory traversal of the object details).
• Then it uses the 4-byte pool memory tagging schema (to uncover kernel runtime
objects from the kernel address space.)
• (+)
• Accurate result
• Low performance overhead

• Fast and nearly complete coverage

Milan Rajpara

October 8, 2013

12
DIGGER & KDD
• DIGGER uses the KDD (Kernel Data Disambiguator) to precisely models the
direct and indirect relations between data structures.
• KDD is a static analysis tool that operates offline on an OS kernel’s source code
• Generates a type-graph for the kernel data with direct and indirect relations
between structures, models data structures [2]
• KDD disambiguates pointer-based relations (including generic pointers)
• by performing static points-to analysis on the kernel’s source code.

• Points-to analysis is the problem of determining statically a set of locations to
which a given variable may point to at runtime.

Milan Rajpara

October 8, 2013

13
KDD Operation

Source: Ref [2]
AST: Abstract Syntax Tree (high-level intermediate representation for the source code )
Milan Rajpara

October 8, 2013

14
KDD Operation
• Interprocedural Analysis 1: Takes AST and differentiate it
• Gets: Variables, Procedure definition, Procedure call, etc.. .

• Interprocedural Analysis 2: Do points-to analysis across different files to perform
whole-program analysis.

• Context Sensitive Analysis:
• It uses Procedure Dependency Graph (PDG) consists of nodes representing the statements of the
data dependency in the program.
• context-sensitive analysis solves two problems: the calling context and the indirect (implicit)
relations between nodes.

Milan Rajpara

October 8, 2013

15
Soundness and Precision of KDD
• The points-to analysis algorithm is sound if the points-to set for each variable
contains all its actual runtime targets, and is imprecise if the inferred set is larger
than necessary.

• Check on C programs from the SPEC2000 and SPEC2006 benchmark suites.
• Achieved a high level of precision and 100% of soundness.

• And 96% precision on Windows (WRK*, Vista) and Linux kernel (v3.0.22). [2]
*WRK – Windows Research Kernel, the only available code from windows [6]

Milan Rajpara

October 8, 2013

16
DIGGER Approach

Source: Ref [1]

Milan Rajpara

October 8, 2013

17
DIGGER Approach
• Static Analysis Component: from KDD
• Signature Extraction Component:
• When the object manager allocates a memory pool block, it associates with a pool tag
(pool tag is a unique four-byte tag for each object type.) Uses this tag to uncover the
kernel objects running instances, and they are static and cannot be changed during
object runtime.

• Dynamic Memory Analysis Component: Extract the object details,
• From Pool Tag, it gets the pool block start memory address and the object’s start
address.

Milan Rajpara

October 8, 2013

18
Analyzing Kernel through DIGGER Gives …
• Disambiguate the points-to relations between data structures, all without any
prior knowledge of the OS kernel data layout.
• Robust and quite small signature size to uncover runtime objects, enhancing
performance
• Able to keep track of all critical objects of kernel

Milan Rajpara

October 8, 2013

19
Protection of Kernel
• Protect the generic pointers.
• Microsoft added a feature PatchGuard, which blocks kernel mode drivers from
altering sensitive parts of the Windows kernel.
• But TDL (rootkit) manages to circumvent this protection as well, by altering a machine's MBR so
that it can intercept Windows startup routines. [7]

• One approach is use of “Object Partitioning” to protect kernel data structure. [3]
• Uses Sentry, that creates access control protections for security-critical kernel data.

Milan Rajpara

October 8, 2013

20
Sentry Architecture
• Sentry protects critical data and
enforces data access restrictions
based upon the origin of the access
within the code of the kernel and its
modules or drivers. [3]
• The data integrity model is
straightforward and matches that of
the Biba ring policy [9]

• The malicious code that modifies
privileges by directly writing to
memory is in a loaded module and
not in the core kernel code, so Sentry
will prevent the write

Milan Rajpara

October 8, 2013

21
Kernel Memory Access Control
• Protect data structure from DCOM
• Sentry’s design uses a hypervisor to remain isolated from an untrusted kernel

• To keep the overhead low, Sentry uses memory partitioning to lay out sensitive
data on separate memory pages and protects those pages using the hypervisor
• The policy enforcer mediates attempted writes to protected data and uses the
policy to determine when writes should be permitted.

Milan Rajpara

October 8, 2013

22
Working of Sentry
• Identifying Security-Critical Members
• Activation of mediated access

• Instruction emulation
• Secure execution history extraction

Milan Rajpara

October 8, 2013

23
Evaluation of Sentry
• Performance
• Low performance overhead
• more performance van be achieved by memory layout optimization

• False Positive Analysis
• There were no instances when security-critical kernel data protected by Sentry was
directly modified by a benign driver.

• Sentry provided a 100% detection rate for DKOM rootkits

Milan Rajpara

October 8, 2013

24
Future Work
• Detect all kernel data structures automatically, beyond the kernel version
• The DIGGER can only be used to analyze Windows Kernels.

• The current prototype of Sentry only protects two key structures.
• Other kernel data structures may also require similar protection.
• This may gives versatile performance of Sentry, (if more data structure included)

Milan Rajpara

October 8, 2013

25
References
[1] Amani S. Ibrahim, James Hamlyn-Harris, John Grundy, Mohamed Almorsy, "Identifying OS Kernel Objects for
Run-Time Security Analysis", DOI: 10.1007/978-3-642-34601-9_6
[2] Amani S. Ibrahim, John Grundy, James Hamlyn-Harris, Mohamed Almorsy, "Operating System Kernel Data
Disambiguation to Support Security Analysis", DOI: 10.1007/978-3-642-34601-9_20
[3] Abhinav Srivastava, Jonathon Giffin, "Efficient Protection of Kernel Data Structures via Object Partitioning", DOI:
10.1145/2420950.2421012
[4] RFC: Linux kernel merging. https://lists.ubuntu.com/archives/kernel-team/2011-October/017471.html
[5] Rootkits detail by Symantec http://www.symantec.com/avcenter/reference/windows.rootkit.overview.pdf
[6] Windows Research Kernel https://www.facultyresourcecenter.com/curriculum/pfv.aspx?ID=7366&c1=enus&c2=0
[7] TDL Rootkit: http://www.theregister.co.uk/2010/11/16/tdl_rootkit_does_64_bit_windows
[8] Windows hooks: http://msdn.microsoft.com/en-us/library/ms644959(v=vs.85).aspx
[9] K. J. Biba. Integrity considerations for secure computer systems. Technical Report MTR-3153, Mitre, Apr. 1977

Milan Rajpara

October 8, 2013

26
Thank you 
Questions
__________________________
- Milan Rajpara

27

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Analyzing Kernel Security and Approaches for Improving it

  • 1. Analyzing Kernel Security and Approaches for Improving It Milan Rajpara IT Systems and Network Security Gujarat Technological University C DAC Ahmedabad Pune
  • 2. Agenda • Kernel Introduction • Necessity for Kernel Security • Kernel breach • Analyzing Kernel Security • Improving Approaches • Future Work Milan Rajpara October 8, 2013 2
  • 3. What is Kernel ? • A computer program that manages input/output requests from software and translates them into data processing instructions for the central processing unit and other electronic components of a computer. [Wikipedia] • The kernel is a fundamental part of a modern computer's operating system. • OS rests on a outer ring, and application above that. Fig: Privilege rings for the x86 available in protected mode [Source: Wikipedia] Milan Rajpara October 8, 2013 3
  • 4. Necessity for Kernel Security • Kernel, a vary basic (core) part of the Operating Systems • Single vulnerability will be exposes large number of systems • Increasing of Cloud Usage with Virtual Systems • Smartphones now is in every hand Milan Rajpara October 8, 2013 4
  • 5. We talk on .. • Kernels for General Purpose Operating System • Some Linux flavor gives Server Optimized Kernel • Ex. Ubuntu older then 12.04, were gave this option. Since 12.04, linux-image-server is merged into linuximage-generic, there is no difference between Generic and Server kernel. [4] • Windows do not disclose. • Kernels which Constructed in C language • Almost kernels are in C • Improvement for Monolithic kernels • All work performed in Virtual environment • The Xen, and VMware used Milan Rajpara October 8, 2013 5
  • 6. How Kernel Affected ? • By Kernel level rootkits • Manipulating pointers • Manipulating data • Direct Kernel Object Manipulation (DKOM) • By Boot-kits • Via hooking techniques • Direct Hardware or Firmware injection Milan Rajpara October 8, 2013 6
  • 7. Effect of this Attacks • Escalate a process’ privileges by overwriting the process’ credentials • Hide itself by illicitly removing data structures identifying their presence from loaded drivers • Eliding task structures for the processes from the kernel’s process accounting list • Alter the overall behavior of OS without injecting any malicious code into the kernel address space, by just pointer manipulating. Milan Rajpara October 8, 2013 7
  • 8. How to analyze the Kernel Security • Find the most critical objects of the kernel, without prior knowledge of the OS kernel data layout in memory • Identifying OS Kernel Objects for Run-time Security Analysis • Sort-out objects which are vulnerable to hijack • Do Kernel Data Disambiguation • This will make the system easy to analyze Milan Rajpara October 8, 2013 8
  • 9. Most critical objects in Kernel • Windows and Linux, the core kernel part are mostly written in C • 40% inter-data structure relations are Pointer based • 35% of these are Generic Pointers • Pointers which defines at run time, no initial value or data type is associated • 28% kernel data structure are well known objects Milan Rajpara October 8, 2013 9
  • 10. Generic Pointer Problem • It is the weak link in kernel security • Use of void pointers *, assists hackers to point somewhere else • Use of NULL pointers (to implements linklist), helps hackers to hide / change runtime objects. • Use of Casting in C • Enables the hackers to exploit data structure layout in physical memory Milan Rajpara October 8, 2013 10
  • 11. To Find Critical Objects 1. Memory Mapping techniques • Travers address space from global variables via pointer dereferencing until reaching running object. • according to a predefined kernel data definition for each kernel version. 2. Value Invariant Approaches • Use the value invariants of certain fields or of a whole data structure as a signature to scan the memory for matching running instances. Ex. DeepScanner, DIMSIM • Drawbacks of this approaches - Not very accurate - Require a predefined definition of the kernel data layout - Not effective when memory mapping and object reachability information is not available. - High performance overhead Milan Rajpara October 8, 2013 11
  • 12. To Find Critical Objects 3. DIGGER [1] • Uncover all system runtime objects without any prior knowledge of the OS kernel data layout in memory. • First it performs offline and constructs type-graph (which is used to enable systematic memory traversal of the object details). • Then it uses the 4-byte pool memory tagging schema (to uncover kernel runtime objects from the kernel address space.) • (+) • Accurate result • Low performance overhead • Fast and nearly complete coverage Milan Rajpara October 8, 2013 12
  • 13. DIGGER & KDD • DIGGER uses the KDD (Kernel Data Disambiguator) to precisely models the direct and indirect relations between data structures. • KDD is a static analysis tool that operates offline on an OS kernel’s source code • Generates a type-graph for the kernel data with direct and indirect relations between structures, models data structures [2] • KDD disambiguates pointer-based relations (including generic pointers) • by performing static points-to analysis on the kernel’s source code. • Points-to analysis is the problem of determining statically a set of locations to which a given variable may point to at runtime. Milan Rajpara October 8, 2013 13
  • 14. KDD Operation Source: Ref [2] AST: Abstract Syntax Tree (high-level intermediate representation for the source code ) Milan Rajpara October 8, 2013 14
  • 15. KDD Operation • Interprocedural Analysis 1: Takes AST and differentiate it • Gets: Variables, Procedure definition, Procedure call, etc.. . • Interprocedural Analysis 2: Do points-to analysis across different files to perform whole-program analysis. • Context Sensitive Analysis: • It uses Procedure Dependency Graph (PDG) consists of nodes representing the statements of the data dependency in the program. • context-sensitive analysis solves two problems: the calling context and the indirect (implicit) relations between nodes. Milan Rajpara October 8, 2013 15
  • 16. Soundness and Precision of KDD • The points-to analysis algorithm is sound if the points-to set for each variable contains all its actual runtime targets, and is imprecise if the inferred set is larger than necessary. • Check on C programs from the SPEC2000 and SPEC2006 benchmark suites. • Achieved a high level of precision and 100% of soundness. • And 96% precision on Windows (WRK*, Vista) and Linux kernel (v3.0.22). [2] *WRK – Windows Research Kernel, the only available code from windows [6] Milan Rajpara October 8, 2013 16
  • 17. DIGGER Approach Source: Ref [1] Milan Rajpara October 8, 2013 17
  • 18. DIGGER Approach • Static Analysis Component: from KDD • Signature Extraction Component: • When the object manager allocates a memory pool block, it associates with a pool tag (pool tag is a unique four-byte tag for each object type.) Uses this tag to uncover the kernel objects running instances, and they are static and cannot be changed during object runtime. • Dynamic Memory Analysis Component: Extract the object details, • From Pool Tag, it gets the pool block start memory address and the object’s start address. Milan Rajpara October 8, 2013 18
  • 19. Analyzing Kernel through DIGGER Gives … • Disambiguate the points-to relations between data structures, all without any prior knowledge of the OS kernel data layout. • Robust and quite small signature size to uncover runtime objects, enhancing performance • Able to keep track of all critical objects of kernel Milan Rajpara October 8, 2013 19
  • 20. Protection of Kernel • Protect the generic pointers. • Microsoft added a feature PatchGuard, which blocks kernel mode drivers from altering sensitive parts of the Windows kernel. • But TDL (rootkit) manages to circumvent this protection as well, by altering a machine's MBR so that it can intercept Windows startup routines. [7] • One approach is use of “Object Partitioning” to protect kernel data structure. [3] • Uses Sentry, that creates access control protections for security-critical kernel data. Milan Rajpara October 8, 2013 20
  • 21. Sentry Architecture • Sentry protects critical data and enforces data access restrictions based upon the origin of the access within the code of the kernel and its modules or drivers. [3] • The data integrity model is straightforward and matches that of the Biba ring policy [9] • The malicious code that modifies privileges by directly writing to memory is in a loaded module and not in the core kernel code, so Sentry will prevent the write Milan Rajpara October 8, 2013 21
  • 22. Kernel Memory Access Control • Protect data structure from DCOM • Sentry’s design uses a hypervisor to remain isolated from an untrusted kernel • To keep the overhead low, Sentry uses memory partitioning to lay out sensitive data on separate memory pages and protects those pages using the hypervisor • The policy enforcer mediates attempted writes to protected data and uses the policy to determine when writes should be permitted. Milan Rajpara October 8, 2013 22
  • 23. Working of Sentry • Identifying Security-Critical Members • Activation of mediated access • Instruction emulation • Secure execution history extraction Milan Rajpara October 8, 2013 23
  • 24. Evaluation of Sentry • Performance • Low performance overhead • more performance van be achieved by memory layout optimization • False Positive Analysis • There were no instances when security-critical kernel data protected by Sentry was directly modified by a benign driver. • Sentry provided a 100% detection rate for DKOM rootkits Milan Rajpara October 8, 2013 24
  • 25. Future Work • Detect all kernel data structures automatically, beyond the kernel version • The DIGGER can only be used to analyze Windows Kernels. • The current prototype of Sentry only protects two key structures. • Other kernel data structures may also require similar protection. • This may gives versatile performance of Sentry, (if more data structure included) Milan Rajpara October 8, 2013 25
  • 26. References [1] Amani S. Ibrahim, James Hamlyn-Harris, John Grundy, Mohamed Almorsy, "Identifying OS Kernel Objects for Run-Time Security Analysis", DOI: 10.1007/978-3-642-34601-9_6 [2] Amani S. Ibrahim, John Grundy, James Hamlyn-Harris, Mohamed Almorsy, "Operating System Kernel Data Disambiguation to Support Security Analysis", DOI: 10.1007/978-3-642-34601-9_20 [3] Abhinav Srivastava, Jonathon Giffin, "Efficient Protection of Kernel Data Structures via Object Partitioning", DOI: 10.1145/2420950.2421012 [4] RFC: Linux kernel merging. https://lists.ubuntu.com/archives/kernel-team/2011-October/017471.html [5] Rootkits detail by Symantec http://www.symantec.com/avcenter/reference/windows.rootkit.overview.pdf [6] Windows Research Kernel https://www.facultyresourcecenter.com/curriculum/pfv.aspx?ID=7366&c1=enus&c2=0 [7] TDL Rootkit: http://www.theregister.co.uk/2010/11/16/tdl_rootkit_does_64_bit_windows [8] Windows hooks: http://msdn.microsoft.com/en-us/library/ms644959(v=vs.85).aspx [9] K. J. Biba. Integrity considerations for secure computer systems. Technical Report MTR-3153, Mitre, Apr. 1977 Milan Rajpara October 8, 2013 26