Analyzing Kernel Security and Approaches for Improving it
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Analyzing Kernel Security and Approaches for Improving it

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This presentation gives a basic detail on kernel security and different approaches to improving it.

This presentation gives a basic detail on kernel security and different approaches to improving it.

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Analyzing Kernel Security and Approaches for Improving it Analyzing Kernel Security and Approaches for Improving it Presentation Transcript

  • 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