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Proof-Carrying Code: A Language-Based Security Approach

Proof-Carrying Code: A Language-Based Security Approach. Thao Doan Wei Hu Liqian Luo Jinlin Yang CS851 Malware 11/16/2004. Outline. Introduction To Language-based Security Proof-carrying Code (PCC) Example 1: Network Packet Filters Example 2: A Certifying Compiler For Java

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Proof-Carrying Code: A Language-Based Security Approach

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  1. Proof-Carrying Code: A Language-Based Security Approach Thao Doan Wei Hu Liqian Luo Jinlin Yang CS851 Malware 11/16/2004

  2. Outline • Introduction To Language-based Security • Proof-carrying Code (PCC) • Example 1: Network Packet Filters • Example 2: A Certifying Compiler For Java • Issues With PCC • Discussion CS851 Malware

  3. Part 1 Introduction to Language-Based Security CS851 Malware

  4. Malicious code - A growing problem • What is malicious code? • “any code added, changed, removed from a software system in order to intentionally cause harm or subvert the intended function of the system.” • What makes it a growing problem? • Growing connectivity (the Internet) • Growing complexity of systems • Support for extensibility CS851 Malware

  5. Two well-known security design principles • Principle of Least Privilege • a component should be given the minimum privilege necessary to accomplish its task • Ex: file access • Principle of Minimum Trusted Computing Base • keep the TCB as small and simple as possible (~ the KISS principle) • Ex: JVM, Proof Checker of PCC CS851 Malware

  6. Approaches againstmalicious code • Analyze the code : before execution [reject] • Ex: scanning, compiler’s dataflow analysis • Rewrite the code : before execution [modify] • Ex: BEQZ R4, BadCode  BEQZ R4, GoodCode • Monitor the code : during execution [stop before harm] • Ex: OS’ page translation hardware • Audit the code : during execution [police on harm] • Ex: audit trail to assess and address the problem CS851 Malware

  7. Disadvantages of traditional approaches • Miss unseen cases • Trust entities required • Performance • Burden on consumers CS851 Malware

  8. Motivation of language based security • Is it possible to enforce security on the semantics or behavior of the code? • Types, logics, & proofs come into play • Examples • Type-Safe Languages • Proof-Carrying Code CS851 Malware

  9. Part 2 Proof-Carrying Code:Concept and Implementation CS851 Malware

  10. Type-safe languages • Type • gives semantic meaning to ultimately mere bits • associated either with values in memory or with objects • Type-safe languages: • have complete type systems • e.g., Java, C#, ML • Code producer writes code in a type-safe language • Code consumer ensures code is safe: • static checks (e.g., type checks) • dynamic checks (e.g., array-bound checks) CS851 Malware

  11. Cons of type-safe languages • Have large trusted computing base • many exploits of JVM itself has been reported http://www.cs.princeton.edu/sip/history/index.php3 • Require many run-time tests • casts, arrays, pointers, etc. • Incur inflexibility CS851 Malware

  12. Proof-carrying code (PCC) Code Consumer Code producer Publicizes safety policy Provides Proof Native Proof code Validates Proof CPU [Necula, POPL’97] CS851 Malware

  13. Benefits of PCC • Shifts the burden of ensuring the safety from code consumer to code producer • Can verify code in low-level languages • Fewer run-time checks • Tamperproof • Simpler, smaller, and faster TCB • No cryptography or external authentication required CS851 Malware

  14. Implementation of PCC • Proof generation theorem proving • extend first-order predicate logic to formalize the safety policy • Proof validation type checking • Edinburgh Logical Framework (LF) • map proof rules into types in LF CS851 Malware

  15. Code Consumer code in high level programming language safety Policy compiler 1. safety rules 2. module interface verification condition (VC) generator theorem prover safety predicate PCC system architecture validator Code Producer annotated assembly code Proof Generator proof native code CS851 Malware

  16. An example function on a DEC Alpha CS851 Malware

  17. Part 3 Example 1 - Network Packet Filters [Necula et. al. OSDI'96] CS851 Malware

  18. The problem • Examples • OS Extensions, Safe Mobile Code, Programming Language Interoperation • Previous Approaches • Hardware memory protection, Runtime checking, Interpretation • We want both safety and performance! CS851 Malware

  19. The solution - PCC CS851 Malware

  20. A PCC example • Goal • Test feasibility of PCC concept • Measure costs (proof size and validation time) • Choose simple but practical applications • Network Packet Filters CS851 Malware

  21. packet filter network monitoring application network Network packet filters user process space OS kernel CS851 Malware

  22. Safety policy CS851 Malware

  23. Safety policy • Follow the BSD Packet Filter (BPF) model of safety • The packet is read-only. • The scratch memory is read-write. • No backward branches. • Only aligned memory accesses. CS851 Malware

  24. Safety policy • Use first-order predicate logic extended with can_rd(addr)and can_wr(addr) • The precondition is: • aligned memory addresses on an 8-byte boundary • r0 (address of packet) • r1 (length of packet) • r2 (address of scratch memory (16 bytes)) CS851 Malware

  25. Code certification CS851 Malware

  26. Code certification • Step 1 - Compute a safety predicate for the code • for example: • For each LD r,n[rb] add can_rd(rb+n) • For each ST r,n[rb] add can_wr(rb+n) • Step 2 – Generate a proof (checkable) of the safety predicate CS851 Malware

  27. Performance – experiment setup • 4 packet filters: • 1 Accepts IP packets (8 instr.) • 2 Accepts IP packets for 128.2.206 (15 instr.) • 3 IP or ARP between 128.2.206 and 128.2.209 (47 instr.) • 4 TCP/IP packets for FTP (28 instr.) • Compared with: • Interpretation: BSD Packet Filter • Runtime Checking: Software Fault Isolation • Type-safe Language: Modula-3 CS851 Malware

  28. Per-packet delay • PCC packet filters: fastest possible on the architecture • The point: Safety without sacrificing performance! CS851 Malware

  29. Cost • Proofs are approx. 3 times larger than the code • Validation time: 0.3-1.8ms CS851 Malware

  30. Startup cost amortization • Conclusion: One-time validation cost amortized quickly CS851 Malware

  31. Conclusion • A very promising framework for ensuring safety of untrusted code • Achieves safety without sacrificing performance • Serious difficulties exist • Needs more experiments CS851 Malware

  32. Part 4 Example 2 - A certifying compiler for Java CS851 Malware

  33. Certifying compiler (recap) [Colby et. al. PLDI ‘00] Source Certifying VC Generator Native Code Compiler Annotations VC Generator Axioms VC & Rules Axioms VC & Rules Proof Proof Proof Checker Generator Code Producer Code Consumer CS851 Malware

  34. An example Class Poly{ Poly(float[] coefficients){…} float eval(float x){ float term = 1.0f; float result = 0.0f; for(int i=0; i<coefficients.length; i++){ result += coefficients[i] * term; term *= x; } return result; } private float[] coefficients; } CS851 Malware

  35. for(int i=0; i<coefficients.length; i++){ result += coefficients[i] * term; term *= x; } LOOP_ENTRY: fxch %st(1) // result on top of FPU LOOP_INV = {(lt edx (sel4 rm (add eax 4))), (ge edx, 0), (type f7 jfloat), (type f6 jfloat)} flds 8(%eax, %edx, 4) // load coefficients[i] fmul %st(2), %st(0) // *term faddp // +result fxch %st(1) // term on top of FPU fmuls 12(%ebp) // *x incl %edx // i++ cmpl %ecx, %edx // i<coefficients.length? jl LOOP_ENTRY // loop back if yes Loop Annotations CS851 Malware

  36. VC generation flds 8(%eax, %edx, 4) // load coefficients[i] prove: (saferd4 (add (sel4 rm_1 (add loc2_1 4)) (add (imul edx_3 4) 8))) It is safe to read coefficients[i] (rdArray4 (tyField (instFld A10 A32 A31) A30) A30 (sub0chk A34) szfloat (aidxi 4 (below1 (lt_b (geswap A38) A37)))) CS851 Malware

  37. CC for modern OO languages Key Challenges: • Handle advanced language features • Dynamic creation of objects • Exception handling • Floating point arithmetic • Optimization • Cost (time & space) CS851 Malware

  38. CC for Java • Handle dynamic object creation, exception handling, and float point arithmetic • Apply many standard optimizations • Proof size: 85% of the code size on average • Negligible checking time [Colby et. al. PLDI ‘00] CS851 Malware

  39. Demo http://raw.cs.berkeley.edu/Ginseng/Images/pccdemo.html CS851 Malware

  40. Part 5 Issues with PCC CS851 Malware

  41. Issues with PCC • Assuming: • Trusted VCgen • Trusted proof checker • No bug in logical axioms • No bug in typing rules • Type-specialized • built-in understanding of a particular type system CS851 Malware

  42. Foundational PCC • Code provider provides: - executable code - proof in foundational logic • Eliminate implicit built-in logic  Explicitly prove relevant concepts and their properties down to the foundation of mathematics CS851 Malware

  43. Comparisons CS851 Malware

  44. Foundational PCC • More secure • More flexible [Appel, LICS ’01] CS851 Malware

  45. Discussion • What do you think is the hardest part in PCC implementation? • Which security problems doesn’t PCC address? • To what extent can it be applied? • Is it easy for legacy systems to adopt PCC? CS851 Malware

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