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High System-Code Security with Low Overhead Jonas Wagner, Volodymyr Kuznetsov, George Candea, and Johannes Kinder cole Polytechnique Fdrale Royal Holloway, de Lausanne University of London High System-Code Security? Todays so fu ware


  1. High System-Code Security with Low Overhead Jonas Wagner, Volodymyr Kuznetsov, George Candea, and Johannes Kinder École Polytechnique Fédérale Royal Holloway, de Lausanne University of London

  2. High System-Code Security? Today’s so fu ware is dangerous. Example: OpenSSL 
 Overflow in ssl/t1_lib.c:3997 → OpenSSL contains 53,073 memory accesses. 
 How to protect them all?

  3. Protect all dangerous operations using sanity checks ✓ Checks are automatically added at compile time ✓ No source code modification is needed if (!isValidAddress(p)) { reportError(p); *p = 42; abort(); AddressSanitizer } *p = 42;

  4. Problem: Sanity checks cause high performance overhead Tool Avg. Overhead AddressSanitizer 73% (memory errors) SoftBound/CETS 116% (full memory safety) UndefinedBehaviorSanitizer 71% (integer overflows, type errors…) Assertions, code contracts, … depends

  5. Problem: Sanity checks cause high performance overhead People use checks heavily for testing, but disable them in production Goal: checks in production

  6. Insight: Checks are not all equal Most of the overhead comes from a few expensive checks Checks in hot code, each executed many times Most of the protection comes from many cheap checks Checks in cold code

  7. Our Approach : ASAP As Safe As Possible Lets users choose their overhead budget (e.g., 5%) Automatically identifies sanity checks in so fu ware Analyzes the cost of every check Selects as many checks as fit in the user’s budget Most of the overhead comes from a few expensive checks Most of the protection comes from many cheap checks

  8. ASAP Insight & Results 100% A few checks are very expensive 80% A user on a 5% budget Fraction of critical operations Sanity level can get 87% of the protection 60% protected by a check Most protection comes 40% from cheap checks 20% 0% 0% 10% 20% 30% 40% 50% 60% Overhead

  9. Outline Introduction: What is ASAP? Design Key Algorithms Results Conclusion

  10. Design ASAP is built into the compiler ✓ Easy to use (set CC and CFLAGS) ✓ Compatible (parallel compilation, …) Compiler (LLVM) Profiler: 
 Optimizer: 
 Identify 
 measure 
 select maximum sanity checks check costs set of checks

  11. Users use ASAP like a regular compiler that adds checks ASAP + .cc .h .exe .llvm ASAP stores intermediate compiler output

  12. Users use ASAP like a regular compiler that adds checks ASAP + .cc .h .exe .llvm ASAP generates a program variant with profiling instrumentation. Users run this to measure check costs. ASAP Costs Profiler .llvm .exe Workload

  13. Users use ASAP like a regular compiler that adds checks ASAP + .cc .h .exe .llvm ASAP generates a program variant with profiling instrumentation. Users run this to measure check costs. ASAP Costs Profiler .llvm .exe Workload ASAP uses costs & budget to generate an optimized program ASAP + + .exe Costs Budget Optimizer .llvm

  14. Outline Introduction: What is ASAP? Design Key Algorithms Results Conclusion

  15. ASAP Budget .exe

  16. ASAP Identify check (de)activate instructions checks Measure compiler driver Quantify check cost Budget IDE integration .exe protection profiling workload Can users trust ASAP If ASAP says you’re 87% to select checks that protected, what does use the least CPU cycles? this mean?

  17. Measure Check Cost ... if (!isValidAddress(p)) { reportError(p); abort(); } *p = 42; ...

  18. Measure Check Cost 1. Add profiling counters ... prof1++; if (!isValidAddress(p)) { prof2++; reportError(p); abort(); } prof3++; *p = 42; ...

  19. Measure Check Cost 1. Add profiling counters ... prof1++; 2. Identify check instructions if (!isValidAddress(p)) { prof2++; reportError(p); abort(); } prof3++; *p = 42; ...

  20. Measure Check Cost 1. Add profiling counters ... prof1++; 2. Identify check instructions if (!isValidAddress(p)) { 3. Use static model 
 prof2++; of cycles per instruction reportError(p); abort(); } prof3++; *p = 42; ...

  21. Measure Check Cost 1. Add profiling counters ... prof1++; 2. Identify check instructions if (!isValidAddress(p)) { 3. Use static model 
 prof2++; of cycles per instruction reportError(p); 4. Compute cost for check 
 abort(); } in CPU cycles: prof3++; X *p = 42; prof( i ) · cycles( i ) ... i ∈ check Precise cost in CPU cycles

  22. ASAP Identify check (de)activate instructions checks Measure compiler driver Quantify check cost Budget IDE integration .exe protection profiling workload If ASAP says you’re 87% protected, what does this mean?

  23. ASAP quantifies protection using the sanity level We would like to know the e ff ective protection level Methodology: measure how many bugs/vulnerabilities are e ff ectively prevented

  24. ASAP quantifies protection using the sanity level Experiment 1 We would like to know the Source code of Python 2.7 e ff ective protection level Bug: line that has received a Methodology: measure how patch between version 
 many bugs/vulnerabilities 2.7.1 and 2.7.8 are e ff ectively prevented

  25. Sanity level 87% ≈ 91% protection Buggy lines covered by checks 100% ASAP quantifies protection using the sanity level 80% We would like to know the 60% e ff ective protection level 40% Methodology: measure how 20% many bugs/vulnerabilities are e ff ectively prevented 0 0 20% 40% 60% 80% 100% Sanity level E ff ective Protection ≥ sanity level

  26. Experiment 2 Known bugs Project Bugs Python 3.4 3 OpenSSL 1 RIPE 10 Benchmarks All of these are in cold code

  27. Experiment 2 Experiment 3 Known bugs Vulnerabilities from CVE DB Project Bugs Analyze 145 vulnerabilities from 2014 • Memory errors Python 3.4 3 • Open source OpenSSL 1 • Patch available RIPE 10 • Error location known Benchmarks 83% of these are in cold code All of these are in cold code Checks in cold code provide real value

  28. Outline Introduction: What is ASAP? Design Key Algorithms Results Conclusion

  29. Results 120 100 Overhead for: Overhead in % SPEC benchmarks 80 AddressSanitizer 60 100% 40 20 sanity level 0 libquantum lbm soplex mcf namd astar bzip2 milc sphinx3 hmmer gobmk sjeng gcc povray

  30. Results 120 CPU cycles saved 100 Overhead for: Overhead in % SPEC benchmarks 80 AddressSanitizer 60 95% 40 20 sanity level 0 libquantum lbm soplex mcf namd astar bzip2 milc sphinx3 hmmer gobmk sjeng gcc povray

  31. Results 120 100 Overhead for: Overhead in % SPEC benchmarks 80 AddressSanitizer 60 90% 40 20 sanity level 0 libquantum lbm soplex mcf namd astar bzip2 milc sphinx3 hmmer gobmk sjeng gcc povray

  32. Results 120 Residual overhead 100 Overhead for: (not due to checks) Overhead in % SPEC benchmarks 80 AddressSanitizer 60 80% 40 20 sanity level 0 libquantum lbm soplex mcf namd astar bzip2 milc sphinx3 hmmer gobmk sjeng gcc povray

  33. Conclusion Protect your so fu ware! dslab.epfl.ch/proj/asap Run-time checks deliver strong protection at high cost ASAP select maximum Identify 
 measure 
 set of checks sanity checks check costs Budget .exe Most of the overhead comes from a few expensive checks Most of the protection comes from many cheap checks

  34. Backup slides

  35. ; <label>:0 %1 = load i32 * %fmap_i_ptr, align 4 %2 = zext i32 %1 to i64 %3 = getelementptr inbounds i32 * %eclass, i64 %2 %4 = ptrtoint i32 * %3 to i64 %5 = lshr i64 %4, 3 %6 = add i64 %5, 17592186044416 %7 = inttoptr i64 %6 to i8 %8 = load i8 * %7, align 1 %9 = icmp eq i8 %8, 0 br i1 %9, label %18, label %10 Sanity Check ; <label>:10 %11 = ptrtoint i32 * %3 to i64 %12 = and i64 %11, 7 %13 = add i64 %12, 3 in LLVM %14 = trunc i64 %13 to i8 %15 = icmp slt i8 %14, %8 br i1 %15 , label %18, label %16 ; <label>:16 %17 = ptrtoint i32 * %3 to i64 call void @__asan_report_load4( i64 %17) #3 call void asm sideeffect "", ""() #3 unreachable ; <label>:18 %19 = load i32 * %3, align 4

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