For EIP-4844, Ethereum purchasers want the power to compute and confirm KZG commitments. Quite than every shopper rolling their very own crypto, researchers and builders got here collectively to write down c-kzg-4844, a comparatively small C library with bindings for higher-level languages. The concept was to create a sturdy and environment friendly cryptographic library that each one purchasers might use. The Protocol Safety Analysis crew on the Ethereum Basis had the chance to assessment and enhance this library. This weblog submit will talk about some issues we do to make C initiatives safer.
Fuzz
Fuzzing is a dynamic code testing approach that includes offering random inputs to find bugs in a program. LibFuzzer and afl++ are two standard fuzzing frameworks for C initiatives. They’re each in-process, coverage-guided, evolutionary fuzzing engines. For c-kzg-4844, we used LibFuzzer since we have been already well-integrated with LLVM challenge’s different choices.
Here is the fuzzer for verify_kzg_proof, one in all c-kzg-4844’s capabilities:
#embody "../base_fuzz.h" static const size_t COMMITMENT_OFFSET = 0; static const size_t Z_OFFSET = COMMITMENT_OFFSET + BYTES_PER_COMMITMENT; static const size_t Y_OFFSET = Z_OFFSET + BYTES_PER_FIELD_ELEMENT; static const size_t PROOF_OFFSET = Y_OFFSET + BYTES_PER_FIELD_ELEMENT; static const size_t INPUT_SIZE = PROOF_OFFSET + BYTES_PER_PROOF; int LLVMFuzzerTestOneInput(const uint8_t* information, size_t dimension) { initialize(); if (dimension == INPUT_SIZE) { bool okay; verify_kzg_proof( &okay, (const Bytes48 *)(information + COMMITMENT_OFFSET), (const Bytes32 *)(information + Z_OFFSET), (const Bytes32 *)(information + Y_OFFSET), (const Bytes48 *)(information + PROOF_OFFSET), &s ); } return 0; }
When executed, that is what the output appears to be like like. If there have been an issue, it could write the enter to disk and cease executing. Ideally, you must have the ability to reproduce the issue.
There’s additionally differential fuzzing, which is a way which fuzzes two or extra implementations of the identical interface and compares the outputs. For a given enter, if the output is totally different, and also you anticipated them to be the identical, you realize one thing is improper. This method could be very standard in Ethereum as a result of we prefer to have a number of implementations of the identical factor. This diversification supplies an additional stage of security, realizing that if one implementation have been flawed the others could not have the identical concern.
For KZG libraries, we developed kzg-fuzz which differentially fuzzes c-kzg-4844 (by means of its Golang bindings) and go-kzg-4844. To this point, there have not been any variations.
Protection
Subsequent, we used llvm-profdata and llvm-cov to generate a protection report from working the assessments. This can be a nice technique to confirm code is executed (“lined”) and examined. See the protection goal in c-kzg-4844’s Makefile for an instance of how one can generate this report.
When this goal is run (i.e., make protection) it produces a desk that serves as a high-level overview of how a lot of every perform is executed. The exported capabilities are on the prime and the non-exported (static) capabilities are on the underside.
There may be a number of inexperienced within the desk above, however there may be some yellow and pink too. To find out what’s and is not being executed, consult with the HTML file (protection.html) that was generated. This webpage reveals the complete supply file and highlights non-executed code in pink. On this challenge’s case, many of the non-executed code offers with hard-to-test error instances comparable to reminiscence allocation failures. For instance, here is some non-executed code:
Originally of this perform, it checks that the trusted setup is sufficiently big to carry out a pairing test. There is not a take a look at case which supplies an invalid trusted setup, so this does not get executed. Additionally, as a result of we solely take a look at with the proper trusted setup, the results of is_monomial_form is all the time the identical and does not return the error worth.
Profile
We do not advocate this for all initiatives, however since c-kzg-4844 is a efficiency crucial library we expect it is vital to profile its exported capabilities and measure how lengthy they take to execute. This will help determine inefficiencies which might doubtlessly DoS nodes. For this, we used gperftools (Google Efficiency Instruments) as a substitute of llvm-xray as a result of we discovered it to be extra feature-rich and simpler to make use of.
The next is a straightforward instance which profiles my_function. Profiling works by checking which instruction is being executed every now and then. If a perform is quick sufficient, it might not be observed by the profiler. To cut back the prospect of this, it’s possible you’ll have to name your perform a number of occasions. On this instance, we name my_function 1000 occasions.
#embody <gperftools/profiler.h> int task_a(int n) { if (n <= 1) return 1; return task_a(n - 1) * n; } int task_b(int n) { if (n <= 1) return 1; return task_b(n - 2) + n; } void my_function(void) { for (int i = 0; i < 500; i++) { if (i % 2 == 0) { task_a(i); } else { task_b(i); } } } int important(void) { ProfilerStart("instance.prof"); for (int i = 0; i < 1000; i++) { my_function(); } ProfilerStop(); return 0; }
Use ProfilerStart(“<filename>”) and ProfilerStop() to mark which elements of your program to profile. When re-compiled and executed, it is going to write a file to disk with profiling information. You may then use pprof to visualise this information.
Right here is the graph generated from the command above:
Here is a much bigger instance from one in all c-kzg-4844’s capabilities. The next picture is the profiling graph for compute_blob_kzg_proof. As you may see, 80% of this perform’s time is spent performing Montgomery multiplications. That is anticipated.
Reverse
Subsequent, view your binary in a software program reverse engineering (SRE) instrument comparable to Ghidra or IDA. These instruments will help you perceive how high-level constructs are translated into low-level machine code. We expect it helps to assessment your code this fashion; like how studying a paper in a unique font will drive your mind to interpret sentences otherwise. It is also helpful to see what kind of optimizations your compiler makes. It is uncommon, however generally the compiler will optimize out one thing which it deemed pointless. Hold a watch out for this, one thing like this really occurred in c-kzg-4844, a few of the assessments have been being optimized out.
Whenever you view a decompiled perform, it won’t have variable names, complicated sorts, or feedback. When compiled, this info is not included within the binary. It will likely be as much as you to reverse engineer this. You may usually see capabilities are inlined right into a single perform, a number of variables declared in code are optimized right into a single buffer, and the order of checks are totally different. These are simply compiler optimizations and are typically wonderful. It could assist to construct your binary with DWARF debugging info; most SREs can analyze this part to supply higher outcomes.
For instance, that is what blob_to_kzg_commitment initially appears to be like like in Ghidra:
With a little bit work, you may rename variables and add feedback to make it simpler to learn. Here is what it might appear like after a couple of minutes:
Static Evaluation
Clang comes built-in with the Clang Static Analyzer, which is a superb static evaluation instrument that may determine many issues that the compiler will miss. Because the title “static” suggests, it examines code with out executing it. That is slower than the compiler, however so much quicker than “dynamic” evaluation instruments which execute code.
Here is a easy instance which forgets to free arr (and has one other drawback however we’ll discuss extra about that later). The compiler won’t determine this, even with all warnings enabled as a result of technically that is fully legitimate code.
#embody <stdlib.h> int important(void) { int* arr = malloc(5 * sizeof(int)); arr[5] = 42; return 0; }
The unix.Malloc checker will determine that arr wasn’t freed. The road within the warning message is a bit deceptive, however it is sensible if you consider it; the analyzer reached the return assertion and observed that the reminiscence hadn’t been freed.
Not all the findings are that straightforward although. Here is a discovering that Clang Static Analyzer present in c-kzg-4844 when initially launched to the challenge:
Given an surprising enter, it was potential to shift this worth by 32 bits which is undefined habits. The answer was to limit the enter with CHECK(log2_pow2(n) != 0) in order that this was unattainable. Good job, Clang Static Analyzer!
Sanitize
Santizers are dynamic evaluation instruments which instrument (add directions) to packages which may level out points throughout execution. These are notably helpful at discovering frequent errors related to reminiscence dealing with. Clang comes built-in with a number of sanitizers; listed below are the 4 we discover most helpful and simple to make use of.
Tackle
AddressSanitizer (ASan) is a quick reminiscence error detector which may determine out-of-bounds accesses, use-after-free, use-after-return, use-after-scope, double-free, and reminiscence leaks.
Right here is identical instance from earlier. It forgets to free arr and it’ll set the sixth component in a 5 component array. This can be a easy instance of a heap-buffer-overflow:
#embody <stdlib.h> int important(void) { int* arr = malloc(5 * sizeof(int)); arr[5] = 42; return 0; }
When compiled with -fsanitize=handle and executed, it is going to output the next error message. This factors you in an excellent path (a 4-byte write in important). This binary could possibly be considered in a disassembler to determine precisely which instruction (at important+0x84) is inflicting the issue.
Equally, here is an instance the place it finds a heap-use-after-free:
#embody <stdlib.h> int important(void) { int *arr = malloc(5 * sizeof(int)); free(arr); return arr[2]; }
It tells you that there is a 4-byte learn of freed reminiscence at important+0x8c.
Reminiscence
MemorySanitizer (MSan) is a detector of uninitialized reads. Here is a easy instance which reads (and returns) an uninitialized worth:
int important(void) { int information[2]; return information[0]; }
When compiled with -fsanitize=reminiscence and executed, it is going to output the next error message:
Undefined Habits
UndefinedBehaviorSanitizer (UBSan) detects undefined habits, which refers back to the state of affairs the place a program’s habits is unpredictable and never specified by the langauge normal….
