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For EIP-4844, Ethereum shoppers want the power to compute and confirm KZG commitments. Fairly 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 every one shoppers may use. The Protocol Safety Analysis workforce on the Ethereum Basis had the chance to evaluation and enhance this library. This weblog put up will talk about some issues we do to make C tasks 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 widespread fuzzing frameworks for C tasks. 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 mission’s different choices.
This is the fuzzer for verify_kzg_proof, considered one of c-kzg-4844’s features:
#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* knowledge, size_t dimension) { initialize(); if (dimension == INPUT_SIZE) { bool okay; verify_kzg_proof( &okay, (const Bytes48 *)(knowledge + COMMITMENT_OFFSET), (const Bytes32 *)(knowledge + Z_OFFSET), (const Bytes32 *)(knowledge + Y_OFFSET), (const Bytes48 *)(knowledge + PROOF_OFFSET), &s ); } return 0; }
When executed, that is what the output seems like. If there have been an issue, it could write the enter to disk and cease executing. Ideally, it’s best to be capable 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 recognize one thing is incorrect. This method could be very widespread in Ethereum as a result of we wish to have a number of implementations of the identical factor. This diversification gives an additional degree of security, understanding that if one implementation have been flawed the others could not have the identical problem.
For KZG libraries, we developed kzg-fuzz which differentially fuzzes c-kzg-4844 (by its Golang bindings) and go-kzg-4844. Up to now, there have not been any variations.
Protection
Subsequent, we used llvm-profdata and llvm-cov to generate a protection report from operating the assessments. This can be a nice option to confirm code is executed (“coated”) and examined. See the coverage goal in c-kzg-4844’s Makefile for an instance of 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 features are on the high and the non-exported (static) features are on the underside.
There may be numerous 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 your complete supply file and highlights non-executed code in pink. On this mission’s case, many of the non-executed code offers with hard-to-test error circumstances corresponding to reminiscence allocation failures. For instance, here is some non-executed code:
Initially of this perform, it checks that the trusted setup is large enough to carry out a pairing verify. There is not a check case which gives an invalid trusted setup, so this does not get executed. Additionally, as a result of we solely check with the right trusted setup, the results of is_monomial_form is at all times the identical and does not return the error worth.
Profile
We do not suggest this for all tasks, however since c-kzg-4844 is a efficiency essential library we expect it is vital to profile its exported features and measure how lengthy they take to execute. This might help establish inefficiencies which may probably 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 occasionally. If a perform is quick sufficient, it will not be seen by the profiler. To scale back the prospect of this, you might must 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 primary(void) { ProfilerStart("instance.prof"); for (int i = 0; i < 1000; i++) { my_function(); } ProfilerStop(); return 0; }
Use ProfilerStart(“<filename>”) and ProfilerStop() to mark which components of your program to profile. When re-compiled and executed, it’s going to write a file to disk with profiling knowledge. You may then use pprof to visualise this knowledge.
Right here is the graph generated from the command above:
This is an even bigger instance from considered one of c-kzg-4844’s features. 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) software corresponding to Ghidra or IDA. These instruments might help you perceive how high-level constructs are translated into low-level machine code. We expect it helps to evaluation your code this fashion; like how studying a paper in a distinct font will power your mind to interpret sentences in a different way. It is also helpful to see what sort 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 truly occurred in c-kzg-4844, some of the tests were being optimized out.
If you view a decompiled perform, it is not going to have variable names, complicated sorts, or feedback. When compiled, this info is not included within the binary. Will probably be as much as you to reverse engineer this. You may usually see features 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 usually positive. It might 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 seems like in Ghidra:
With somewhat work, you may rename variables and add feedback to make it simpler to learn. This is what it may appear like after a couple of minutes:
Static Evaluation
Clang comes built-in with the Clang Static Analyzer, which is a superb static evaluation software that may establish 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 quite a bit sooner than “dynamic” evaluation instruments which execute code.
This is a easy instance which forgets to free arr (and has one other drawback however we are going to speak extra about that later). The compiler is not going to establish this, even with all warnings enabled as a result of technically that is fully legitimate code.
#embody <stdlib.h> int primary(void) { int* arr = malloc(5 * sizeof(int)); arr[5] = 42; return 0; }
The unix.Malloc checker will establish that arr wasn’t freed. The road within the warning message is a bit deceptive, nevertheless it is smart if you concentrate on it; the analyzer reached the return assertion and seen that the reminiscence hadn’t been freed.
Not the entire findings are that easy although. This is a discovering that Clang Static Analyzer present in c-kzg-4844 when initially launched to the mission:
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 here are the 4 we discover most helpful and simple to make use of.
Deal with
AddressSanitizer (ASan) is a quick reminiscence error detector which may establish 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 primary(void) { int* arr = malloc(5 * sizeof(int)); arr[5] = 42; return 0; }
When compiled with -fsanitize=handle and executed, it’s going to output the next error message. This factors you in a superb path (a 4-byte write in primary). This binary may very well be seen in a disassembler to determine precisely which instruction (at primary+0x84) is inflicting the issue.
Equally, here is an instance the place it finds a heap-use-after-free:
#embody <stdlib.h> int primary(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 primary+0x8c.
Reminiscence
MemorySanitizer (MSan) is a detector of uninitialized reads. This is a easy instance which reads (and returns) an uninitialized worth:
int primary(void) { int knowledge[2]; return knowledge[0]; }
When compiled with -fsanitize=reminiscence and executed, it’s going to output the next error message:
Undefined Conduct
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 customary. Some frequent examples of this are accessing out-of-bounds reminiscence, dereferencing an invalid pointer, studying uninitialized variables, and overflow of a signed integer. For instance, right here we increment INT_MAX which is undefined habits.
#embody <limits.h> int primary(void) { int a = INT_MAX; return a + 1; }
When compiled with -fsanitize=undefined and executed, it’s going to output the next error message which tells us precisely the place the issue is and what the situations are:
Thread
ThreadSanitizer (TSan) detects knowledge races, which may happen in multi-threaded packages when two or extra threads entry a shared reminiscence location on the similar time. This example introduces unpredictability and might result in undefined habits. This is an instance wherein two threads increment a world counter variable. There are no locks or semaphores, so it is solely potential that these two threads will increment the variable on the similar time.
#embody <pthread.h> int counter = 0; void *increment(void *arg) { (void)arg; for (int i = 0; i < 1000000; i++) counter++; return NULL; } int primary(void) { pthread_t thread1, thread2; pthread_create(&thread1, NULL, increment, NULL); pthread_create(&thread2, NULL, increment, NULL); pthread_join(thread1, NULL); pthread_join(thread2, NULL); return 0; }
When compiled with -fsanitize=thread and executed, it’s going to output the next error message:
This error message tells us that there is a knowledge race. In two threads, the increment perform is writing to the identical 4 bytes on the similar time. It even tells us that the reminiscence is counter.
Valgrind
Valgrind is a strong instrumentation framework for constructing dynamic evaluation instruments, however its finest identified for figuring out reminiscence errors and leaks with its built-in Memcheck software.
The next picture reveals the output from operating c-kzg-4844’s assessments with Valgrind. Within the pink field is a sound discovering for a “conditional soar or transfer [that] is dependent upon uninitialized worth(s).”
This identified an edge case in expand_root_of_unity. If the incorrect root of unity or width have been offered, it was potential that the loop will break earlier than out[width] was initialized. On this state of affairs, the ultimate verify would rely upon an uninitialized worth.
static C_KZG_RET expand_root_of_unity( fr_t *out, const fr_t *root, uint64_t width ) { out[0] = FR_ONE; out[1] = *root; for (uint64_t i = 2; !fr_is_one(&out[i - 1]); i++) { CHECK(i <= width); blst_fr_mul(&out[i], &out[i - 1], root); } CHECK(fr_is_one(&out[width])); return C_KZG_OK; }
Safety Assessment
After growth stabilizes, it has been completely examined, and your workforce has manually reviewed the codebase themselves a number of occasions, it is time to get a safety evaluation by a good safety group. This would possibly not be a stamp of approval, nevertheless it reveals that your mission is at the least considerably safe. Be mindful there isn’t a such factor as good safety. There’ll at all times be the danger of vulnerabilities.
For c-kzg-4844 and go-kzg-4844, the Ethereum Basis contracted Sigma Prime to conduct a safety evaluation. They produced this report with 8 findings. It comprises one essential vulnerability in go-kzg-4844 that was a extremely good discover. The BLS12-381 library that go-kzg-4844 makes use of, gnark-crypto, had a bug which allowed invalid G1 and G2 factors to be sucessfully decoded. Had this not been mounted, this might have resulted in a consensus bug (a disagreement between implementations) in Ethereum.
Bug Bounty
If a vulnerability in your mission may very well be exploited for positive aspects, like it’s for Ethereum, think about organising a bug bounty program. This permits safety researchers, or anybody actually, to submit vulnerability reviews in alternate for cash. Usually, that is particularly for findings which may show that an exploit is feasible. If the bug bounty payouts are affordable, bug finders will notify you of the bug reasonably than exploiting it or promoting it to a different occasion. We suggest beginning your bug bounty program after the findings from the primary safety evaluation are resolved; ideally, the safety evaluation would price lower than the bug bounty payouts.
Conclusion
The event of sturdy C tasks, particularly within the essential area of blockchain and cryptocurrencies, requires a multi-faceted method. Given the inherent vulnerabilities related to the C language, a mixture of finest practices and instruments is important for producing resilient software program. We hope our experiences and findings from our work with c-kzg-4844 present worthwhile insights and finest practices for others embarking on related tasks.
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