For EIP-4844, Ethereum shoppers want the power to compute and confirm KZG commitments. Fairly than every consumer rolling their very own crypto, researchers and builders got here collectively to jot down c-kzg-4844, a comparatively small C library with bindings for higher-level languages. The concept was to create a strong and environment friendly cryptographic library that each one shoppers may use. The Protocol Safety Analysis crew on the Ethereum Basis had the chance to evaluate and enhance this library. This weblog publish will talk about some issues we do to make C tasks safer.
Fuzz
Fuzzing is a dynamic code testing method that entails offering random inputs to find bugs in a program. LibFuzzer and afl++ are two fashionable 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 venture’s different choices.
This 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 measurement) { initialize(); if (measurement == 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 might write the enter to disk and cease executing. Ideally, it’s best to be capable of 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 completely different, and also you anticipated them to be the identical, one thing is mistaken. This system may be very fashionable in Ethereum as a result of we wish to have a number of implementations of the identical factor. This diversification supplies an additional degree of security, realizing that if one implementation have been flawed the others might not have the identical problem.
For KZG libraries, we developed kzg-fuzz which differentially fuzzes c-kzg-4844 (by way of its Golang bindings) and go-kzg-4844. Thus far, there have not been any variations.
Protection
Subsequent, we used llvm-profdata and llvm-cov to generate a protection report from operating the assessments. It is a nice technique to confirm code is executed (“coated”) and examined. See the coverage goal in c-kzg-4844’s Makefile for an instance of tips on how to 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 operate is executed. The exported capabilities are on the prime and the non-exported (static) capabilities are on the underside.
There may be numerous inexperienced within the desk above, however there may be some yellow and purple too. To find out what’s and is not being executed, confer with the HTML file (protection.html) that was generated. This webpage reveals your entire supply file and highlights non-executed code in purple. On this venture’s case, a lot of the non-executed code offers with hard-to-test error circumstances resembling reminiscence allocation failures. For instance, this is some non-executed code:
Originally of this operate, it checks that the trusted setup is sufficiently big to carry out a pairing verify. 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 would not return the error worth.
Profile
We do not suggest this for all tasks, however since c-kzg-4844 is a efficiency crucial library we predict it is vital to profile its exported capabilities and measure how lengthy they take to execute. This may also help determine inefficiencies which may 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 an easy instance which profiles my_function. Profiling works by checking which instruction is being executed on occasion. If a operate is quick sufficient, it will not be seen by the profiler. To cut back the possibility of this, it’s possible you’ll have to name your operate a number of instances. On this instance, we name my_function 1000 instances.
#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 should write a file to disk with profiling information. You possibly can then use pprof to visualise this information.
Right here is the graph generated from the command above:
This is an even 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’ll be able to see, 80% of this operate’s time is spent performing Montgomery multiplications. That is anticipated.
Reverse
Subsequent, view your binary in a software program reverse engineering (SRE) software resembling Ghidra or IDA. These instruments may also help you perceive how high-level constructs are translated into low-level machine code. We predict it helps to evaluate your code this manner; like how studying a paper in a unique font will drive your mind to interpret sentences in a different way. 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. Preserve an eye fixed out for this, one thing like this really occurred in c-kzg-4844, some of the tests were being optimized out.
While you view a decompiled operate, it is not going to have variable names, complicated sorts, or feedback. When compiled, this data is not included within the binary. It will likely be as much as you to reverse engineer this. You will typically see capabilities are inlined right into a single operate, a number of variables declared in code are optimized right into a single buffer, and the order of checks are completely different. These are simply compiler optimizations and are usually tremendous. It might assist to construct your binary with DWARF debugging data; 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 somewhat work, you’ll be able to 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 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 lots 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’ll discuss extra about that later). The compiler is not going to determine this, even with all warnings enabled as a result of technically that is utterly 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, but it surely is sensible 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 venture:
Given an sudden enter, it was potential to shift this worth by 32 bits which is undefined conduct. The answer was to limit the enter with CHECK(log2_pow2(n) != 0) in order that this was not possible. Good job, Clang Static Analyzer!
Sanitize
Santizers are dynamic evaluation instruments which instrument (add directions) to applications which may level out points throughout execution. These are notably helpful at discovering widespread 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 straightforward to make use of.
Deal with
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. It is 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=deal with and executed, it should output the next error message. This factors you in a superb course (a 4-byte write in important). This binary might be seen in a disassembler to determine precisely which instruction (at important+0x84) is inflicting the issue.
Equally, this 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. This 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 should output the next error message:
Undefined Conduct
UndefinedBehaviorSanitizer (UBSan) detects undefined conduct, which refers back to the scenario the place a program’s conduct is unpredictable and never specified by the langauge commonplace. Some widespread 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 conduct.
#embody <limits.h> int important(void) { int a = INT_MAX; return a + 1; }
When compiled with -fsanitize=undefined and executed, it should output the next error message which tells us precisely the place the issue is and what the circumstances are:
Thread
ThreadSanitizer (TSan) detects information races, which may happen in multi-threaded applications when two or extra threads entry a shared reminiscence location on the identical time. This example introduces unpredictability and might result in undefined conduct. This is an instance by which two threads increment a worldwide counter variable. There are not any locks or semaphores, so it is solely potential that these two threads will increment the variable on the identical time.
#embody <pthread.h> int counter = 0; void *increment(void *arg) { (void)arg; for (int i = 0; i < 1000000; i++) counter++; return NULL; } int important(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 should output the next error message:
This error message tells us that there is a information race. In two threads, the increment operate is writing to the identical 4 bytes on the identical time. It even tells us that the reminiscence is counter.
Valgrind
Valgrind is a robust 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 purple field is a legitimate discovering for a “conditional soar or transfer [that] depends upon uninitialized worth(s).”
This identified an edge case in expand_root_of_unity. If the mistaken root of unity or width have been supplied, it was potential that the loop will break earlier than out[width] was initialized. On this scenario, 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 improvement stabilizes, it has been totally examined, and your crew has manually reviewed the codebase themselves a number of instances, it is time to get a safety evaluate by a good safety group. This would possibly not be a stamp of approval, but it surely reveals that your venture is at the very least considerably safe. Have in mind there isn’t a such factor as good safety. There’ll all the time be the danger of vulnerabilities.
For c-kzg-4844 and go-kzg-4844, the Ethereum Basis contracted Sigma Prime to conduct a safety evaluate. They produced this report with 8 findings. It comprises one crucial 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 fastened, this might have resulted in a consensus bug (a disagreement between implementations) in Ethereum.
Bug Bounty
If a vulnerability in your venture might be exploited for good points, like it’s for Ethereum, contemplate establishing a bug bounty program. This enables safety researchers, or anybody actually, to submit vulnerability stories in alternate for cash. Typically, that is particularly for findings which may show that an exploit is feasible. If the bug bounty payouts are cheap, bug finders will notify you of the bug moderately than exploiting it or promoting it to a different social gathering. We suggest beginning your bug bounty program after the findings from the primary safety evaluate are resolved; ideally, the safety evaluate would value lower than the bug bounty payouts.
Conclusion
The event of strong C tasks, particularly within the crucial area of blockchain and cryptocurrencies, requires a multi-faceted strategy. 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 beneficial insights and finest practices for others embarking on comparable tasks.
