For EIP-4844, Ethereum purchasers 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 jot down c-kzg-4844, a comparatively small C library with bindings for higher-level languages. The thought was to create a sturdy and environment friendly cryptographic library that each one purchasers may use. The Protocol Safety Analysis group on the Ethereum Basis had the chance to assessment and enhance this library. This weblog submit will focus on some issues we do to make C initiatives safer.
Fuzz
Fuzzing is a dynamic code testing method that includes offering random inputs to find bugs in a program. LibFuzzer and afl++ are two in style fuzzing frameworks for C initiatives. They’re each in-process, coverage-guided, evolutionary fuzzing engines. For c-kzg-4844, we used LibFuzzer since we had been already well-integrated with LLVM venture’s different choices.
This is the fuzzer for verify_kzg_proof, one in every of c-kzg-4844’s features:
#embrace "../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 measurement) { initialize(); if (measurement == 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 appears to be like like. If there have been an issue, it might 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 method 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 system may be very in style 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, understanding that if one implementation had 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. 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 checks. It is a nice strategy to confirm code is executed (“coated”) and examined. See the protection goal in c-kzg-4844’s Makefile for an instance of the right way 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 perform is executed. The exported features are on the high and the non-exported (static) features are on the underside.
There may be lots of 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 all the 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:
Initially 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 right trusted setup, the results of is_monomial_form is at all times the identical and would not return the error worth.
Profile
We do not suggest this for all initiatives, however since c-kzg-4844 is a efficiency important library we expect it is essential to profile its exported features and measure how lengthy they take to execute. This may help determine inefficiencies which may doubtlessly DoS nodes. For this, we used gperftools (Google Efficiency Instruments) as an alternative 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 on occasion. If a perform is quick sufficient, it will not be observed by the profiler. To cut back the possibility of this, you could have to name your perform a number of occasions. On this instance, we name my_function 1000 occasions.
#embraceint 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 foremost(void) { ProfilerStart("instance.prof"); for (int i = 0; i < 1000; i++) { my_function(); } ProfilerStop(); return 0; }
Use ProfilerStart(“
Right here is the graph generated from the command above:
This is a much bigger instance from one in every 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) device resembling Ghidra or IDA. These instruments may help you perceive how high-level constructs are translated into low-level machine code. We expect it helps to assessment your code this manner; like how studying a paper in a special font will pressure your mind to interpret sentences in another 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, a few of the checks had been being optimized out.
If you view a decompiled perform, it is not going to have variable names, advanced sorts, or feedback. When compiled, this info is not included within the binary. It is going to be as much as you to reverse engineer this. You will typically 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 typically effective. 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 appears to be like 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 to be after a couple of minutes:
Static Evaluation
Clang comes built-in with the Clang Static Analyzer, which is a superb static evaluation device that may determine many issues that the compiler will miss. Because the identify “static” suggests, it examines code with out executing it. That is slower than the compiler, however loads sooner than “dynamic” evaluation instruments which execute code.
This is a easy instance which forgets to free arr (and has one other downside 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.
#embraceint foremost(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, nevertheless it is smart if you concentrate on it; the analyzer reached the return assertion and observed that the reminiscence hadn’t been freed.
Not all the findings are that straightforward although. This is a discovering that Clang Static Analyzer present in c-kzg-4844 when initially launched to the venture:
Given an surprising 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 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 significantly 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.
Handle
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 similar instance from earlier. It forgets to free arr and it’ll set the sixth aspect in a 5 aspect array. It is a easy instance of a heap-buffer-overflow:
#embraceint foremost(void) { int* arr = malloc(5 * sizeof(int)); arr[5] = 42; return 0; }
When compiled with -fsanitize=deal with and executed, it can output the next error message. This factors you in a very good course (a 4-byte write in foremost). This binary might be considered in a disassembler to determine precisely which instruction (at foremost+0x84) is inflicting the issue.
Equally, this is an instance the place it finds a heap-use-after-free:
#embraceint foremost(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 foremost+0x8c.
Reminiscence
MemorySanitizer (MSan) is a detector of uninitialized reads. This is a easy instance which reads (and returns) an uninitialized worth:
int foremost(void) { int knowledge[2]; return knowledge[0]; }
When compiled with -fsanitize=reminiscence and executed, it can output the next error message:
Undefined Habits
UndefinedBehaviorSanitizer (UBSan) detects undefined conduct, which refers back to the state of affairs 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.
#embraceint foremost(void) { int a = INT_MAX; return a + 1; }
When compiled with -fsanitize=undefined and executed, it can output the next error message which tells us precisely the place the issue is and what the circumstances 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 identical time. This case introduces unpredictability and may 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 totally potential that these two threads will increment the variable on the identical time.
#embraceint counter = 0; void *increment(void *arg) { (void)arg; for (int i = 0; i < 1000000; i++) counter++; return NULL; } int foremost(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 can 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 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 greatest recognized for figuring out reminiscence errors and leaks with its built-in Memcheck device.
The next picture reveals the output from operating c-kzg-4844’s checks with Valgrind. Within the purple field is a sound discovering for a “conditional bounce or transfer [that] is dependent upon uninitialized worth(s).”
This recognized an edge case in expand_root_of_unity. If the improper root of unity or width had been offered, it was potential that the loop will break earlier than out[width] was initialized. On this state of affairs, the ultimate test would rely on 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 Overview
After improvement stabilizes, it has been completely examined, and your group has manually reviewed the codebase themselves a number of occasions, it is time to get a safety assessment by a good safety group. This would possibly not be a stamp of approval, nevertheless it reveals that your venture is no less than considerably safe. Take into account there isn’t any such factor as excellent 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 assessment. They produced this report with 8 findings. It comprises one important 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 beneficial properties, like it’s for Ethereum, think about establishing a bug bounty program. This enables safety researchers, or anybody actually, to submit vulnerability studies in change for cash. Usually, 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 slightly than exploiting it or promoting it to a different get together. We suggest beginning your bug bounty program after the findings from the primary safety assessment are resolved; ideally, the safety assessment would price lower than the bug bounty payouts.
Conclusion
The event of strong C initiatives, particularly within the important area of blockchain and cryptocurrencies, requires a multi-faceted strategy. Given the inherent vulnerabilities related to the C language, a mix of greatest practices and instruments is important for producing resilient software program. We hope our experiences and findings from our work with c-kzg-4844 present helpful insights and greatest practices for others embarking on related initiatives.