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 thought was to create a strong and environment friendly cryptographic library that each one shoppers might use. The Protocol Safety Analysis crew on the Ethereum Basis had the chance to evaluate 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 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 have been already well-integrated with LLVM venture’s different choices.
Here is the fuzzer for verify_kzg_proof, one in every of c-kzg-4844’s capabilities:
#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 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 appears like. If there have been an issue, it will write the enter to disk and cease executing. Ideally, you need to be capable 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 understand one thing is mistaken. 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 gives an additional degree of security, figuring out 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 (via 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 operating the exams. It is a nice approach to confirm code is executed (“lined”) and examined. See the protection goal in c-kzg-4844’s Makefile for an instance of the 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 capabilities are on the prime and the non-exported (static) capabilities are on the underside.
There’s a variety 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 your entire supply file and highlights non-executed code in pink. On this venture’s case, many of the non-executed code offers with hard-to-test error circumstances reminiscent of 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 test. There is not a take a look at case which gives 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 does 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 capabilities and measure how lengthy they take to execute. This may help determine inefficiencies which might 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 once in a while. If a perform is quick sufficient, it might not be seen by the profiler. To cut back the possibility of this, you might must 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 predominant(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:
Here is a much bigger instance from one in every of 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) device reminiscent of Ghidra or IDA. These instruments may 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 distinct font will power your mind to interpret sentences otherwise. It is also helpful to see what sort of optimizations your compiler makes. It is uncommon, however typically the compiler will optimize out one thing which it deemed pointless. Preserve an eye fixed out for this, one thing like this truly occurred in c-kzg-4844, a number of the exams have been being optimized out.
While you view a decompiled perform, it won’t have variable names, complicated varieties, or feedback. When compiled, this data is not included within the binary. Will probably 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 high-quality. It could assist to construct your binary with DWARF debugging data; most SREs can analyze this part to offer higher outcomes.
For instance, that is what blob_to_kzg_commitment initially appears like in Ghidra:
With a bit work, you may rename variables and add feedback to make it simpler to learn. Here is what it might appear to be after a couple of minutes:
Static Evaluation
Clang comes built-in with the Clang Static Analyzer, which is a wonderful static evaluation device 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 rather a lot sooner 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 speak 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.
#embraceint predominant(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 smart if you concentrate on it; the analyzer reached the return assertion and seen that the reminiscence hadn’t been freed.
Not all the findings are that easy although. Here is a discovering that Clang Static Analyzer present in c-kzg-4844 when initially launched to the venture:
Given an sudden enter, it was doable 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 unimaginable. 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 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 factor in a 5 factor array. It is a easy instance of a heap-buffer-overflow:
#embraceint predominant(void) { int* arr = malloc(5 * sizeof(int)); arr[5] = 42; return 0; }
When compiled with -fsanitize=tackle and executed, it should output the next error message. This factors you in a great course (a 4-byte write in predominant). This binary might be seen in a disassembler to determine precisely which instruction (at predominant+0x84) is inflicting the issue.
Equally, here is an instance the place it finds a heap-use-after-free:
#embraceint predominant(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 predominant+0x8c.
Reminiscence
MemorySanitizer (MSan) is a detector of uninitialized reads. Here is a easy instance which reads (and returns) an uninitialized worth:
int predominant(void) { int knowledge[2]; return knowledge[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 customary. 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 predominant(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 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 may result in undefined conduct. Here is an instance through which two threads increment a world counter variable. There are not any locks or semaphores, so it is solely doable that these two threads will increment the variable on the similar time.
#embraceint counter = 0; void *increment(void *arg) { (void)arg; for (int i = 0; i < 1000000; i++) counter++; return NULL; } int predominant(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 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 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 exams with Valgrind. Within the pink field is a legitimate discovering for a “conditional leap or transfer [that] is determined by uninitialized worth(s).”
This recognized an edge case in expand_root_of_unity. If the mistaken root of unity or width have been supplied, it was doable that the loop will break earlier than out[width] was initialized. On this scenario, the ultimate test would depend 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 Evaluation
After improvement stabilizes, it has been completely examined, and your crew has manually reviewed the codebase themselves a number of occasions, it is time to get a safety evaluate by a good safety group. This may not be a stamp of approval, however it reveals that your venture is at the very least considerably safe. Bear in mind 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 evaluate. They produced this report with 8 findings. It accommodates 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 organising a bug bounty program. This permits safety researchers, or anybody actually, to submit vulnerability studies in trade 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 relatively than exploiting it or promoting it to a different celebration. 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 sturdy C initiatives, particularly within the important area of blockchain and cryptocurrencies, requires a multi-faceted method. Given the inherent vulnerabilities related to the C language, a mix of finest practices and instruments is crucial 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 initiatives.
