For EIP-4844, Ethereum shoppers want the flexibility to compute and confirm KZG commitments. Quite 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 sturdy and environment friendly cryptographic library that each one shoppers may use. The Protocol Safety Analysis crew on the Ethereum Basis had the chance to evaluation and enhance this library. This weblog put up will focus on some issues we do to make C initiatives 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 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.
This is the fuzzer for verify_kzg_proof, one among 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* 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 seems like. If there have been an issue, it might 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 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 already know one thing is fallacious. This system may be very standard in Ethereum as a result of we prefer to have a number of implementations of the identical factor. This diversification gives an additional stage of security, understanding 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 (via its Golang bindings) and go-kzg-4844. To date, there have not been any variations.
Protection
Subsequent, we used llvm-profdata and llvm-cov to generate a protection report from working the assessments. It is a nice strategy to confirm code is executed (“lined”) and examined. See the protection goal in c-kzg-4844’s Makefile for an instance of the best 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 prime and the non-exported (static) features are on the underside.
There may be quite a lot of inexperienced within the desk above, however there’s some yellow and purple too. To find out what’s and is not being executed, check with the HTML file (protection.html) that was generated. This webpage reveals the whole supply file and highlights non-executed code in purple. On this challenge’s case, many of the non-executed code offers with hard-to-test error circumstances comparable to reminiscence allocation failures. For instance, here is some non-executed code:
At first of this perform, it checks that the trusted setup is sufficiently big to carry out a pairing examine. 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 advocate this for all initiatives, however since c-kzg-4844 is a efficiency vital library we predict it is vital to profile its exported features and measure how lengthy they take to execute. This might help determine inefficiencies which may probably 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 from time to time. If a perform is quick sufficient, it is probably not seen by the profiler. To cut back the possibility of this, chances are you’ll must name your perform a number of occasions. On this instance, we name my_function 1000 occasions.
#embodyint 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 among 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) instrument comparable 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 pressure 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. Preserve a watch out for this, one thing like this truly occurred in c-kzg-4844, a few of the assessments have been being optimized out.
While you view a decompiled perform, it is not going to have variable names, advanced 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 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 superb. It could 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 seems like in Ghidra:
With a bit work, you may rename variables and add feedback to make it simpler to learn. This is what it may seem 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 loads quicker 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 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 fully legitimate code.
#embodyint 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, however it is smart if you consider it; the analyzer reached the return assertion and seen that the reminiscence hadn’t been freed.
Not all the findings are that easy although. This is a discovering that Clang Static Analyzer present in c-kzg-4844 when initially launched to the challenge:
Given an sudden 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 inconceivable. 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 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 straightforward 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 aspect in a 5 aspect array. It is a easy instance of a heap-buffer-overflow:
#embodyint foremost(void) { int* arr = malloc(5 * sizeof(int)); arr[5] = 42; return 0; }
When compiled with -fsanitize=deal with and executed, it’s going to output the next error message. This factors you in a very good path (a 4-byte write in foremost). This binary might be seen in a disassembler to determine precisely which instruction (at foremost+0x84) is inflicting the issue.
Equally, here is an instance the place it finds a heap-use-after-free:
#embodyint 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 information[2]; return information[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 scenario the place a program’s habits is unpredictable and never specified by the langauge commonplace. 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.
#embodyint foremost(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 information races, which may happen in multi-threaded packages when two or extra threads entry a shared reminiscence location on the identical time. This example introduces unpredictability and may result in undefined habits. This is an instance through which two threads increment a world 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.
#embodyint 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’s going to output the next error message:
This error message tells us that there is a information 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 strong instrumentation framework for constructing dynamic evaluation instruments, however its finest recognized for figuring out reminiscence errors and leaks with its built-in Memcheck instrument.
The next picture reveals the output from working c-kzg-4844’s assessments with Valgrind. Within the purple 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 fallacious root of unity or width have been offered, it was potential that the loop will break earlier than out[width] was initialized. On this scenario, the ultimate examine 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 Assessment
After growth stabilizes, it has been totally examined, and your crew has manually reviewed the codebase themselves a number of occasions, it is time to get a safety evaluation by a good safety group. This may not be a stamp of approval, however it reveals that your challenge is at the very least considerably safe. Take note there is no such thing as 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 vital vulnerability in go-kzg-4844 that was a very 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 challenge might be exploited for positive factors, like it’s for Ethereum, contemplate establishing a bug bounty program. This enables safety researchers, or anybody actually, to submit vulnerability reviews in alternate for cash. Typically, 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 slightly than exploiting it or promoting it to a different get together. We advocate 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 strong C initiatives, particularly within the vital 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 useful insights and finest practices for others embarking on comparable initiatives.
