For EIP-4844, Ethereum purchasers want the flexibility to compute and confirm KZG commitments. Fairly than every consumer 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 thought was to create a strong and environment friendly cryptographic library that every one purchasers might use. The Protocol Safety Analysis staff on the Ethereum Basis had the chance to evaluation and enhance this library. This weblog publish will focus on some issues we do to make C tasks 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 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 challenge’s different choices.
This is the fuzzer for verify_kzg_proof, considered one 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 to be like like. If there have been an issue, it might write the enter to disk and cease executing. Ideally, it is best to 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 already know one thing is unsuitable. This method could be very in style in Ethereum as a result of we wish to have a number of implementations of the identical factor. This diversification offers an additional stage of security, realizing that if one implementation have been flawed the others might not have the identical concern.
For KZG libraries, we developed kzg-fuzz which differentially fuzzes c-kzg-4844 (by way of 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 exams. It is a nice approach to confirm code is executed (“coated”) and examined. See the protection 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 high and the non-exported (static) capabilities are on the underside.
There may be a number of inexperienced within the desk above, however there may be some yellow and crimson 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 crimson. On this challenge’s case, many of the non-executed code offers with hard-to-test error instances equivalent to reminiscence allocation failures. For instance, here is some non-executed code:
Firstly of this operate, 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 offers 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 advocate this for all tasks, however since c-kzg-4844 is a efficiency crucial library we expect it is essential to profile its exported capabilities and measure how lengthy they take to execute. This will help determine inefficiencies which might 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 once in a while. If a operate is quick sufficient, it will not be observed by the profiler. To scale back the prospect of this, chances are you’ll have to name your operate 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:
This is a much bigger instance from considered one of c-kzg-4844’s capabilities. The next picture is the profiling graph for compute_blob_kzg_proof. As you possibly can 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) device equivalent to Ghidra or IDA. These instruments will 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 otherwise. It is also helpful to see what kind of optimizations your compiler makes. It is uncommon, however typically the compiler will optimize out one thing which it deemed pointless. Hold a watch out for this, one thing like this really occurred in c-kzg-4844, a number of the exams have been being optimized out.
If 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 may usually 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 totally different. These are simply compiler optimizations and are usually positive. It might 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 to be like like in Ghidra:
With slightly work, you possibly can rename variables and add feedback to make it simpler to learn. This is what it might appear like 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.
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 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, but it surely 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 challenge:
Given an surprising 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 applications which might 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 might 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 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=deal with and executed, it is going to output the next error message. This factors you in a great path (a 4-byte write in predominant). This binary could possibly 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. This 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 is going to output the next error message:
Undefined Conduct
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 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 is going to 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 might happen in multi-threaded applications when two or extra threads entry a shared reminiscence location on the similar time. This example introduces unpredictability and might result in undefined conduct. This is an instance through which two threads increment a world counter variable. There are not any locks or semaphores, so it is completely 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 is going to output the next error message:
This error message tells us that there is a knowledge race. In two threads, the increment operate 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 greatest identified for figuring out reminiscence errors and leaks with its built-in Memcheck device.
The next picture reveals the output from working c-kzg-4844’s exams with Valgrind. Within the crimson field is a legitimate discovering for a “conditional leap or transfer [that] will depend on uninitialized worth(s).”
This recognized an edge case in expand_root_of_unity. If the unsuitable root of unity or width have been offered, it was doable that the loop will break earlier than out[width] was initialized. On this state of affairs, 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 growth stabilizes, it has been totally examined, and your staff 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, but it surely reveals that your challenge is at the very least considerably safe. Remember there isn’t a such factor as excellent safety. There’ll at all times be the chance 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 accommodates 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 mounted, this might have resulted in a consensus bug (a disagreement between implementations) in Ethereum.
Bug Bounty
If a vulnerability in your challenge could possibly be exploited for features, like it’s for Ethereum, take into account establishing a bug bounty program. This permits safety researchers, or anybody actually, to submit vulnerability stories in trade for cash. Usually, that is particularly for findings which might show that an exploit is feasible. If the bug bounty payouts are cheap, bug finders will notify you of the bug fairly than exploiting it or promoting it to a different social gathering. We advocate beginning your bug bounty program after the findings from the primary safety evaluation are resolved; ideally, the safety evaluation 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 method. 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 beneficial insights and greatest practices for others embarking on related tasks.
