For EIP-4844, Ethereum shoppers want the power to compute and confirm KZG commitments. Somewhat 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 every one shoppers might use. The Protocol Safety Analysis crew on the Ethereum Basis had the chance to assessment and enhance this library. This weblog put up will focus on 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 had been already well-integrated with LLVM venture’s different choices.
This is the fuzzer for verify_kzg_proof, certainly 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* 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 to be like. If there have been an issue, it could 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 totally different, and also you anticipated them to be the identical, you realize one thing is improper. This method may be very fashionable in Ethereum as a result of we wish to have a number of implementations of the identical factor. This diversification offers an additional degree of security, understanding that if one implementation had been flawed the others could not have the identical difficulty.
For KZG libraries, we developed kzg-fuzz which differentially fuzzes c-kzg-4844 (by means of its Golang bindings) and go-kzg-4844. Up to now, 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 solution to confirm code is executed (“coated”) and examined. See the coverage goal in c-kzg-4844’s Makefile for an instance of methods 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 a whole 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, consult 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, many of the non-executed code offers with hard-to-test error instances resembling reminiscence allocation failures. For instance, here is some non-executed code:
Initially of this operate, it checks that the trusted setup is sufficiently big to carry out a pairing test. There is not a check case which offers an invalid trusted setup, so this does not get executed. Additionally, as a result of we solely check with the proper 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 tasks, however since c-kzg-4844 is a efficiency crucial library we predict it is essential to profile its exported capabilities and measure how lengthy they take to execute. This will help establish 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 on occasion. If a operate is quick sufficient, it might not be observed by the profiler. To scale back the prospect of this, it’s possible you’ll have to name your operate a number of occasions. On this instance, we name my_function 1000 occasions.
#embrace <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 primary(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’ll write a file to disk with profiling information. You may then use pprof to visualise this information.
Right here is the graph generated from the command above:
This is an even bigger instance from certainly one 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 operate’s time is spent performing Montgomery multiplications. That is anticipated.
Reverse
Subsequent, view your binary in a software program reverse engineering (SRE) instrument resembling Ghidra or IDA. These instruments will help you perceive how high-level constructs are translated into low-level machine code. We predict it helps to assessment your code this fashion; like how studying a paper in a unique 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. Hold a watch out for this, one thing like this truly occurred in c-kzg-4844, some of the tests were 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 is going to 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 typically 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 seems to be like in Ghidra:
With slightly work, you may 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 superb static evaluation instrument that may establish 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 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 are going to discuss extra about that later). The compiler is not going to establish this, even with all warnings enabled as a result of technically that is utterly legitimate code.
#embrace <stdlib.h> int primary(void) { int* arr = malloc(5 * sizeof(int)); arr[5] = 42; return 0; }
The unix.Malloc checker will establish 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 observed 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 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 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 here are the 4 we discover most helpful and straightforward to make use of.
Handle
AddressSanitizer (ASan) is a quick reminiscence error detector which might establish 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:
#embrace <stdlib.h> int primary(void) { int* arr = malloc(5 * sizeof(int)); arr[5] = 42; return 0; }
When compiled with -fsanitize=tackle and executed, it’ll output the next error message. This factors you in a great path (a 4-byte write in primary). This binary might be considered in a disassembler to determine precisely which instruction (at primary+0x84) is inflicting the issue.
Equally, here is an instance the place it finds a heap-use-after-free:
#embrace <stdlib.h> int primary(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 primary+0x8c.
Reminiscence
MemorySanitizer (MSan) is a detector of uninitialized reads. This is a easy instance which reads (and returns) an uninitialized worth:
int primary(void) { int information[2]; return information[0]; }
When compiled with -fsanitize=reminiscence and executed, it’ll 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.
#embrace <limits.h> int primary(void) { int a = INT_MAX; return a + 1; }
When compiled with -fsanitize=undefined and executed, it’ll 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 might 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 during 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.
#embrace <pthread.h> int counter = 0; void *increment(void *arg) { (void)arg; for (int i = 0; i < 1000000; i++) counter++; return NULL; } int primary(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’ll 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 recognized for figuring out reminiscence errors and leaks with its built-in Memcheck instrument.
The next picture reveals the output from operating c-kzg-4844’s checks with Valgrind. Within the purple field is a legitimate discovering for a “conditional leap or transfer [that] depends upon uninitialized worth(s).”
This identified 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 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 Assessment
After growth 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 assessment by a good safety group. This may not be a stamp of approval, however it reveals that your venture is not less than considerably safe. Consider there isn’t 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 assessment. They produced this report with 8 findings. It comprises one crucial 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 venture might be exploited for positive aspects, like it’s for Ethereum, take into account organising a bug bounty program. This permits safety researchers, or anybody actually, to submit vulnerability experiences in trade for cash. Typically, 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 slightly than exploiting it or promoting it to a different occasion. We advocate beginning your bug bounty program after the findings from the primary safety assessment are resolved; ideally, the safety assessment would value lower than the bug bounty payouts.
Conclusion
The event of sturdy 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 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 comparable tasks.