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 thought was to create a strong and environment friendly cryptographic library that every one shoppers may use. The Protocol Safety Analysis group on the Ethereum Basis had the chance to evaluate 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 common 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 undertaking’s different choices.
Here is the fuzzer for verify_kzg_proof, one in all c-kzg-4844’s capabilities:
#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 measurement) { initialize(); if (measurement == 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 will write the enter to disk and cease executing. Ideally, you must 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 recognize one thing is incorrect. This method could be very common in Ethereum as a result of we prefer to have a number of implementations of the identical factor. This diversification offers an additional degree of security, figuring out that if one implementation had been flawed the others might not have the identical challenge.
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. This can be a nice approach to confirm code is executed (“lined”) and examined. See the coverage goal in c-kzg-4844’s Makefile for an instance of learn 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 loads 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, discuss with the HTML file (protection.html) that was generated. This webpage reveals your complete supply file and highlights non-executed code in pink. On this undertaking’s case, a lot of the non-executed code offers with hard-to-test error instances corresponding to reminiscence allocation failures. For instance, here is some non-executed code:
Firstly of this operate, it checks that the trusted setup is large enough to carry out a pairing examine. 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 vital library we predict it is essential to profile its exported capabilities 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 a substitute of llvm-xray as a result of we discovered it to be extra feature-rich and simpler to make use of.
The next is an easy instance which profiles my_function. Profiling works by checking which instruction is being executed occasionally. If a operate is quick sufficient, it might not be seen by the profiler. To scale back the prospect of this, you could must name your operate a number of occasions. On this instance, we name my_function 1000 occasions.
#embody <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 should 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:
Here is an even bigger instance from one in all 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) instrument corresponding to Ghidra or IDA. These instruments might help you perceive how high-level constructs are translated into low-level machine code. We predict it helps to evaluate 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 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, some of the tests were being optimized out.
Whenever you view a decompiled operate, it is not going to have variable names, advanced 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 typically 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 superb. 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 seems to be like in Ghidra:
With a bit work, you possibly can rename variables and add feedback to make it simpler to learn. Here 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.
Here 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.
#embody <stdlib.h> int primary(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 sensible if you concentrate on it; the analyzer reached the return assertion and seen that the reminiscence hadn’t been freed.
Not the entire findings are that straightforward although. Here is a discovering that Clang Static Analyzer present in c-kzg-4844 when initially launched to the undertaking:
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 inconceivable. Good job, Clang Static Analyzer!
Sanitize
Santizers are dynamic evaluation instruments which instrument (add directions) to packages which might level out points throughout execution. These are notably helpful at discovering frequent 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 simple to make use of.
Handle
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 aspect in a 5 aspect array. This can be a easy instance of a heap-buffer-overflow:
#embody <stdlib.h> int primary(void) { int* arr = malloc(5 * sizeof(int)); arr[5] = 42; return 0; }
When compiled with -fsanitize=handle and executed, it should output the next error message. This factors you in path (a 4-byte write in primary). This binary may very well 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:
#embody <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. Here 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 should 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 normal. 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 conduct.
#embody <limits.h> int primary(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 information races, which might 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 wherein two threads increment a world counter variable. There are not any locks or semaphores, so it is totally potential that these two threads will increment the variable on the similar time.
#embody <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 should 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 similar 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 instrument.
The next picture reveals the output from operating c-kzg-4844’s checks with Valgrind. Within the pink field is a legitimate discovering for a “conditional soar or transfer [that] is determined by uninitialized worth(s).”
This identified an edge case in expand_root_of_unity. If the incorrect root of unity or width had been supplied, it was potential that the loop will break earlier than out[width] was initialized. On this state of affairs, 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 Evaluation
After improvement stabilizes, it has been totally examined, and your group has manually reviewed the codebase themselves a number of occasions, it is time to get a safety evaluate by a good safety group. This would possibly not be a stamp of approval, nevertheless it reveals that your undertaking is a minimum of considerably safe. Remember 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 evaluate. They produced this report with 8 findings. It incorporates one vital 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 undertaking may very well be exploited for positive aspects, like it’s for Ethereum, contemplate organising a bug bounty program. This permits safety researchers, or anybody actually, to submit vulnerability stories in alternate 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 reasonably 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 evaluate are resolved; ideally, the safety evaluate would value lower than the bug bounty payouts.
Conclusion
The event of sturdy C tasks, particularly within the vital 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 useful insights and greatest practices for others embarking on comparable tasks.
