For EIP-4844, Ethereum purchasers want the flexibility to compute and confirm KZG commitments. Moderately than every shopper rolling their very own crypto, researchers and builders got here collectively to put in writing 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 purchasers might use. The Protocol Safety Analysis staff on the Ethereum Basis had the chance to evaluation and enhance this library. This weblog submit will focus on some issues we do to make C initiatives safer.
Fuzz
Fuzzing is a dynamic code testing approach that entails offering random inputs to find bugs in a program. LibFuzzer and afl++ are two well-liked fuzzing frameworks for C initiatives. 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, 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 might write the enter to disk and cease executing. Ideally, it is 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 system may be very well-liked in Ethereum as a result of we prefer to have a number of implementations of the identical factor. This diversification offers an additional stage of security, figuring out that if one implementation had been flawed the others might 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. Thus far, there have not been any variations.
Protection
Subsequent, we used llvm-profdata and llvm-cov to generate a protection report from operating the exams. This can be a nice strategy to confirm code is executed (“coated”) and examined. See the coverage 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 operate is executed. The exported capabilities are on the prime and the non-exported (static) capabilities are on the underside.
There’s numerous 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 the complete supply file and highlights non-executed code in pink. On this venture’s case, a lot of the non-executed code offers with hard-to-test error circumstances corresponding 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 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 initiatives, however since c-kzg-4844 is a efficiency essential library we expect it is necessary 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 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 a straightforward instance which profiles my_function. Profiling works by checking which instruction is being executed now and again. If a operate is quick sufficient, it will not be observed by the profiler. To cut back the possibility of this, you might have to name your operate a number of instances. On this instance, we name my_function 1000 instances.
#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 major(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 possibly can then use pprof to visualise this information.
Right here is the graph generated from the command above:
This 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’ll be able to 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 corresponding to 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 evaluation your code this manner; like how studying a paper in a special font will power your mind to interpret sentences in a different way. 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. Maintain a watch 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, complicated varieties, 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 will 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 effective. 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 seems to be like in Ghidra:
With just a little work, you’ll be able to rename variables and add feedback to make it simpler to learn. This 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 superb 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 quite a bit 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 speak 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.
#embody <stdlib.h> int major(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 consider 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 surprising enter, it was doable 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 unimaginable. 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 significantly 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.
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 similar instance from earlier. It forgets to free arr and it’ll set the sixth factor in a 5 factor array. This can be a easy instance of a heap-buffer-overflow:
#embody <stdlib.h> int major(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 very good route (a 4-byte write in major). This binary may very well be seen in a disassembler to determine precisely which instruction (at major+0x84) is inflicting the issue.
Equally, here is an instance the place it finds a heap-use-after-free:
#embody <stdlib.h> int major(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 major+0x8c.
Reminiscence
MemorySanitizer (MSan) is a detector of uninitialized reads. This is a easy instance which reads (and returns) an uninitialized worth:
int major(void) { int information[2]; return information[0]; }
When compiled with -fsanitize=reminiscence and executed, it should output the next error message:
Undefined Habits
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 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 habits.
#embody <limits.h> int major(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 circumstances 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 case introduces unpredictability and might result in undefined habits. This is an instance by which two threads increment a world counter variable. There are no locks or semaphores, so it is totally doable 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 major(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 identified 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 sound discovering for a “conditional leap or transfer [that] relies on 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 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 Overview
After improvement stabilizes, it has been totally examined, and your staff has manually reviewed the codebase themselves a number of instances, it is time to get a safety evaluation by a good safety group. This may not be a stamp of approval, nevertheless it reveals that your venture is a minimum of considerably safe. Remember 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 evaluation. They produced this report with 8 findings. It comprises one essential 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 may very well be exploited for features, like it’s for Ethereum, think about organising a bug bounty program. This permits safety researchers, or anybody actually, to submit vulnerability studies in change 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 celebration. 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 sturdy C initiatives, particularly within the essential area of blockchain and cryptocurrencies, requires a multi-faceted strategy. Given the inherent vulnerabilities related to the C language, a mixture 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 priceless insights and greatest practices for others embarking on related initiatives.
