For EIP-4844, Ethereum shoppers want the power to compute and confirm KZG commitments. Somewhat than every shopper 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 group on the Ethereum Basis had the chance to assessment 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 approach that entails offering random inputs to find bugs in a program. LibFuzzer and afl++ are two well-liked 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, one in all 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 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 appears like. If there have been an issue, it might write the enter to disk and cease executing. Ideally, it’s best 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 understand one thing is fallacious. This system could 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, realizing that if one implementation have been flawed the others might not have the identical situation.
For KZG libraries, we developed kzg-fuzz which differentially fuzzes c-kzg-4844 (by means 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 checks. This can be a nice solution to confirm code is executed (“lined”) and examined. See the protection goal in c-kzg-4844’s Makefile for an instance of the right 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 capabilities are on the prime and the non-exported (static) capabilities are on the underside.
There may be a variety 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, discuss with the HTML file (protection.html) that was generated. This webpage exhibits the whole supply file and highlights non-executed code in crimson. On this challenge’s case, a lot of the non-executed code offers with hard-to-test error instances similar to reminiscence allocation failures. For instance, here is some non-executed code:
In the beginning of this perform, 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 all the time the identical and does not return the error worth.
Profile
We do not suggest this for all tasks, however since c-kzg-4844 is a efficiency crucial library we expect it is vital to profile its exported capabilities and measure how lengthy they take to execute. This will help establish 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 on occasion. If a perform is quick sufficient, it is probably not observed by the profiler. To scale back the prospect of this, it’s possible you’ll have to name your perform 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 principal(void) { ProfilerStart("instance.prof"); for (int i = 0; i < 1000; i++) { my_function(); } ProfilerStop(); return 0; }
Use ProfilerStart(“<filename>”) and ProfilerStop() to mark which components of your program to profile. When re-compiled and executed, it is going to 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 a much 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 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) software similar 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 assessment your code this manner; like how studying a paper in a unique font will drive your mind to interpret sentences in another 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. Maintain an eye fixed out for this, one thing like this truly occurred in c-kzg-4844, a number of the checks have been being optimized out.
Once you view a decompiled perform, it won’t have variable names, advanced varieties, or feedback. When compiled, this info is not included within the binary. Will probably be as much as you to reverse engineer this. You will typically see capabilities 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 positive. It could assist to construct your binary with DWARF debugging info; most SREs can analyze this part to offer higher outcomes.
For instance, that is what blob_to_kzg_commitment initially appears like in Ghidra:
With just a little work, you may 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 wonderful static evaluation software 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 so much quicker than “dynamic” evaluation instruments which execute code.
This is a easy instance which forgets to free arr (and has one other downside however we are going to speak extra about that later). The compiler won’t establish this, even with all warnings enabled as a result of technically that is utterly legitimate code.
#embrace <stdlib.h> int principal(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, but it surely is smart 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 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 attainable 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 not possible. 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.
Deal with
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 component in a 5 component array. This can be a easy instance of a heap-buffer-overflow:
#embrace <stdlib.h> int principal(void) { int* arr = malloc(5 * sizeof(int)); arr[5] = 42; return 0; }
When compiled with -fsanitize=handle and executed, it is going to output the next error message. This factors you in a superb route (a 4-byte write in principal). This binary might be considered in a disassembler to determine precisely which instruction (at principal+0x84) is inflicting the issue.
Equally, here is an instance the place it finds a heap-use-after-free:
#embrace <stdlib.h> int principal(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 principal+0x8c.
Reminiscence
MemorySanitizer (MSan) is a detector of uninitialized reads. This is a easy instance which reads (and returns) an uninitialized worth:
int principal(void) { int information[2]; return information[0]; }
When compiled with -fsanitize=reminiscence and executed, it is going to 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 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.
#embrace <limits.h> int principal(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 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 identical time. This case introduces unpredictability and may result in undefined habits. This is an instance wherein two threads increment a worldwide counter variable. There are not any locks or semaphores, so it is completely attainable 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 principal(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 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 software.
The next picture exhibits the output from working c-kzg-4844’s checks with Valgrind. Within the crimson field is a sound discovering for a “conditional bounce or transfer [that] relies on uninitialized worth(s).”
This recognized an edge case in expand_root_of_unity. If the fallacious root of unity or width have been supplied, it was attainable that the loop will break earlier than out[width] was initialized. On this scenario, the ultimate test 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 Evaluate
After improvement stabilizes, it has been completely examined, and your group has manually reviewed the codebase themselves a number of occasions, it is time to get a safety assessment by a good safety group. This would possibly not be a stamp of approval, but it surely exhibits that your challenge is at the very least considerably safe. Be mindful there is no such thing as a such factor as excellent safety. There’ll all the time 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 challenge might 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. Usually, that is particularly for findings which might show that an exploit is feasible. If the bug bounty payouts are affordable, bug finders will notify you of the bug quite than exploiting it or promoting it to a different celebration. We suggest beginning your bug bounty program after the findings from the primary safety assessment are resolved; ideally, the safety assessment would price 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 beneficial insights and finest practices for others embarking on comparable tasks.
