For EIP-4844, Ethereum shoppers want the power to compute and confirm KZG commitments. Reasonably 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 sturdy and environment friendly cryptographic library that every one shoppers may use. The Protocol Safety Analysis staff on the Ethereum Basis had the chance to evaluate and enhance this library. This weblog submit will talk about 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 have been already well-integrated with LLVM venture’s different choices.
Here is the fuzzer for verify_kzg_proof, one in every of c-kzg-4844’s features:
#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 measurement) { initialize(); if (measurement == 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 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 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 completely different, and also you anticipated them to be the identical, you already know one thing is fallacious. This system may be very well-liked in Ethereum as a result of we wish to have a number of implementations of the identical factor. This diversification supplies an additional degree of security, realizing that if one implementation have been flawed the others could not have the identical subject.
For KZG libraries, we developed kzg-fuzz which differentially fuzzes c-kzg-4844 (by way of 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 checks. It is a nice method to confirm code is executed (“lined”) and examined. See the coverage goal in c-kzg-4844’s Makefile for an instance of how one can 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 features are on the high and the non-exported (static) features are on the underside.
There’s plenty of inexperienced within the desk above, however there may be 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 your entire supply file and highlights non-executed code in purple. On this venture’s case, a lot of the non-executed code offers with hard-to-test error circumstances similar to reminiscence allocation failures. For instance, this is some non-executed code:
At the start of this operate, it checks that the trusted setup is large enough to carry out a pairing test. There is not a check case which supplies 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 all the time the identical and would 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 predict it is necessary to profile its exported features and measure how lengthy they take to execute. This will help establish inefficiencies which may 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 operate is quick sufficient, it will not be observed by the profiler. To scale back the prospect of this, you might must name your operate a number of instances. On this instance, we name my_function 1000 instances.
#embraceint task_a(int n) { if (n return task_a(n - 1) * n; } int task_b(int n) { if (n return task_b(n - 2) + n; } void my_function(void) { for (int i = 0; i if (i % 2 == 0) { task_a(i); } else { task_b(i); } } } int fundamental(void) { ProfilerStart("instance.prof"); for (int i = 0; i my_function(); } ProfilerStop(); return 0; }
Use ProfilerStart(“
Right here is the graph generated from the command above:
Here is a much bigger instance from one in every of c-kzg-4844’s features. 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) 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 evaluate your code this fashion; like how studying a paper in a unique font will drive 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 really occurred in c-kzg-4844, some of the tests were being optimized out.
Whenever you view a decompiled operate, it won’t have variable names, complicated sorts, or feedback. When compiled, this data is not included within the binary. Will probably be as much as you to reverse engineer this. You may usually see features 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 completely 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 supply higher outcomes.
For instance, that is what blob_to_kzg_commitment initially seems to be like in Ghidra:
With just a little work, you possibly can rename variables and add feedback to make it simpler to learn. Here is what it may appear like after a couple of minutes:
Static Evaluation
Clang comes built-in with the Clang Static Analyzer, which is a superb static evaluation software that may establish 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.
Here is a easy instance which forgets to free arr (and has one other downside however we’ll discuss 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.
#embraceint fundamental(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 sensible if you consider it; the analyzer reached the return assertion and observed that the reminiscence hadn’t been freed.
Not the entire findings are that easy although. Here 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 habits. 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 applications 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 below 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 identical 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:
#embraceint fundamental(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 superb route (a 4-byte write in fundamental). This binary may very well be considered in a disassembler to determine precisely which instruction (at fundamental+0x84) is inflicting the issue.
Equally, this is an instance the place it finds a heap-use-after-free:
#embraceint fundamental(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 fundamental+0x8c.
Reminiscence
MemorySanitizer (MSan) is a detector of uninitialized reads. Here is a easy instance which reads (and returns) an uninitialized worth:
int fundamental(void) { int knowledge[2]; return knowledge[0]; }
When compiled with -fsanitize=reminiscence and executed, it’ll output the next error message:
Undefined Habits
UndefinedBehaviorSanitizer (UBSan) detects undefined habits, which refers back to the state of affairs 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.
#embraceint fundamental(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 situations 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 case introduces unpredictability and may result in undefined habits. Here is an instance through which two threads increment a world counter variable. There are no locks or semaphores, so it is solely potential 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 counter++; return NULL; } int fundamental(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 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 robust instrumentation framework for constructing dynamic evaluation instruments, however its greatest recognized for figuring out reminiscence errors and leaks with its built-in Memcheck software.
The next picture reveals the output from operating c-kzg-4844’s checks with Valgrind. Within the purple field is a sound discovering for a “conditional soar or transfer [that] will depend on uninitialized worth(s).”
This identified an edge case in expand_root_of_unity. If the fallacious root of unity or width have been supplied, it was potential that the loop will break earlier than out[width] was initialized. On this state of affairs, the ultimate test would rely 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 blst_fr_mul(&out[i], &out[i - 1], root); } CHECK(fr_is_one(&out[width])); return C_KZG_OK; }
Safety Overview
After growth stabilizes, it has been completely examined, and your staff has manually reviewed the codebase themselves a number of instances, it is time to get a safety evaluate by a good safety group. This may not be a stamp of approval, but it surely reveals that your venture is a minimum of considerably safe. Consider there isn’t a such factor as good 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 evaluate. They produced this report with 8 findings. It accommodates 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 establishing a bug bounty program. This enables 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 affordable, bug finders will notify you of the bug reasonably than exploiting it or promoting it to a different occasion. 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 strong C initiatives, particularly within the essential 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 crucial for producing resilient software program. We hope our experiences and findings from our work with c-kzg-4844 present worthwhile insights and greatest practices for others embarking on related initiatives.
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