For EIP-4844, Ethereum shoppers want the flexibility to compute and confirm KZG commitments. Reasonably than every consumer rolling their very own crypto, researchers and builders got here collectively to write 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 might use. The Protocol Safety Analysis staff on the Ethereum Basis had the chance to assessment 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 method that includes offering random inputs to find bugs in a program. LibFuzzer and afl++ are two standard 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, considered one of c-kzg-4844’s features:
#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 appears to be like like. If there have been an issue, it might write the enter to disk and cease executing. Ideally, you must have the ability 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 completely different, and also you anticipated them to be the identical, you already know one thing is incorrect. This system may be very standard in Ethereum as a result of we wish to have a number of implementations of the identical factor. This diversification supplies an additional stage of security, figuring out that if one implementation had been flawed the others might 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. To date, 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 option to confirm code is executed (“lined”) and examined. See the protection 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 perform is executed. The exported features are on the high and the non-exported (static) features are on the underside.
There may be numerous inexperienced within the desk above, however there may be some yellow and purple too. To find out what’s and is not being executed, check 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 instances similar to reminiscence allocation failures. For instance, here is some non-executed code:
Initially of this perform, 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 supplies 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 would not return the error worth.
Profile
We do not suggest this for all initiatives, however since c-kzg-4844 is a efficiency essential library we expect it is vital to profile its exported features and measure how lengthy they take to execute. This will help determine inefficiencies which might 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 on occasion. If a perform is quick sufficient, it might not be seen by the profiler. To scale back the prospect of this, you could must name your perform 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 fundamental(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’s 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 an even bigger instance from considered one of c-kzg-4844’s features. The next picture is the profiling graph for compute_blob_kzg_proof. As you’ll be able to 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 fashion; like how studying a paper in a distinct font will pressure your mind to interpret sentences in another 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, a number of the exams had been being optimized out.
If you view a decompiled perform, it won’t have variable names, advanced sorts, or feedback. When compiled, this info is not included within the binary. It is going to be as much as you to reverse engineer this. You may typically see features 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 completely different. These are simply compiler optimizations and are usually 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 to be like like in Ghidra:
With somewhat 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 software that may determine 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 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’ll discuss extra about that later). The compiler won’t determine this, even with all warnings enabled as a result of technically that is utterly legitimate code.
#embody <stdlib.h> int fundamental(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 seen that the reminiscence hadn’t been freed.
Not the entire findings are that straightforward 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 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 unimaginable. 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 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 similar instance from earlier. It forgets to free arr and it’ll set the sixth ingredient in a 5 ingredient array. This can be a easy instance of a heap-buffer-overflow:
#embody <stdlib.h> int fundamental(void) { int* arr = malloc(5 * sizeof(int)); arr[5] = 42; return 0; }
When compiled with -fsanitize=tackle and executed, it’s going to output the next error message. This factors you in path (a 4-byte write in fundamental). This binary might be considered in a disassembler to determine precisely which instruction (at fundamental+0x84) is inflicting the issue.
Equally, here is an instance the place it finds a heap-use-after-free:
#embody <stdlib.h> int 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. This is a easy instance which reads (and returns) an uninitialized worth:
int fundamental(void) { int information[2]; return information[0]; }
When compiled with -fsanitize=reminiscence and executed, it’s going to output the next error message:
Undefined Conduct
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 customary. 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.
#embody <limits.h> int fundamental(void) { int a = INT_MAX; return a + 1; }
When compiled with -fsanitize=undefined and executed, it’s 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 applications when two or extra threads entry a shared reminiscence location on the similar time. This example introduces unpredictability and may result in undefined habits. This is an instance during which two threads increment a worldwide counter variable. There are not any locks or semaphores, so it is fully 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 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’s 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 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 exams with Valgrind. Within the purple field is a sound discovering for a “conditional soar or transfer [that] is determined by uninitialized worth(s).”
This recognized an edge case in expand_root_of_unity. If the incorrect root of unity or width had been offered, it was potential that the loop will break earlier than out[width] was initialized. On this state of affairs, the ultimate examine 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 <= 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 completely examined, and your staff has manually reviewed the codebase themselves a number of instances, it is time to get a safety assessment by a good safety group. This would possibly not be a stamp of approval, nevertheless it reveals that your venture is no less than considerably safe. Take into accout there is no such thing as a such factor as good safety. There’ll at all times be the chance 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 accommodates one essential 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 venture might be exploited for positive aspects, like it’s for Ethereum, take into account organising a bug bounty program. This enables safety researchers, or anybody actually, to submit vulnerability experiences 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 quite than exploiting it or promoting it to a different occasion. We suggest 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 strong 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 crucial for producing resilient software program. We hope our experiences and findings from our work with c-kzg-4844 present invaluable insights and greatest practices for others embarking on related initiatives.
