For EIP-4844, Ethereum shoppers want the power to compute and confirm KZG commitments. Reasonably than every consumer 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 concept was to create a sturdy and environment friendly cryptographic library that every one shoppers might use. The Protocol Safety Analysis workforce on the Ethereum Basis had the chance to overview and enhance this library. This weblog submit will focus on some issues we do to make C tasks 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 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 mission’s different choices.
Here is the fuzzer for verify_kzg_proof, certainly 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 dimension) { initialize(); if (dimension == 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, it’s best to have the ability 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 realize one thing is mistaken. This system could 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 degree of security, figuring out that if one implementation had been flawed the others might not have the identical situation.
For KZG libraries, we developed kzg-fuzz which differentially fuzzes c-kzg-4844 (by way of its Golang bindings) and go-kzg-4844. To this point, 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 (“lined”) and examined. See the coverage goal in c-kzg-4844’s Makefile for an instance of tips on 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 prime and the non-exported (static) features are on the underside.
There’s a whole lot 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, seek advice from the HTML file (protection.html) that was generated. This webpage exhibits the whole supply file and highlights non-executed code in purple. On this mission’s case, a lot of the non-executed code offers with hard-to-test error instances equivalent to reminiscence allocation failures. For instance, here is some non-executed code:
At the start 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 right 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 suggest this for all tasks, however since c-kzg-4844 is a efficiency crucial library we expect it is necessary to profile its exported features and measure how lengthy they take to execute. This might help establish inefficiencies which might doubtlessly DoS nodes. For this, we used gperftools (Google Efficiency Instruments) as an alternative 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 once in a while. If a perform is quick sufficient, it will not be observed by the profiler. To cut back the possibility 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.
#embodyint 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(“
Right here is the graph generated from the command above:
Here is a much bigger instance from certainly one 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 perform’s time is spent performing Montgomery multiplications. That is anticipated.
Reverse
Subsequent, view your binary in a software program reverse engineering (SRE) software equivalent to Ghidra or IDA. These instruments might help you perceive how high-level constructs are translated into low-level machine code. We expect it helps to overview your code this manner; 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 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.
If 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. It will likely 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 totally different. These are simply compiler optimizations and are typically nice. It might 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 a bit of work, you possibly can rename variables and add feedback to make it simpler to learn. Here is what it might 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 identify “static” suggests, it examines code with out executing it. That is slower than the compiler, however quite a bit 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 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.
#embodyint 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 concentrate on it; the analyzer reached the return assertion and observed that the reminiscence hadn’t been freed.
Not all the findings are that easy although. Here is a discovering that Clang Static Analyzer present in c-kzg-4844 when initially launched to the mission:
Given an surprising enter, it was doable 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 not possible. 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 significantly 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 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:
#embodyint principal(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 a great path (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:
#embodyint 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. Here 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 should output the next error message:
Undefined Habits
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.
#embodyint principal(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 applications 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 no locks or semaphores, so it is fully doable that these two threads will increment the variable on the similar time.
#embodyint 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 should 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 strong instrumentation framework for constructing dynamic evaluation instruments, however its greatest identified for figuring out reminiscence errors and leaks with its built-in Memcheck software.
The next picture exhibits the output from operating c-kzg-4844’s exams with Valgrind. Within the purple field is a legitimate discovering for a “conditional bounce or transfer [that] is determined by uninitialized worth(s).”
This identified an edge case in expand_root_of_unity. If the mistaken root of unity or width had been supplied, it was doable that the loop will break earlier than out[width] was initialized. On this state of affairs, the ultimate examine 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 Assessment
After growth stabilizes, it has been totally examined, and your workforce has manually reviewed the codebase themselves a number of occasions, it is time to get a safety overview by a good safety group. This would possibly not be a stamp of approval, but it surely exhibits that your mission is no less than considerably safe. Take note there isn’t any such factor as excellent 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 overview. They produced this report with 8 findings. It accommodates 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 mission might be exploited for positive factors, like it’s for Ethereum, take into account organising a bug bounty program. This enables safety researchers, or anybody actually, to submit vulnerability reviews in change for cash. Usually, 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 relatively than exploiting it or promoting it to a different occasion. We suggest beginning your bug bounty program after the findings from the primary safety overview are resolved; ideally, the safety overview would price lower than the bug bounty payouts.
Conclusion
The event of strong 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 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 worthwhile insights and greatest practices for others embarking on comparable tasks.
