For EIP-4844, Ethereum shoppers want the flexibility to compute and confirm KZG commitments. Fairly 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 each one shoppers may use. The Protocol Safety Analysis group on the Ethereum Basis had the chance to evaluate and enhance this library. This weblog publish 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 fashionable 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 undertaking’s different choices.
Here is the fuzzer for verify_kzg_proof, considered one 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* 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 like. If there have been an issue, it might write the enter to disk and cease executing. Ideally, you need 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 completely different, and also you anticipated them to be the identical, you recognize one thing is fallacious. This system could be very fashionable in Ethereum as a result of we prefer to have a number of implementations of the identical factor. This diversification supplies an additional degree of security, figuring out that if one implementation have been flawed the others might not have the identical challenge.
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 working the exams. It is 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 how you 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 may be lots 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, seek advice from the HTML file (protection.html) that was generated. This webpage exhibits the complete supply file and highlights non-executed code in crimson. On this undertaking’s case, a lot of the non-executed code offers with hard-to-test error circumstances akin 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 sufficiently big 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 all the time 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 essential to profile its exported features and measure how lengthy they take to execute. This may also help determine inefficiencies which may probably 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 a straightforward instance which profiles my_function. Profiling works by checking which instruction is being executed from time to time. If a operate is quick sufficient, it might not be seen by the profiler. To cut back the possibility of this, chances are you’ll must name your operate a number of instances. On this instance, we name my_function 1000 instances.
#embraceint 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(“
Right here is the graph generated from the command above:
Here 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 may 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) instrument akin to Ghidra or IDA. These instruments may also help you perceive how high-level constructs are translated into low-level machine code. We predict it helps to evaluate 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 sort of optimizations your compiler makes. It is uncommon, however typically the compiler will optimize out one thing which it deemed pointless. Hold an eye fixed 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 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 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 fantastic. It could assist to construct your binary with DWARF debugging info; most SREs can analyze this part to supply higher outcomes.
For instance, that is what blob_to_kzg_commitment initially appears like in Ghidra:
With a little bit work, you may rename variables and add feedback to make it simpler to learn. Here is what it may 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 instrument 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 so much 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 are going to speak extra about that later). The compiler won’t determine this, even with all warnings enabled as a result of technically that is fully legitimate code.
#embraceint 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 smart if you concentrate on it; the analyzer reached the return assertion and seen 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 undertaking:
Given an sudden enter, it was potential 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 inconceivable. Good job, Clang Static Analyzer!
Sanitize
Santizers are dynamic evaluation instruments which instrument (add directions) to applications which may 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.
Tackle
AddressSanitizer (ASan) is a quick reminiscence error detector which may 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 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=deal with and executed, it would output the next error message. This factors you in an excellent path (a 4-byte write in fundamental). This binary might be seen 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 information[2]; return information[0]; }
When compiled with -fsanitize=reminiscence and executed, it would output the next error message:
Undefined Habits
UndefinedBehaviorSanitizer (UBSan) detects undefined conduct, which refers back to the scenario the place a program’s conduct 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 conduct.
#embraceint fundamental(void) { int a = INT_MAX; return a + 1; }
When compiled with -fsanitize=undefined and executed, it would 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 may happen in multi-threaded applications when two or extra threads entry a shared reminiscence location on the similar time. This case introduces unpredictability and might result in undefined conduct. Here is an instance through which two threads increment a worldwide counter variable. There are not any locks or semaphores, so it is totally 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 < 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 would 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 strong instrumentation framework for constructing dynamic evaluation instruments, however its greatest identified for figuring out reminiscence errors and leaks with its built-in Memcheck instrument.
The next picture exhibits the output from working c-kzg-4844’s exams with Valgrind. Within the crimson field is a sound discovering for a “conditional bounce or transfer [that] depends upon 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 scenario, the ultimate examine 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 Evaluation
After improvement stabilizes, it has been totally examined, and your group has manually reviewed the codebase themselves a number of instances, it is time to get a safety evaluate by a good safety group. This would possibly not be a stamp of approval, nevertheless it exhibits that your undertaking is at the very least considerably safe. Consider there is no such thing as a such factor as good safety. There’ll all the time be the chance 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 mounted, this might have resulted in a consensus bug (a disagreement between implementations) in Ethereum.
Bug Bounty
If a vulnerability in your undertaking might be exploited for good points, like it’s for Ethereum, contemplate 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 may show that an exploit is feasible. If the bug bounty payouts are affordable, bug finders will notify you of the bug slightly than exploiting it or promoting it to a different occasion. We suggest 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 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 comparable initiatives.