For EIP-4844, Ethereum purchasers want the flexibility to compute and confirm KZG commitments. Reasonably than every shopper 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 strong and environment friendly cryptographic library that every one purchasers may use. The Protocol Safety Analysis staff 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 initiatives safer.
Fuzz
Fuzzing is a dynamic code testing method that entails offering random inputs to find bugs in a program. LibFuzzer and afl++ are two in style 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 mission’s different choices.
This is the fuzzer for verify_kzg_proof, one among 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 seems like. If there have been an issue, it might write the enter to disk and cease executing. Ideally, it is 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 completely different, and also you anticipated them to be the identical, one thing is mistaken. This system could be very in style 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 had been flawed the others could 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. Up to now, there have not been any variations.
Protection
Subsequent, we used llvm-profdata and llvm-cov to generate a protection report from working the assessments. This can be a nice approach to confirm code is executed (“lined”) and examined. See the protection goal in c-kzg-4844’s Makefile for an instance of the best 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 features are on the prime and the non-exported (static) features are on the underside.
There’s loads 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, confer with the HTML file (protection.html) that was generated. This webpage exhibits your complete supply file and highlights non-executed code in crimson. On this mission’s case, many of the non-executed code offers with hard-to-test error circumstances equivalent 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 verify. 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 does 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 vital 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 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 is probably not observed by the profiler. To scale back the possibility of this, it’s possible you’ll have to 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 major(void) { ProfilerStart("instance.prof"); for (int i = 0; i < 1000; i++) { my_function(); } ProfilerStop(); return 0; }
Use ProfilerStart(“<filename>”) and ProfilerStop() to mark which elements of your program to profile. When re-compiled and executed, it’s going to write a file to disk with profiling information. You’ll be able to then use pprof to visualise this information.
Right here is the graph generated from the command above:
This is an even bigger instance from one among 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) instrument equivalent to Ghidra or IDA. These instruments will help you perceive how high-level constructs are translated into low-level machine code. We predict it helps to assessment your code this fashion; like how studying a paper in a special font will power your mind to interpret sentences otherwise. It is also helpful to see what kind of optimizations your compiler makes. It is uncommon, however generally 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, among the assessments had been being optimized out.
Whenever you view a decompiled perform, it won’t have variable names, complicated varieties, or feedback. When compiled, this data is not included within the binary. It is going to be as much as you to reverse engineer this. You may usually 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 advantageous. It could assist to construct your binary with DWARF debugging data; most SREs can analyze this part to offer higher outcomes.
For instance, that is what blob_to_kzg_commitment initially seems like in Ghidra:
With slightly work, you possibly can rename variables and add feedback to make it simpler to learn. This 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 wonderful static evaluation instrument 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 loads 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 discuss extra about that later). The compiler won’t establish this, even with all warnings enabled as a result of technically that is fully legitimate code.
#embody <stdlib.h> int major(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, however it is smart if you concentrate on it; the analyzer reached the return assertion and observed 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 mission:
Given an surprising enter, it was attainable 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 unimaginable. 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 significantly helpful at discovering widespread 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 straightforward to make use of.
Deal with
AddressSanitizer (ASan) is a quick reminiscence error detector which may 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:
#embody <stdlib.h> int major(void) { int* arr = malloc(5 * sizeof(int)); arr[5] = 42; return 0; }
When compiled with -fsanitize=handle and executed, it’s going to output the next error message. This factors you in a very good course (a 4-byte write in major). This binary could possibly be considered in a disassembler to determine precisely which instruction (at major+0x84) is inflicting the issue.
Equally, here is an instance the place it finds a heap-use-after-free:
#embody <stdlib.h> int major(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 major+0x8c.
Reminiscence
MemorySanitizer (MSan) is a detector of uninitialized reads. This is a easy instance which reads (and returns) an uninitialized worth:
int major(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 conduct, which refers back to the state of affairs the place a program’s conduct is unpredictable and never specified by the langauge customary. Some widespread 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.
#embody <limits.h> int major(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 may 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. This is an instance during which two threads increment a worldwide counter variable. There are not any locks or semaphores, so it is totally attainable 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 major(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 instrument.
The next picture exhibits the output from working c-kzg-4844’s assessments with Valgrind. Within the crimson field is a legitimate discovering for a “conditional bounce or transfer [that] depends upon uninitialized worth(s).”
This recognized an edge case in expand_root_of_unity. If the mistaken root of unity or width had been offered, it was attainable that the loop will break earlier than out[width] was initialized. On this state of affairs, the ultimate verify 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 Assessment
After improvement stabilizes, it has been totally 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 may not be a stamp of approval, however it exhibits that your mission is at the very least considerably safe. Be mindful there isn’t a such factor as excellent 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 assessment. 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 mission could possibly be exploited for positive factors, like it’s for Ethereum, contemplate organising a bug bounty program. This enables safety researchers, or anybody actually, to submit vulnerability experiences in change 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 reasonably than exploiting it or promoting it to a different social gathering. We advocate 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 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 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 invaluable insights and greatest practices for others embarking on related initiatives.
