For EIP-4844, Ethereum purchasers want the power to compute and confirm KZG commitments. Somewhat 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 thought was to create a sturdy and environment friendly cryptographic library that each one purchasers might use. The Protocol Safety Analysis crew 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 common 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.
Here is the fuzzer for verify_kzg_proof, one in every 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 will write the enter to disk and cease executing. Ideally, it is best to be capable of 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 improper. This system may be very common in Ethereum as a result of we prefer to have a number of implementations of the identical factor. This diversification offers an additional stage of security, understanding 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 way 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 working the exams. This can be a nice method to confirm code is executed (“lined”) and examined. See the protection goal in c-kzg-4844’s Makefile for an instance of 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’s lots of inexperienced within the desk above, however there’s 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 all the supply file and highlights non-executed code in purple. On this venture’s case, many of the non-executed code offers with hard-to-test error circumstances corresponding to reminiscence allocation failures. For instance, here is some non-executed code:
Firstly of this perform, it checks that the trusted setup is large enough to carry out a pairing test. There is not a check case which offers an invalid trusted setup, so this does not get executed. Additionally, as a result of we solely check 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 crucial library we predict it is vital to profile its exported features and measure how lengthy they take to execute. This might help determine inefficiencies which might 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 once in a while. If a perform is quick sufficient, it is probably not seen by the profiler. To scale back the possibility of this, you could have to name your perform a number of instances. On this instance, we name my_function 1000 instances.
#embodyint 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 major(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 an even 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’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) instrument corresponding to Ghidra or IDA. These instruments might help you perceive how high-level constructs are translated into low-level machine code. We predict it helps to assessment your code this manner; like how studying a paper in a distinct font will drive your mind to interpret sentences otherwise. It is also helpful to see what sort of optimizations your compiler makes. It is uncommon, however generally the compiler will optimize out one thing which it deemed pointless. Preserve a watch out for this, one thing like this really occurred in c-kzg-4844, a few of the exams had been being optimized out.
Whenever you view a decompiled perform, it is not going to 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 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 fantastic. 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 a bit work, you’ll be able to rename variables and add feedback to make it simpler to learn. Here 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 instrument 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 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 downside however we are going to speak extra about that later). The compiler is not going to determine this, even with all warnings enabled as a result of technically that is fully legitimate code.
#embodyint major(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, but it surely is smart if you consider it; the analyzer reached the return assertion and seen 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 venture:
Given an surprising 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 not possible. Good job, Clang Static Analyzer!
Sanitize
Santizers are dynamic evaluation instruments which instrument (add directions) to packages 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 determine 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 component in a 5 component array. This can be a easy instance of a heap-buffer-overflow:
#embodyint major(void) { int* arr = malloc(5 * sizeof(int)); arr[5] = 42; return 0; }
When compiled with -fsanitize=handle and executed, it is going to output the next error message. This factors you in an excellent route (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:
#embodyint 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. Here 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 is going to 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 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 conduct.
#embodyint major(void) { int a = INT_MAX; return a + 1; }
When compiled with -fsanitize=undefined and executed, it is going to 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 packages when two or extra threads entry a shared reminiscence location on the identical time. This example introduces unpredictability and might result in undefined conduct. Here is an instance wherein two threads increment a worldwide counter variable. There are no locks or semaphores, so it is fully potential that these two threads will increment the variable on the identical time.
#embodyint counter = 0; void *increment(void *arg) { (void)arg; for (int i = 0; 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 is 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 identical time. It even tells us that the reminiscence is counter.
Valgrind
Valgrind is a strong instrumentation framework for constructing dynamic evaluation instruments, however its finest 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 purple field is a legitimate discovering for a “conditional bounce or transfer [that] will depend on uninitialized worth(s).”
This recognized an edge case in expand_root_of_unity. If the improper 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 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 Assessment
After improvement stabilizes, it has been totally examined, and your crew 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, but it surely exhibits that your venture is no less than considerably safe. Take note there isn’t any 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 assessment. 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 venture could possibly be exploited for features, like it’s for Ethereum, think about establishing a bug bounty program. This permits safety researchers, or anybody actually, to submit vulnerability studies 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 fairly than exploiting it or promoting it to a different occasion. We advocate 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 sturdy C initiatives, particularly within the crucial area of blockchain and cryptocurrencies, requires a multi-faceted strategy. Given the inherent vulnerabilities related to the C language, a mix of finest 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 finest practices for others embarking on related initiatives.
