Add CBMC target platform support#1199
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Add explicit CBMC target platform selection for the proof infrastructure, including i386 Linux support with an i686 preprocessor and matching target-model flags. Add target compiler shims for goto-instrument, a target ABI canary proof, and the solver/proof configuration tweaks needed by the 32-bit ML-DSA suite. Verification: git diff --check; python3 -B -m py_compile scripts/tests proofs/cbmc/run-cbmc-proofs.py; ./scripts/tests cbmc --help target list; canary dry-runs for i386-linux, x86_64-linux, aarch64-linux, riscv64-linux, riscv32-linux, and ppc64le-linux; nix eval --raw .#devShells.aarch64-linux.cbmc32.drvPath. Signed-off-by: Joe Doyle <joseph.doyle@trailofbits.com> Co-authored-by: Codex <codex@openai.com>
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Superseded by #1200, which keeps the same patch content but uses contiguous machine-parseable commit trailers. |
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Summary
i386-linux,x86_64-linux,aarch64-linux,riscv64-linux,riscv32-linux, andppc64le-linuxcbmc32Nix shell with the matching target compilersgoto-ccandgoto-instrumentsize_t,long, anduint64_twidthsTarget execution model
The CBMC proofs do not execute target binaries. No QEMU or binfmt is involved in these proof runs. The target compiler is used to build the GOTO program with matching headers/preprocessor definitions, and CBMC checks that program on the host under the selected target model.
The repository also has an
aarch64_becross shell, but this PR does not expose it as a CBMC target because this CBMC toolchain exposesarm64rather than a separate big-endian Arm64 model. The compiler and CBMC target model should agree before adding that lane.Verification
git diff --checkpython3 -B -m py_compile scripts/tests proofs/cbmc/run-cbmc-proofs.py./scripts/tests cbmc --help | rg -- '--cbmc-target|i386-linux|x86_64-linux|aarch64-linux|riscv64-linux|riscv32-linux|ppc64le-linux|native|ilp32'i386-linux,x86_64-linux,aarch64-linux,riscv64-linux,riscv32-linux, andppc64le-linuxnix eval --raw .#devShells.aarch64-linux.cbmc32.drvPathThis work was completed by Trail of Bits as part of the Patch The Planet project in collaboration with OpenAI. The issue was identified primarily by the Codex coding agent, and manually reviewed before submission.