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Zeroize Audit

Trail of BitsOfficialPublished by Trail of Bits

  • Skill
  • Review and audit
  • Security
  • CC-BY-SA-4.0
  • Low risk
  • Has scripts

From the author

Detects missing zeroization of sensitive data in source code and identifies zeroization removed by compiler optimizations, with assembly-level analysis, and control-flow verification. Use for auditing C/C++/Rust code handling secrets, keys, passwords, or other sensitive data.
— the description by Trail of Bits

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

zeroize-audit is a specialized security analysis tool designed to verify that sensitive data—such as cryptographic keys, passwords, and tokens—is properly wiped from memory. It goes beyond simple source-level scanning by performing assembly-level analysis and control-flow verification to detect instances where compiler optimizations, such as dead-store elimination, inadvertently remove security-critical zeroization operations. The tool produces a structured report and generates proof-of-concept programs to validate findings, providing a rigorous audit path for security-sensitive software.

What it does

  • Detects missing zeroization of sensitive data in source code.
  • Identifies zeroization operations removed by compiler optimizations using IR and assembly diffing.
  • Performs control-flow graph analysis to verify cleanup on all execution paths.
  • Generates and validates proof-of-concept programs for identified vulnerabilities.
  • Provides assembly-level analysis to detect stack retention and register spills of secrets.
  • Supports C, C++, and Rust codebases with language-specific analysis pipelines.

When to use it

  • Auditing cryptographic implementations and key management systems.
  • Reviewing authentication systems handling passwords or session tokens.
  • Analyzing codebases that process PII or sensitive credentials.
  • Verifying secure memory cleanup in security-critical software.
  • Investigating memory safety and data leakage risks in compiled binaries.

Advantages

  • Reduces false negatives by accounting for compiler-level optimization behaviors.
  • Provides actionable evidence through generated proof-of-concept programs.
  • Supports complex analysis including control-flow and assembly-level verification.
  • Automates the tedious process of manual security code review for memory wiping.
  • Integrates with existing build systems via compile_commands.json or Cargo manifests.

Usage examples

“Audit this C library for secrets left in memory.”
The agent will analyze the provided compile_commands.json, perform source and compiler-level analysis, and generate a report detailing any missing or optimized-away zeroization.
“Check that this Rust crate actually wipes its keys.”
The agent will use the Cargo manifest to perform MIR and LLVM IR analysis, identifying if sensitive data is properly cleared or if compiler optimizations have weakened the security.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/trailofbits/zeroize-audit/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip zeroize-audit.zip -d .agents/skills

Documentation by Trail of Bits

zeroize-audit

When to Use

  • Auditing cryptographic implementations (keys, seeds, nonces, secrets)

  • Reviewing authentication systems (passwords, tokens, session data)

  • Analyzing code that handles PII or sensitive credentials

  • Verifying secure cleanup in security-critical codebases

  • Investigating memory safety of sensitive data handling

When NOT to Use

  • General code review without security focus

  • Performance optimization (unless related to secure wiping)

  • Refactoring tasks not related to sensitive data

  • Code without identifiable secrets or sensitive values


Execution Contract

Use the agent environment's available tools for file access, shell commands, worker execution, and user input. The allowed-tools entry and role-file frontmatter are legacy host metadata; they do not define another environment's tool names or grant permissions there.

  • Resolve resources. Set baseDir to the absolute directory containing this SKILL.md. Confirm the linked input schema and orchestrator prompt exist there. {baseDir}, {workdir}, and {{input}} are notation for values the orchestrator must substitute, not environment variables or automatic host expansion. Resolve relative Markdown links against the directory of the file containing them; resolve {baseDir}/… paths against the skill directory. Pass resolved paths to workers and shell commands.

  • Launch a role. Read the role prompt linked in the Agent Architecture table. When the environment has a registered worker for the role, use its zeroize-audit:<role-name> identifier (for example, zeroize-audit:0-preflight); otherwise create an independent worker with the Markdown body of that prompt, the current phase's instructions, and its parameter values. Always include the resolved baseDir and, once created, workdir, even when a phase table does not repeat them. Resolve resource references using the rules above before delegation. Worker file/search/shell actions use the environment's actual tool schemas and permissions. The role's name identifies its instructions, not a required dispatch API or model.

  • Wait for results. Retain each worker's handle and wait through the environment's completion mechanism. A launch acknowledgement is not completion. Read the phase's required artifacts before updating its completion state or starting a dependent phase. On worker failure or unavailable dispatch, apply only that phase's documented fallback; otherwise record the failure in the existing run state and report the affected phase as blocked.

  • Concurrency. Respect available concurrency and phase barriers. Run workers sequentially when parallel execution is unavailable. Per-TU compiler workers write to separate directories and may run concurrently.

  • Collect decisions. Use the environment's user-input facility or ask in the conversation. When a phase requires an answer, wait for it; do not substitute a default or elapsed time for the user's decision. Preserve the validation and verification outcomes when recording any accepted or rejected PoC result.

How to Run

On a request like "audit this crate for secrets left in memory" or "check that this C library actually wipes its keys":

  1. Collect inputs. Map the request onto the Inputs table below (full schema: schemas/input.json). path is required, plus at least one of compile_db (C/C++) or cargo_manifest (Rust); if neither is given or derivable from the repo, ask the user, because preflight stops the run without one. Leave all other fields at their defaults unless the user says otherwise.

  2. Read the orchestrator prompt, substituting the collected inputs for its {{placeholder}} values. You act as the orchestrator it describes: it defines state recovery, the phase loop, early termination, and error handling. Read the shared instructions alongside it for the shared working-directory layout and the agent error protocol every phase depends on.

  3. Execute its phase loop. Run Phases 0-7 sequentially. Before each phase, read that phase's workflow file from {baseDir}/workflows/phase-{N}-{name}.md and follow its Preconditions, Instructions, State Update, and Error Handling sections. Each workflow specifies the role prompt and parameters to use under the Execution Contract above. Honor the per-phase skip conditions and the early-termination rules in task.md.

  4. Return the report (Phase 8, inline): read {workdir}/report/final-report.md and return its contents as the skill output.

To resume an interrupted run: if a workdir is known from prior context, read {workdir}/orchestrator-state.json and continue from its current_phase instead of starting at Phase 0 (see the Recovery section of task.md).


Purpose

Detect missing zeroization of sensitive data in source code and identify zeroization that is removed or weakened by compiler optimizations (e.g., dead-store elimination), with mandatory LLVM IR/asm evidence. Capabilities include:

  • Assembly-level analysis for register spills and stack retention

  • Data-flow tracking for secret copies

  • Heap allocator security warnings

  • Semantic IR analysis for loop unrolling and SSA form

  • Control-flow graph analysis for path coverage verification

  • Runtime validation test generation

Scope

  • Read-only against the target codebase (does not modify audited code; writes analysis artifacts to a temporary working directory).

  • Produces a structured report (JSON).

  • Requires valid build context (compile_commands.json) and compilable translation units.

  • "Optimized away" findings only allowed with compiler evidence (IR/asm diff).


Inputs

See schemas/input.json for the full schema. Key fields:

FieldRequiredDefaultDescription
pathyes—Repo root
compile_dbnonullPath to compile_commands.json for C/C++ analysis. Required if cargo_manifest is not set.
cargo_manifestnonullPath to Cargo.toml for Rust crate analysis. Required if compile_db is not set.
configno—YAML defining heuristics and approved wipes
opt_levelsno["O0","O1","O2"]Optimization levels for IR comparison. O1 is the diagnostic level: if a wipe disappears at O1 it is simple DSE; O2 catches more aggressive eliminations.
languagesno["c","cpp","rust"]Languages to analyze
max_tusno50Limit on translation units processed from compile DB
mcp_modenopreferoff, prefer, or require — controls Serena MCP usage
mcp_required_for_advancednotrueDowngrade SECRET_COPY, MISSING_ON_ERROR_PATH, and NOT_DOMINATING_EXITS to needs_review when MCP is unavailable
mcp_timeout_msno10000Timeout budget for MCP semantic queries
poc_categoriesnoall 11 exploitableFinding categories for which to generate PoCs. C/C++ findings: all 11 categories supported. Rust findings: only MISSING_SOURCE_ZEROIZE, SECRET_COPY, and PARTIAL_WIPE are supported; other Rust categories are marked poc_supported=false.
poc_output_dirnogenerated_pocs/Output directory for generated PoCs
enable_asmnotrueEnable assembly emission and analysis (Step 8); produces STACK_RETENTION, REGISTER_SPILL. Auto-disabled if emit_asm.sh is missing.
enable_semantic_irnofalseEnable semantic LLVM IR analysis (Step 9); produces LOOP_UNROLLED_INCOMPLETE
enable_cfgnofalseEnable control-flow graph analysis (Step 10); produces MISSING_ON_ERROR_PATH, NOT_DOMINATING_EXITS
enable_runtime_testsnofalseEnable runtime test harness generation (Step 11)

Prerequisites

Before running, verify the following. Each has a defined failure mode.

C/C++ prerequisites:

PrerequisiteFailure mode if missing
compile_commands.json at compile_db pathFail fast — do not proceed
clang on PATHFail fast — IR/ASM analysis impossible
uvx on PATH (for Serena)If mcp_mode=require: fail. If mcp_mode=prefer: continue without MCP; downgrade affected findings per Confidence Gating rules.
{baseDir}/tools/extract_compile_flags.pyFail fast — cannot extract per-TU flags
{baseDir}/tools/emit_ir.shFail fast — IR analysis impossible
{baseDir}/tools/emit_asm.shWarn and skip assembly findings (STACK_RETENTION, REGISTER_SPILL)
{baseDir}/tools/mcp/check_mcp.shWarn and treat as MCP unavailable
{baseDir}/tools/mcp/normalize_mcp_evidence.pyWarn and use raw MCP output

Rust prerequisites:

PrerequisiteFailure mode if missing
Cargo.toml at cargo_manifest pathFail fast — do not proceed
cargo check passesFail fast — crate must be buildable
cargo +nightly on PATHFail fast — nightly required for MIR and LLVM IR emission
uv on PATHFail fast — required to run Python analysis scripts
{baseDir}/tools/validate_rust_toolchain.shWarn — run preflight manually. Checks all tools, scripts, nightly, and optionally cargo check. Use --json for machine-readable output, --manifest to also validate the crate builds.
{baseDir}/tools/emit_rust_mir.shFail fast — MIR analysis impossible (--opt, --crate, --bin/--lib supported; --out can be file or directory)
{baseDir}/tools/emit_rust_ir.shFail fast — LLVM IR analysis impossible (--opt required; --crate, --bin/--lib supported; --out must be .ll)
{baseDir}/tools/emit_rust_asm.shWarn and skip assembly findings (STACK_RETENTION, REGISTER_SPILL). Supports --opt, --crate, --bin/--lib, --target, --intel-syntax; --out can be .s file or directory.
{baseDir}/tools/diff_rust_mir.shWarn and skip MIR-level optimization comparison. Accepts 2+ MIR files, normalizes, diffs pairwise, and reports first opt level where zeroize/drop-glue patterns disappear.
{baseDir}/tools/scripts/semantic_audit.pyWarn and skip semantic source analysis
{baseDir}/tools/scripts/find_dangerous_apis.pyWarn and skip dangerous API scan
{baseDir}/tools/scripts/check_mir_patterns.pyWarn and skip MIR analysis
{baseDir}/tools/scripts/check_llvm_patterns.pyWarn and skip LLVM IR analysis
{baseDir}/tools/scripts/check_rust_asm.pyWarn and skip Rust assembly analysis (STACK_RETENTION, REGISTER_SPILL, drop-glue checks). Dispatches to check_rust_asm_x86.py (production) or check_rust_asm_aarch64.py (EXPERIMENTAL — AArch64 findings require manual verification).
{baseDir}/tools/scripts/check_rust_asm_x86.pyRequired by check_rust_asm.py for x86-64 analysis; warn and skip if missing
{baseDir}/tools/scripts/check_rust_asm_aarch64.pyRequired by check_rust_asm.py for AArch64 analysis (EXPERIMENTAL); warn and skip if missing

Common prerequisite:

PrerequisiteFailure mode if missing
{baseDir}/tools/generate_poc.pyFail fast — PoC generation is mandatory

Approved Wipe APIs

The following are recognized as valid zeroization. Configure additional entries in {baseDir}/configs/.

C/C++

  • explicit_bzero

  • memset_s

  • SecureZeroMemory

  • OPENSSL_cleanse

  • sodium_memzero

  • Volatile wipe loops (pattern-based; see volatile_wipe_patterns in {baseDir}/configs/default.yaml)

  • In IR: llvm.memset with volatile flag, volatile stores, or non-elidable wipe call

Rust

  • zeroize::Zeroize trait (zeroize() method)

  • Zeroizing<T> wrapper (drop-based)

  • ZeroizeOnDrop derive macro


Finding Capabilities

Findings are grouped by required evidence. Only attempt findings for which the required tooling is available.

Finding IDDescriptionRequiresPoC Support
MISSING_SOURCE_ZEROIZENo zeroization found in sourceSource onlyYes (C/C++ + Rust)
PARTIAL_WIPEIncorrect size or incomplete wipeSource onlyYes (C/C++ + Rust)
NOT_ON_ALL_PATHSZeroization missing on some control-flow paths (heuristic)Source onlyYes (C/C++ only)
SECRET_COPYSensitive data copied without zeroization trackingSource + MCP preferredYes (C/C++ + Rust)
INSECURE_HEAP_ALLOCSecret uses insecure allocator (malloc vs. secure_malloc)Source onlyYes (C/C++ only)
OPTIMIZED_AWAY_ZEROIZECompiler removed zeroizationIR diff required (never source-only)Yes
STACK_RETENTIONStack frame may retain secrets after returnAssembly required (C/C++); LLVM IR alloca+lifetime.end evidence (Rust); assembly corroboration upgrades to confirmedYes (C/C++ only)
REGISTER_SPILLSecrets spilled from registers to stackAssembly required (C/C++); LLVM IR load+call-site evidence (Rust); assembly corroboration upgrades to confirmedYes (C/C++ only)
MISSING_ON_ERROR_PATHError-handling paths lack cleanupCFG or MCP requiredYes
NOT_DOMINATING_EXITSWipe doesn't dominate all exitsCFG or MCP requiredYes
LOOP_UNROLLED_INCOMPLETEUnrolled loop wipe is incompleteSemantic IR requiredYes

Agent Architecture

The analysis pipeline uses 11 worker roles across 8 phases, launched by the orchestrator using the Execution Contract above. Agents write persistent finding files to a shared working directory (/tmp/zeroize-audit-{run_id}/), enabling parallel execution and protecting against context pressure.

AgentPhasePurposeOutput Directory
0-preflightPhase 0Preflight checks (tools, toolchain, compile DB, crate build), config merge, workdir creation, TU enumeration{workdir}/
1-mcp-resolverPhase 1, Wave 1 (C/C++ only)Resolve symbols, types, and cross-file references via Serena MCPmcp-evidence/
2-source-analyzerPhase 1, Wave 2a (C/C++ only)Identify sensitive objects, detect wipes, validate correctness, data-flow/heapsource-analysis/
2b-rust-source-analyzerPhase 1, Wave 2b (Rust only, parallel with 2a)Rustdoc JSON trait-aware analysis + dangerous API grepsource-analysis/
3-tu-compiler-analyzerPhase 2, Wave 3 (C/C++ only, N parallel)Per-TU IR diff, assembly, semantic IR, CFG analysiscompiler-analysis/{tu_hash}/
3b-rust-compiler-analyzerPhase 2, Wave 3R (Rust only, single agent)Crate-level MIR, LLVM IR, and assembly analysisrust-compiler-analysis/
4-report-assemblerPhase 3 (interim) + Phase 6 (final)Collect findings from all agents, apply confidence gates; merge PoC results and produce final reportreport/
5-poc-generatorPhase 4Craft bespoke proof-of-concept programs (C/C++: all categories; Rust: MISSING_SOURCE_ZEROIZE, SECRET_COPY, PARTIAL_WIPE)poc/
5b-poc-validatorPhase 5Compile and run all PoCspoc/
5c-poc-verifierPhase 5Verify each PoC proves its claimed findingpoc/
6-test-generatorPhase 7 (optional)Generate runtime validation test harnessestests/

The orchestrator reads one per-phase workflow file from {baseDir}/workflows/ at a time, and maintains orchestrator-state.json for recovery after context compression. Agents receive configuration by file path (config_path), not by value.

Execution flow
Phase 0: 0-preflight agent — Preflight + config + create workdir + enumerate TUs
           → writes orchestrator-state.json, merged-config.yaml, preflight.json
Phase 1: Wave 1:  1-mcp-resolver              (skip if mcp_mode=off OR language_mode=rust)
         Wave 2a: 2-source-analyzer           (C/C++ only; skip if no compile_db)  ─┐ parallel
         Wave 2b: 2b-rust-source-analyzer     (Rust only; skip if no cargo_manifest) ─┘
Phase 2: Wave 3:  3-tu-compiler-analyzer x N  (C/C++ only; parallel per TU)
         Wave 3R: 3b-rust-compiler-analyzer   (Rust only; single crate-level agent)
Phase 3: Wave 4:  4-report-assembler          (mode=interim → findings.json; reads all agent outputs)
Phase 4: Wave 5:  5-poc-generator             (C/C++: all categories; Rust: MISSING_SOURCE_ZEROIZE, SECRET_COPY, PARTIAL_WIPE; other Rust findings: poc_supported=false)
Phase 5: PoC Validation & Verification
           Step 1: 5b-poc-validator agent      (compile and run all PoCs)
           Step 2: 5c-poc-verifier agent       (verify each PoC proves its claimed finding)
           Step 3: Orchestrator asks the user to accept or reject failed verification
           Step 4: Orchestrator merges all results into poc_final_results.json
Phase 6: Wave 6: 4-report-assembler           (mode=final → merge PoC results, final-report.md)
Phase 7: Wave 7: 6-test-generator             (optional)
Phase 8: Orchestrator — Return final-report.md

Cross-Reference Convention

IDs are namespaced per agent to prevent collisions during parallel execution:

EntityPatternAssigned By
Sensitive object (C/C++)SO-0001–SO-49992-source-analyzer
Sensitive object (Rust)SO-5000–SO-9999 (Rust namespace)2b-rust-source-analyzer
Source finding (C/C++)F-SRC-NNNN2-source-analyzer
Source finding (Rust)F-RUST-SRC-NNNN2b-rust-source-analyzer
IR finding (C/C++)F-IR-{tu_hash}-NNNN3-tu-compiler-analyzer
ASM finding (C/C++)F-ASM-{tu_hash}-NNNN3-tu-compiler-analyzer
CFG findingF-CFG-{tu_hash}-NNNN3-tu-compiler-analyzer
Semantic IR findingF-SIR-{tu_hash}-NNNN3-tu-compiler-analyzer
Rust MIR findingF-RUST-MIR-NNNN3b-rust-compiler-analyzer
Rust LLVM IR findingF-RUST-IR-NNNN3b-rust-compiler-analyzer
Rust assembly findingF-RUST-ASM-NNNN3b-rust-compiler-analyzer
Translation unitTU-{hash}Orchestrator
Final findingZA-NNNN4-report-assembler

Every finding JSON object includes related_objects, related_findings, and evidence_files fields for cross-referencing between agents.


Detection Strategy

Analysis runs in two phases. For complete step-by-step guidance, see {baseDir}/references/detection-strategy.md.

PhaseStepsFindings producedRequired tooling
Phase 1 (Source)1–6MISSING_SOURCE_ZEROIZE, PARTIAL_WIPE, NOT_ON_ALL_PATHS, SECRET_COPY, INSECURE_HEAP_ALLOCSource + compile DB
Phase 2 (Compiler)7–12OPTIMIZED_AWAY_ZEROIZE, STACK_RETENTION, REGISTER_SPILL, LOOP_UNROLLED_INCOMPLETE†, MISSING_ON_ERROR_PATH‡, NOT_DOMINATING_EXITS‡clang, IR/ASM tools

* requires enable_asm=true (default) † requires enable_semantic_ir=true ‡ requires enable_cfg=true

For Rust, {baseDir}/references/rust-zeroization-patterns.md catalogues 40 named anti-patterns, keyed to the script that detects each one: Section A for rustdoc-JSON semantics (semantic_audit.py), Section B for dangerous APIs (find_dangerous_apis.py), and Section C for MIR/LLVM IR/assembly (check_mir_patterns.py, check_llvm_patterns.py, check_rust_asm.py). Read the relevant section when triaging a Rust finding, writing its fix recommendation, or deciding whether a hand-spotted pattern is already covered.

Two limits on how far that reference goes. The 34 entries in Sections A-C are what the scripts detect today; Section D's six are known gaps no script covers, so treat those as unaudited rather than clean. Sections A and C are also partial — the scripts emit some classes with no entry — so a finding that matches no catalogued pattern is still a finding, carrying whatever evidence the script produced.


Output Format

Each run produces two outputs:

  1. final-report.md — Comprehensive markdown report (primary human-readable output)

  2. findings.json — Structured JSON matching {baseDir}/schemas/output.json (for machine consumption and downstream tools)

Markdown Report Structure

The markdown report (final-report.md) contains these sections:

  • Header: Run metadata (run_id, timestamp, repo, compile_db, config summary)

  • Executive Summary: Finding counts by severity, confidence, and category

  • Sensitive Objects Inventory: Table of all identified objects with IDs, types, locations

  • Findings: Grouped by severity then confidence. Each finding includes location, object, all evidence (source/IR/ASM/CFG), compiler evidence details, and recommended fix

  • Superseded Findings: Source findings replaced by CFG-backed findings

  • Confidence Gate Summary: Downgrades applied and overrides rejected

  • Analysis Coverage: TUs analyzed, agent success/failure, features enabled, and any Section D patterns the crate uses that no script audits

  • Appendix: Evidence Files: Mapping of finding IDs to evidence file paths

Structured JSON

The findings.json file follows the schema in {baseDir}/schemas/output.json. Each Finding object:

{
  "id": "ZA-0001",
  "category": "OPTIMIZED_AWAY_ZEROIZE",
  "severity": "high",
  "confidence": "confirmed",
  "language": "c",
  "file": "src/crypto.c",
  "line": 42,
  "symbol": "key_buf",
  "evidence": "store volatile i8 0 count: O0=32, O2=0 — wipe eliminated by DSE",
  "compiler_evidence": {
    "opt_levels": ["O0", "O2"],
    "o0": "32 volatile stores targeting key_buf",
    "o2": "0 volatile stores (all eliminated)",
    "diff_summary": "All volatile wipe stores removed at O2 — classic DSE pattern"
  },
  "suggested_fix": "Replace memset with explicit_bzero or add compiler_fence(SeqCst) after the wipe",
  "poc": {
    "file": "generated_pocs/ZA-0001.c",
    "makefile_target": "ZA-0001",
    "compile_opt": "-O2",
    "requires_manual_adjustment": false,
    "validated": true,
    "validation_result": "exploitable"
  }
}

See {baseDir}/schemas/output.json for the full schema and enum values.


Confidence Gating

Evidence thresholds

A finding requires at least 2 independent signals to be marked confirmed. With 1 signal, mark likely. With 0 strong signals (name-pattern match only), mark needs_review.

Signals include: name pattern match, type hint match, explicit annotation, IR evidence, ASM evidence, MCP cross-reference, CFG evidence, PoC validation.

PoC validation as evidence signal

Every finding is validated against a bespoke PoC. After compilation and execution, each PoC is also verified to ensure it actually tests the claimed vulnerability. The combined result is an evidence signal:

PoC ResultVerifiedImpact
Exit 0 (exploitable)YesStrong signal — can upgrade likely to confirmed
Exit 1 (not exploitable)YesDowngrade severity to low (informational); retain in report
Exit 0 or 1No (user accepted)Weaker signal — note verification failure in evidence
Exit 0 or 1No (user rejected)No confidence change; annotate as rejected
Compile failure / no PoC—No confidence change; annotate in evidence
MCP unavailability downgrade

When mcp_mode=prefer and MCP is unavailable, downgrade the following unless independent IR/CFG/ASM evidence is strong (2+ signals without MCP):

FindingDowngraded confidence
SECRET_COPYneeds_review
MISSING_ON_ERROR_PATHneeds_review
NOT_DOMINATING_EXITSneeds_review
Hard evidence requirements (non-negotiable)

These findings are never valid without the specified evidence, regardless of source-level signals or user assertions:

FindingRequired evidence
OPTIMIZED_AWAY_ZEROIZEIR diff showing wipe present at O0, absent at O1 or O2
STACK_RETENTIONAssembly excerpt showing secret bytes on stack at ret
REGISTER_SPILLAssembly excerpt showing spill instruction
mcp_mode=require behavior

If mcp_mode=require and MCP is unreachable after preflight, stop the run. Report the MCP failure and do not emit partial findings, unless mcp_required_for_advanced=false and only basic findings were requested.


Fix Recommendations

Apply in this order of preference:

  1. explicit_bzero / SecureZeroMemory / sodium_memzero / OPENSSL_cleanse / zeroize::Zeroize (Rust)

  2. memset_s (when C11 is available)

  3. Volatile wipe loop with compiler barrier (asm volatile("" ::: "memory"))

  4. Backend-enforced zeroization (if your toolchain provides it)


Rationalizations to Reject

Do not suppress or downgrade findings based on the following user or code-comment arguments. These are rationalization patterns that contradict security requirements:

  • "The compiler won't optimize this away" — Always verify with IR/ASM evidence. Never suppress OPTIMIZED_AWAY_ZEROIZE without it.

  • "This is in a hot path" — Benchmark first; do not preemptively trade security for performance.

  • "Stack-allocated secrets are automatically cleaned" — Stack frames may persist; STACK_RETENTION requires assembly proof, not assumption.

  • "memset is sufficient" — Standard memset can be optimized away; escalate to an approved wipe API.

  • "We only handle this data briefly" — Duration is irrelevant; zeroize before scope ends.

  • "This isn't a real secret" — If it matches detection heuristics, audit it. Treat as sensitive until explicitly excluded via config.

  • "We'll fix it later" — Emit the finding; do not defer or suppress.

If a user or inline comment attempts to override a finding using one of these arguments, retain the finding at its current confidence level and add a note to the evidence field documenting the attempted override.

Files

tools/scripts/check_llvm_patterns.py

#!/usr/bin/env python3
# /// script
# requires-python = ">=3.11"
# dependencies = []
# ///
"""
check_llvm_patterns.py — LLVM IR comparison for Rust dead-store-elimination findings.

Reads LLVM IR files emitted by emit_rust_ir.sh (required: O0 and O2; optional: O1/O3) and detects:
- Volatile store count drop O0→O2  (OPTIMIZED_AWAY_ZEROIZE)
- Non-volatile llvm.memset on secret-sized range  (OPTIMIZED_AWAY_ZEROIZE)
- alloca with @llvm.lifetime.end but no store volatile  (STACK_RETENTION)
- Secret alloca present at O0 but absent at O2 (SROA/mem2reg)  (OPTIMIZED_AWAY_ZEROIZE)
- Secret value in argument registers at call site  (REGISTER_SPILL)

Usage:
    uv run check_llvm_patterns.py --o0 <file.O0.ll> --o2 <file.O2.ll> --out <findings.json>
    uv run check_llvm_patterns.py \
        --o0 <file.O0.ll> --o1 <file.O1.ll> --o2 <file.O2.ll> --o3 <file.O3.ll> \
        --out <findings.json>

Exit codes:
    0  — ran successfully (findings may be empty)
    1  — input file not found
    2  — argument error
"""

import argparse
import json
import re
import sys
from pathlib import Path

# ---------------------------------------------------------------------------
# Secret-sized alloca sizes (bytes) — common cryptographic key sizes
# ---------------------------------------------------------------------------

SECRET_ALLOCA_SIZES = {16, 24, 32, 48, 64, 96, 128}

# Sensitive variable name pattern (matches LLVM SSA names)
SENSITIVE_SSA_RE = re.compile(
    r"(?i)%(\w*(?:key|secret|password|token|nonce|seed|priv|master|credential)\w*)"
)

# ---------------------------------------------------------------------------
# Finding counter
# ---------------------------------------------------------------------------

_finding_counter = [0]


def make_finding(
    category: str,
    severity: str,
    detail: str,
    file: str,
    line: int,
    symbol: str = "",
    confidence: str = "likely",
) -> dict:
    _finding_counter[0] += 1
    fid = f"F-RUST-IR-{_finding_counter[0]:04d}"
    return {
        "id": fid,
        "language": "rust",
        "category": category,
        "severity": severity,
        "confidence": confidence,
        "detail": detail,
        "symbol": symbol,
        "location": {"file": file, "line": line},
        "evidence": [{"source": "llvm_ir", "detail": detail}],
    }


# ---------------------------------------------------------------------------
# IR helpers
# ---------------------------------------------------------------------------


def count_volatile_stores(ir_text: str) -> int:
    return len(re.findall(r"\bstore volatile\b", ir_text))


def extract_volatile_stores_by_target(ir_text: str) -> dict[str, int]:
    """
    Return volatile-store counts keyed by the destination symbol.
    Example matches:
      store volatile i8 0, ptr %key
      store volatile i32 0, i32* %buf
    """
    stores: dict[str, int] = {}
    vol_re = re.compile(r"\bstore volatile\b[^,]*,\s*(?:ptr|i\d+\*)\s+%([\w\.\-]+)")
    for m in vol_re.finditer(ir_text):
        name = m.group(1)
        stores[name] = stores.get(name, 0) + 1
    return stores


def extract_allocas(ir_text: str) -> dict[str, int]:
    """
    Return {alloca_name: size_bytes} for fixed-size byte array allocas.
    Matches: %name = alloca [N x i8]
    """
    alloca_re = re.compile(r"%(\w+)\s*=\s*alloca\s+\[(\d+)\s*x\s*i8\]")
    allocas: dict[str, int] = {}
    for m in alloca_re.finditer(ir_text):
        allocas[m.group(1)] = int(m.group(2))
    return allocas


def extract_lifetime_ends(ir_text: str) -> set[str]:
    """Return set of alloca names referenced in @llvm.lifetime.end calls."""
    lifetime_re = re.compile(r"call void @llvm\.lifetime\.end[^(]*\([^,]+,\s*(?:ptr|i8\*)\s+%(\w+)")
    return {m.group(1) for m in lifetime_re.finditer(ir_text)}


def extract_volatile_store_targets(ir_text: str) -> set[str]:
    """Return set of symbols that receive volatile stores."""
    return set(extract_volatile_stores_by_target(ir_text).keys())


def find_nonvolatile_memsets(ir_text: str) -> list[tuple[int, str]]:
    """
    Return (lineno, line) for non-volatile @llvm.memset calls.
    Volatile variant is @llvm.memset.element.unordered.atomic or has i1 true volatile flag.
    """
    results: list[tuple[int, str]] = []
    memset_re = re.compile(r"call void @llvm\.memset\.")
    volatile_flag_re = re.compile(r"i1\s+true")  # old-style volatile flag in args

    for lineno, line in enumerate(ir_text.splitlines(), start=1):
        if not memset_re.search(line):
            continue
        # Skip if it's the volatile atomic variant
        if "unordered.atomic" in line:
            continue
        # Skip if volatile flag (i1 true) is present in args
        if volatile_flag_re.search(line):
            continue
        results.append((lineno, line.strip()))
    return results


def find_secret_returns(ir_text: str) -> list[tuple[int, str]]:
    """
    Detect returns of secret-named SSA values.
    Returns (lineno, symbol_without_percent).
    """
    results: list[tuple[int, str]] = []
    ret_re = re.compile(
        r"\bret\s+[^%]*%(\w*(?:key|secret|password|token|nonce|seed|priv|master|credential)\w*)",
        re.IGNORECASE,
    )
    for lineno, line in enumerate(ir_text.splitlines(), start=1):
        m = ret_re.search(line)
        if m:
            results.append((lineno, m.group(1)))
    return results


def find_secret_aggregate_passes(ir_text: str) -> list[tuple[int, str]]:
    """
    Detect call sites that appear to pass aggregate values containing secret-named
    symbols by value. This is heuristic and intentionally conservative.
    Returns (lineno, argument_snippet).
    """
    results: list[tuple[int, str]] = []
    call_re = re.compile(r"\bcall\s+\S+\s+@\w+\s*\(([^)]*)\)")
    for lineno, line in enumerate(ir_text.splitlines(), start=1):
        m = call_re.search(line)
        if not m:
            continue
        args = m.group(1)
        if re.search(
            r"%\w*(?:key|secret|password|token|nonce|seed|priv|master|credential)\w*",
            args,
            re.IGNORECASE,
        ) and ("{" in args or "byval" in args):
            results.append((lineno, args[:120]))
    return results


def find_arg_load_calls(ir_text: str) -> list[tuple[int, str, str]]:
    """
    Detect: %secret_val = load ... %secret_alloca  followed by a call that uses %secret_val.
    Returns (lineno, varname, callee).
    """
    results: list[tuple[int, str, str]] = []
    lines = ir_text.splitlines()

    load_re = re.compile(
        r"(%\w*(?:key|secret|password|token|nonce|seed)\w*)\s*=\s*load\b", re.IGNORECASE
    )
    call_re = re.compile(r"call\s+\S+\s+(@\w+)\s*\(([^)]*)\)")

    loaded_vars: dict[str, int] = {}  # varname → lineno
    define_re = re.compile(r"^define\s")

    for lineno, line in enumerate(lines, start=1):
        # Reset tracked loads at each LLVM IR function boundary to avoid
        # cross-function false positives (I17).
        if define_re.match(line):
            loaded_vars.clear()
            continue

        # Track loads of sensitive-named SSA values
        m = load_re.search(line)
        if m:
            loaded_vars[m.group(1)] = lineno
            continue

        # Check call sites
        mc = call_re.search(line)
        if not mc:
            continue
        callee = mc.group(1)
        if "zeroize" in callee.lower() or "memset" in callee.lower():
            continue
        args = mc.group(2)
        for varname, _load_lineno in loaded_vars.items():
            if varname in args:
                results.append((lineno, varname.lstrip("%"), callee))

    return results


# ---------------------------------------------------------------------------
# Main analysis
# ---------------------------------------------------------------------------


def analyze(level_to_ir: dict[str, tuple[str, str]]) -> list[dict]:
    """Analyze LLVM IR files for zeroization issues.

    Precondition: ``level_to_ir`` must contain at least ``"O0"`` and ``"O2"``
    keys — if either is absent the function returns an empty list with no
    diagnostic.  The CLI always satisfies this; library callers must ensure it.
    """
    findings: list[dict] = []
    if "O0" not in level_to_ir or "O2" not in level_to_ir:
        return findings

    o0_file, o0_text = level_to_ir["O0"]
    o2_file, o2_text = level_to_ir["O2"]

    # --- 1. Global volatile store count drop O0 → O2 ---
    o0_vol_count = count_volatile_stores(o0_text)
    o2_vol_count = count_volatile_stores(o2_text)

    if o0_vol_count > o2_vol_count:
        diff = o0_vol_count - o2_vol_count
        # line=0 is used for file-level findings that cannot be attributed to a
        # single source line (I18).  Downstream consumers should treat line 0
        # as "file-level / unknown line".
        findings.append(
            make_finding(
                "OPTIMIZED_AWAY_ZEROIZE",
                "high",
                f"Volatile store count dropped from {o0_vol_count} (O0) to {o2_vol_count} (O2) "
                f"— {diff} volatile wipe(s) eliminated by dead-store elimination",
                o2_file,
                0,
            )
        )

    # --- 1b. Per-target volatile store drop O0 -> O2 (hard evidence by symbol) ---
    o0_vol_by_target = extract_volatile_stores_by_target(o0_text)
    o2_vol_by_target = extract_volatile_stores_by_target(o2_text)
    for target, o0_count in sorted(o0_vol_by_target.items()):
        o2_count = o2_vol_by_target.get(target, 0)
        if o0_count > o2_count:
            findings.append(
                make_finding(
                    "OPTIMIZED_AWAY_ZEROIZE",
                    "high",
                    f"Volatile stores to %{target} dropped from {o0_count} (O0) to {o2_count} (O2) "
                    f"— symbol-specific wipe elimination detected",
                    o2_file,
                    0,
                    symbol=target,
                )
            )

    # --- 2. Non-volatile llvm.memset calls in O2 IR ---
    for lineno, line_text in find_nonvolatile_memsets(o2_text):
        findings.append(
            make_finding(
                "OPTIMIZED_AWAY_ZEROIZE",
                "high",
                f"Non-volatile @llvm.memset in O2 IR — DSE-eligible, may be removed at higher "
                f"optimization. Use zeroize crate or volatile memset. IR: {line_text[:80]}",
                o2_file,
                lineno,
            )
        )

    # --- 3. alloca with lifetime.end but no volatile store (STACK_RETENTION) ---
    o2_allocas = extract_allocas(o2_text)
    o2_lifetime_ends = extract_lifetime_ends(o2_text)
    o2_vol_targets = extract_volatile_store_targets(o2_text)

    for alloca_name, size in o2_allocas.items():
        if size not in SECRET_ALLOCA_SIZES:
            continue
        if alloca_name not in o2_lifetime_ends:
            continue
        if alloca_name in o2_vol_targets:
            continue
        findings.append(
            make_finding(
                "STACK_RETENTION",
                "high",
                f"alloca [{size} x i8] %{alloca_name} has @llvm.lifetime.end but no "
                "volatile store — stack bytes not wiped before slot is freed",
                o2_file,
                0,
                symbol=alloca_name,
            )
        )

    # --- 4. SROA/mem2reg: secret alloca present at O0 but absent at O2 ---
    o0_allocas = extract_allocas(o0_text)

    o0_vol_targets = extract_volatile_store_targets(o0_text)
    for alloca_name, size in o0_allocas.items():
        if size not in SECRET_ALLOCA_SIZES:
            continue
        if alloca_name in o2_allocas:
            continue
        # Hard evidence gate: only emit when O0 showed a wipe target on this alloca.
        if alloca_name not in o0_vol_targets:
            continue
        findings.append(
            make_finding(
                "OPTIMIZED_AWAY_ZEROIZE",
                "high",
                f"alloca [{size} x i8] %{alloca_name} present at O0 but absent at O2 — "
                "SROA/mem2reg promoted it to registers; any volatile stores targeting this "
                "alloca are now unreachable",
                o2_file,
                0,
                symbol=alloca_name,
            )
        )

    # --- 5. Secret value in argument registers at call site (REGISTER_SPILL) ---
    for lineno, varname, callee in find_arg_load_calls(o2_text):
        findings.append(
            make_finding(
                "REGISTER_SPILL",
                "medium",
                f"Secret-named SSA value '%{varname}' loaded and passed directly to "
                f"'{callee}' — value in argument register may not be cleared after call",
                o2_file,
                lineno,
                symbol=varname,
            )
        )

    # --- 6. Secret return values can persist in return registers ---
    for lineno, varname in find_secret_returns(o2_text):
        findings.append(
            make_finding(
                "REGISTER_SPILL",
                "medium",
                f"Secret-named SSA value '%{varname}' is returned directly — "
                "value may persist in return registers after function exit",
                o2_file,
                lineno,
                symbol=varname,
            )
        )

    # --- 7. Aggregate/by-value secret argument passing ---
    for lineno, snippet in find_secret_aggregate_passes(o2_text):
        findings.append(
            make_finding(
                "SECRET_COPY",
                "medium",
                "Potential by-value aggregate call argument contains secret-named data; "
                f"copy may escape zeroization tracking. Args: {snippet}",
                o2_file,
                lineno,
            )
        )

    # Collect targets already reported in section 1b (O0→O2 per-symbol comparison)
    # so that the multi-level section below does not re-emit the same target.
    reported_by_1b: set[str] = {
        target
        for target, o0_count in o0_vol_by_target.items()
        if o0_count > o2_vol_by_target.get(target, 0)
    }

    # --- 8. Optional multi-level comparison (O0->O1->O2, O2->O3) ---
    # Skip the (O0, O2) adjacent pair when O1 is absent — that comparison is already
    # done by sections 1 and 1b above, and re-emitting it here causes duplicate findings.
    level_order = ["O0", "O1", "O2", "O3"]
    present = [lvl for lvl in level_order if lvl in level_to_ir]
    for idx in range(len(present) - 1):
        from_level = present[idx]
        to_level = present[idx + 1]
        # O0→O2 without an intermediate O1 is already covered by sections 1/1b.
        if from_level == "O0" and to_level == "O2":
            continue
        _, from_ir = level_to_ir[from_level]
        to_file, to_ir = level_to_ir[to_level]
        from_targets = extract_volatile_stores_by_target(from_ir)
        to_targets = extract_volatile_stores_by_target(to_ir)
        for target, from_count in sorted(from_targets.items()):
            # Skip targets already covered by section 1b to avoid cascading duplicates.
            if target in reported_by_1b:
                continue
            to_count = to_targets.get(target, 0)
            if from_count > to_count:
                findings.append(
                    make_finding(
                        "OPTIMIZED_AWAY_ZEROIZE",
                        "high",
                        f"Volatile stores to %{target} dropped from {from_count} ({from_level}) "
                        f"to {to_count} ({to_level})",
                        to_file,
                        0,
                        symbol=target,
                    )
                )

    return findings


# ---------------------------------------------------------------------------
# CLI
# ---------------------------------------------------------------------------


def main() -> int:
    parser = argparse.ArgumentParser(
        description="LLVM IR O0 vs O2 comparison for Rust dead-store-elimination findings"
    )
    parser.add_argument("--o0", required=True, help="Path to O0 .ll file")
    parser.add_argument("--o2", required=True, help="Path to O2 .ll file")
    parser.add_argument("--o1", required=False, help="Path to O1 .ll file (optional)")
    parser.add_argument("--o3", required=False, help="Path to O3 .ll file (optional)")
    parser.add_argument("--out", required=True, help="Output findings JSON path")
    args = parser.parse_args()

    level_paths: dict[str, Path] = {
        "O0": Path(args.o0),
        "O2": Path(args.o2),
    }
    if args.o1:
        level_paths["O1"] = Path(args.o1)
    if args.o3:
        level_paths["O3"] = Path(args.o3)

    for p in level_paths.values():
        if not p.exists():
            print(f"check_llvm_patterns.py: IR file not found: {p}", file=sys.stderr)
            return 1

    level_to_ir: dict[str, tuple[str, str]] = {}
    try:
        for level, path in level_paths.items():
            level_to_ir[level] = (str(path), path.read_text(encoding="utf-8", errors="replace"))
    except OSError as e:
        print(f"check_llvm_patterns.py: failed to read IR: {e}", file=sys.stderr)
        return 1

    findings = analyze(level_to_ir)

    out_path = Path(args.out)
    out_path.parent.mkdir(parents=True, exist_ok=True)
    out_path.write_text(json.dumps(findings, indent=2), encoding="utf-8")

    print(f"check_llvm_patterns.py: {len(findings)} finding(s) written to {out_path}")
    return 0


if __name__ == "__main__":
    sys.exit(main())

Requirements and compatibility

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Source
trailofbits/skills · plugins/zeroize-audit/skills/zeroize-audit · commit e4dd0bb
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