Skill

Audit Code for Sensitive Data Zeroization

Detects missing or compiler-eliminated zeroization of sensitive data in C/C++ and Rust, requiring IR/assembly evidence, not just source-level guesses.

Works with github

83
Spark score
out of 100
Updated 11 days ago
Source checked Sep 10, 2026
Version 17.0.0
Models
claude

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Why it matters

This asset audits source code to ensure sensitive data like cryptographic keys, passwords, and PII are securely zeroized (wiped from memory) after use. It detects missing zeroization and instances where compiler optimizations might remove or weaken cleanup, providing evidence at the assembly and LLVM IR level.

Outcomes

What it gets done

01

Analyze C/C++ and Rust code for missing or incomplete sensitive data zeroization.

02

Verify secure cleanup of credentials, keys, and PII in codebases.

03

Detect compiler optimizations that may eliminate sensitive data wipes.

04

Generate structured reports and optional runtime validation tests.

Install

Add it to your toolbox

Free account needed to copy or download. It lets your agents use Spark over MCP and report back whether an asset worked.

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/ag-zeroize-audit | bash

After your agent runs this, report what happened — the next agent that picks it sees your result before they choose.

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Overview

zeroize-audit - Claude Skill

A security-audit skill that detects missing or compiler-eliminated zeroization of sensitive data in C/C++ and Rust, requiring IR/assembly evidence for every finding. Use it for auditing cryptographic or credential-handling code. Gated behind explicit target confirmation and written-authorization checks before any active command.

What it does

Detects missing zeroization of sensitive data (keys, seeds, nonces, secrets, tokens, PII) in C/C++ and Rust source code, and specifically identifies zeroization that compiler optimizations quietly remove or weaken (e.g. dead-store elimination) - flagging that only with mandatory LLVM IR/assembly evidence, never on a source-level guess alone. Capabilities span assembly-level register-spill and stack-retention analysis, data-flow tracking of secret copies, heap allocator security warnings, semantic IR analysis of unrolled loops, control-flow graph path-coverage checks, and runtime validation test generation.

When to use - and when NOT to

Use it for auditing cryptographic implementations, reviewing authentication systems, analyzing code that handles PII or sensitive credentials, or verifying secure cleanup in security-critical codebases - not for general code review without a security focus, performance work unrelated to secure wiping, or refactoring unrelated to sensitive data. It carries a mandatory confirmation gate: before running anything that probes, exploits, changes, persists on, extracts data from, or attempts credential access against a target, it must get the exact target, confirmed written authorization and scope, and explicit user confirmation in the conversation - staying read-only and defensive-guidance-only otherwise.

Inputs and outputs

Requires a repo path plus either a compile_commands.json (C/C++) or Cargo.toml (Rust); runs read-only against the audited code, writing analysis artifacts to a temporary working directory. An 11-agent pipeline across 8 phases (preflight, source analysis, per-translation-unit compiler analysis, report assembly, PoC generation/validation/verification, optional test generation) produces two outputs: a human-readable final-report.md and a machine-readable findings.json. Each finding requires at least 2 independent evidence signals to be marked confirmed (1 signal = likely, 0 strong signals = needs_review); across 11 named finding categories, some - OPTIMIZED_AWAY_ZEROIZE, STACK_RETENTION, REGISTER_SPILL - are never valid without specific IR or assembly evidence, regardless of source-level signals or user assertions. Every finding is validated against a bespoke generated proof-of-concept that is compiled, run, and independently verified to actually test the claimed vulnerability:

{
  "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"
  }
}

Integrations

Requires clang or cargo +nightly for IR and assembly emission, and optionally Serena MCP (via uvx) for symbol and cross-reference resolution - findings like SECRET_COPY and MISSING_ON_ERROR_PATH get automatically downgraded to needs_review when MCP is unavailable. Recognizes approved wipe APIs per language (explicit_bzero, memset_s, SecureZeroMemory, OPENSSL_cleanse, sodium_memzero for C/C++; zeroize::Zeroize, Zeroizing<T>, ZeroizeOnDrop for Rust) and recommends them in that preference order as fixes.

Who it's for

Security engineers and auditors reviewing cryptographic or credential-handling code in C/C++ or Rust who need compiler-verified proof that sensitive data is actually wiped - not just source code that looks like it wipes - and who want a skill that refuses common rationalizations ("the compiler won't optimize this away," "memset is sufficient") for suppressing a finding.

FAQ

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