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dwarf-expert

Analyzes DWARF debug information in compiled binaries

Install / Use

npx skills add trailofbits/skills --skill dwarf-expert

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

81/100

Supported Platforms

Universal

Tags

Our assessment of dwarf-expert

dwarf-expert scores 81/100 on our quality scale, 329th of 503 Content & Media skills we index.

Its SKILL.md is 5.8 KB long, split into 7 sections and no code examples: a solid amount of guidance for an agent.

With 7,225 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
26/30
Structure
11/20
Description
8/15
Adoption
16/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 3 days ago, so dwarf-expert is actively maintained.
  • It is released under the CC-BY-SA-4.0 license; check its terms before commercial use.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

dwarf-expert compared with similar skills

All 4 of these similar skills score higher than dwarf-expert; compare them before choosing.

SkillScoreStarsUpdatedFormat
dwarf-expert (this skill)by trailofbits817.2k3d agoSKILL.md
siyuanby siyuan-note10046.5ktodayMCP Server
algorithmic-artby anthropics100177.9k4d agoSKILL.md
pptxby anthropics100177.9k4d agoSKILL.md
designby nextlevelbuilder100130.2k5d agoSKILL.md

Frequently asked questions

How do I install dwarf-expert?
Run npx skills add trailofbits/skills --skill dwarf-expert. The install tabs above show the steps for each supported agent.
Which AI agents does dwarf-expert work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is dwarf-expert safe to use?
It is CC-BY-SA-4.0-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is dwarf-expert still maintained?
The repository was last updated 3 days ago, so dwarf-expert is actively maintained.

name: dwarf-expert description: Analyzes DWARF debug information in compiled binaries. Use when inspecting .debug_* sections, DIE trees, or DW_TAG_/DW_AT_ entries with dwarfdump/llvm-dwarfdump or readelf, verifying debug info with llvm-dwarfdump --verify, answering DWARF standard questions, or writing code that parses DWARF (libdwarf, pyelftools, gimli). effort: medium allowed-tools: Read Write Edit Bash Grep Glob WebSearch WebFetch

DWARF Expert

Expertise for DWARF debug info: parsing and searching it, verifying its integrity, answering questions about the standard, and writing code that consumes it. Out of scope: runtime debugging (use gdb/lldb), reverse engineering beyond the DWARF sections (use Ghidra/IDA), and compiler-specific DWARF generation bugs.

Authoritative Sources

When precision matters, look standard details up instead of answering from memory:

  1. dwarfstd.org — the official specification. Web-search specific sections, e.g. "DWARF5 DW_TAG_subprogram attributes site:dwarfstd.org".
  2. LLVM — llvm/lib/DebugInfo/DWARF/ is a reliable reference implementation: DWARFDie.cpp (DIE and attribute access), DWARFUnit.cpp (compilation units), DWARFDebugLine.cpp (line tables), DWARFVerifier.cpp (validation).
  3. libdwarf — the reference C implementation at github.com/davea42/libdwarf-code.

Parsing and Searching with dwarfdump

Prefer dwarfdump over readelf for DWARF-specific work. Two implementations exist — libdwarf's dwarfdump and LLVM's llvm-dwarfdump — with different options, and a bare dwarfdump command may be either: check dwarfdump --version first. The options below are LLVM's.

On macOS, linked Mach-O executables do not carry DWARF: it stays in the .o files until dsymutil collects it into a .dSYM bundle. Point dwarfdump at the dSYM (or the object files), not the executable. pyelftools is ELF-only — for Mach-O scripted work, stay with the LLVM tools.

  • --all: dump every DWARF section; --debug-info, --debug-line, etc. dump one
  • --show-children [--recurse-depth=<n>]: include child DIEs when printing selected entries — parameters, locals, and struct members are children of function and type DIEs
  • --show-parents [--parent-recurse-depth=<n>]: include parent DIEs
  • --show-form: print attribute form types, for when encoding details matter
  • --find=<name>: exact-name lookup via the accelerator tables — fast but not exhaustive; fall back to --name when it misses
  • --name=<pattern> [--ignore-case] [--regex]: exhaustive DIE-name search
  • --lookup=<address>: find the DIE covering an address
  • --verbose: print low-level encoding detail

Searching DIEs

Escalate through these strategies as the query grows more complex:

  1. Name or address match: --find, then --name; --lookup for addresses.
  2. Attribute or type queries (e.g. all parameters of type float *): dump and filter. grep -B pulls in the header line carrying each DIE's offset: llvm-dwarfdump file | grep -B 5 "float \*" | grep DW_TAG_formal_parameter, then print each DIE at its offset with --debug-info=<offset> --show-children (--lookup takes a program address, not a DIE offset).
  3. Multi-attribute or structural queries: when grep pipelines turn brittle, write a Python script using pyelftools instead.

Verifying DWARF Integrity

  • llvm-dwarfdump --verify <binary>: structural checks (unit chains, DIE relationships, address ranges). --error-display=<quiet|summary|details|full> controls detail; --verify-json=<path> writes a machine-readable error summary; --quiet for exit-code-only checks.
  • llvm-dwarfdump --statistics <binary>: debug-info quality metrics as JSON — compare across compiler versions or optimization levels to catch regressions.

Verify after producing DWARF (compilers, binary rewriters), when a debugger misbehaves on a binary, and when developing DWARF tooling against known-good files.

When a current-generation compiler emitted an old DWARF version, the build explicitly passed -gdwarf-N — modern gcc and clang default to v4/v5, so check the build system rather than assuming a toolchain default. GCC embeds its flags in DW_AT_producer, so the pin is often readable right there; clang's producer string carries no flags. Old versions remain common in the wild and read the same way apart from surface forms: in v2 output, member offsets appear as location expressions (DW_OP_plus_uconst) and linkage names as DW_AT_MIPS_linkage_name.

readelf

For general ELF structure, or when dwarfdump is unavailable:

  • --debug-dump=<section>: dump a DWARF section (info, line, ...)
  • --dwarf-depth=<n> / --dwarf-start=<n>: limit DIE depth / start offset

Writing Code That Parses DWARF

Prefer an existing library over parsing by hand:

| Library | Language | Notes | |---------|----------|-------| | libdwarf | C/C++ | github.com/davea42/libdwarf-code — low-level; used to implement dwarfdump | | pyelftools | Python | github.com/eliben/pyelftools — also parses ELF in general | | gimli | Rust | github.com/gimli-rs/gimli — pair with object to load container files | | debug/dwarf | Go | standard library | | LibObjectFile | .NET | github.com/xoofx/LibObjectFile — also handles ELF/PE object files |

Default to Python with pyelftools for one-off scripts unless the task dictates otherwise.

DWARF-specific pitfalls to handle — and to check for when reviewing DWARF code:

  • Attributes are optional: a DIE may omit DW_AT_name, DW_AT_type, ranges, etc.
  • Attribute indirection: a DIE's attributes may live on the DIE referenced by its DW_AT_abstract_origin (inlined instances) or DW_AT_specification (out-of-line definitions) — resolve the chain before concluding data is absent.
  • Type chains: qualifiers and modifiers (DW_TAG_const_type, DW_TAG_pointer_type, ...) wrap the underlying type; walk DW_AT_type links to reach the base type.

Related Skills

View on GitHub
GitHub Stars7.2k
CategoryContent
Updated3d ago
Forks615

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions