Writes and executes IDAPython scripts via IDA Domain API to analyze binaries, extract functions/strings/xrefs, decompile code, and automate IDA Pro (.idb/.i64) tasks.
From reverse-engineering-with-code-eval-and-ida-domainnpx claudepluginhub hexrayssa/ida-claude-plugins --plugin reverse-engineering-with-code-eval-and-ida-domainThis skill uses the workspace's default tool permissions.
API_REFERENCE.mdpyproject.tomlrun.pysetup.pyGuides Next.js Cache Components and Partial Prerendering (PPR) with cacheComponents enabled. Implements 'use cache', cacheLife(), cacheTag(), revalidateTag(), static/dynamic optimization, and cache debugging.
Migrates code, prompts, and API calls from Claude Sonnet 4.0/4.5 or Opus 4.1 to Opus 4.5, updating model strings on Anthropic, AWS, GCP, Azure platforms.
Orchestrates subagents to execute phased plans: deploys for implementation, verification, anti-pattern checks, code quality review, and commits only after passing checks.
IMPORTANT - Path Resolution:
This skill can be installed in different locations. Before executing any commands, determine the skill directory based
on where you loaded this SKILL.md file, and use that path in all commands below. Replace $SKILL_DIR with the actual
discovered path.
Common installation paths:
<project>/.claude/skills/ida-domain-scripting~/.claude/skills/ida-domain-scriptingGeneral-purpose binary analysis skill. I'll write custom IDAPython code for any reverse engineering task you request and execute it via the universal executor.
CRITICAL WORKFLOW - Follow these steps in order:
Create a work dir in /tmp with timestamp - NEVER write scripts to skill directory; always create a workdir
/tmp/ida-domain-YYYYMMDD_HHMMSS_ffffff-<name> with microseconds for uniqueness (e.g.,
/tmp/ida-domain-20260109_143052_847291-list-functions). Generate timestamp with: datetime.now(). strftime ('%Y%m%d_%H%M%S_%f').
This will always be referenced as <work_dir>
Check API_REFERENCE.md exists - Always check that $SKILL_DIR/API_REFERENCE.md exists. Inform the user to run the bootstrap if not.
Execute from skill directory - Always run:
cd $SKILL_DIR && uv run python run.py <work_dir>/script.py -f <binary>
Ask before saving - Scripts that modify the database require explicit user confirmation before using --save
<work_dir>/script.py (timestamped with microseconds for parallel execution)cd $SKILL_DIR && uv run python run.py <work_dir>/script.py -f <binary>cd $SKILL_DIR && uv run python setup.py
This clones ida-domain from GitHub and installs dependencies. Only needed once.
Using a specific version:
uv run python setup.py --ref v0.1.0 # Specific release
uv run python setup.py --ref main # Bleeding edge
Requirements:
Step 1: Write analysis script to <work_dir>
# <work_dir>/script.py
for func in db.functions:
name = db.functions.get_name(func)
print(f"{name}: 0x{func.start_ea:08X}")
Step 2: Execute from skill directory
cd $SKILL_DIR && uv run python run.py <work_dir>/script.py -f /path/to/binary
Step 3: Review results
Scripts are auto-wrapped with Database.open() boilerplate. The db variable is available for accessing all entities.
# <work_dir>/script.py
for func in db.functions:
name = db.functions.get_name(func)
size = func.end_ea - func.start_ea
print(f"{name}: 0x{func.start_ea:08X} - 0x{func.end_ea:08X} ({size} bytes)")
# <work_dir>/script.py
func = db.functions.get_function_by_name("main")
if func:
print(f"Found main at 0x{func.start_ea:08X}")
# Get callers
callers = db.functions.get_callers(func)
print(f"Called by {len(callers)} functions:")
for caller in callers:
print(f" - {db.functions.get_name(caller)}")
else:
print("main not found")
# <work_dir>/script.py
import re
# Find all strings
for s in db.strings:
print(f"0x{s.address:08X}: {s}")
# Find URLs
url_pattern = re.compile(r"https?://[\w./]+", re.IGNORECASE)
for s in db.strings:
try:
content = str(s)
if url_pattern.search(content):
print(f"URL found: {content}")
except:
pass
# <work_dir>/script.py
# Get xrefs TO an address
target = 0x00401000
print(f"References TO 0x{target:08X}:")
for xref in db.xrefs.to_ea(target):
print(f" From 0x{xref.from_ea:08X} (type: {xref.type.name})")
# Get xrefs FROM an address
print(f"References FROM 0x{target:08X}:")
for xref in db.xrefs.from_ea(target):
print(f" To 0x{xref.to_ea:08X} (type: {xref.type.name})")
# <work_dir>/script.py
func = db.functions.get_function_by_name("main")
if func:
try:
lines = db.functions.get_pseudocode(func)
print("\n".join(lines))
except RuntimeError as e:
print(f"Decompilation failed: {e}")
# <work_dir>/script.py
complex_funcs = []
for func in db.functions:
flowchart = db.functions.get_flowchart(func)
if flowchart:
block_count = len(flowchart)
edge_count = sum(b.count_successors() for b in flowchart)
cyclomatic = edge_count - block_count + 2
if cyclomatic > 10:
name = db.functions.get_name(func)
complex_funcs.append((name, func.start_ea, cyclomatic))
complex_funcs.sort(key=lambda x: x[2], reverse=True)
print("Most complex functions:")
for name, addr, cc in complex_funcs[:10]:
print(f" {name}: complexity={cc} at 0x{addr:08X}")
# <work_dir>/script.py
# Search for NOP sled
pattern = b"\x90\x90\x90\x90"
results = db.bytes.find_binary_sequence(pattern)
for addr in results:
print(f"Found NOP sled at 0x{addr:08X}")
# Search for x64 function prologue
prologue = b"\x55\x48\x89\xE5" # push rbp; mov rbp, rsp
for addr in db.bytes.find_binary_sequence(prologue):
print(f"Prologue at 0x{addr:08X}")
# <work_dir>/script.py
import json
from pathlib import Path
functions = []
for func in db.functions:
name = db.functions.get_name(func)
functions.append({
"name": name,
"start": f"0x{func.start_ea:08X}",
"end": f"0x{func.end_ea:08X}",
"size": func.end_ea - func.start_ea,
})
output = {"module": db.module, "functions": functions}
Path("/tmp/functions.json").write_text(json.dumps(output, indent=2))
print(f"Exported {len(functions)} functions to /tmp/functions.json")
For quick one-off tasks, you can execute code inline without creating files:
# Quick function count
cd $SKILL_DIR && uv run python run.py -c "print(f'Functions: {len(db.functions)}')" -f binary
# Get binary info
cd $SKILL_DIR && uv run python run.py -c "print(f'{db.module}: {db.architecture} {db.bitness}-bit')" -f binary
When to use inline vs files:
For comprehensive IDA Domain API documentation, see API_REFERENCE.md:
--save only when modifications should persist (and ask user first!)--timeout 0 for long-running analysis--no-wrap when your script already has Database.open()get_function_by_name() return None if not foundWhen encountering errors:
Check the ida-domain source code first by searching for the method signature in $SKILL_DIR/ida-domain/ida_domain/. The
API may differ from what's documented or expected.
Virtual environment not found:
cd $SKILL_DIR && uv run python setup.py
IDA SDK fails to load / IDADIR error:
export IDADIR=/path/to/ida
Script timeout:
cd $SKILL_DIR && uv run python run.py --timeout 3600 ... # 1 hour
cd $SKILL_DIR && uv run python run.py --timeout 0 ... # No timeout
AttributeError: 'Xrefs' has no attribute 'get_xrefs_to':
Use db.xrefs.to_ea(addr) not db.xrefs.get_xrefs_to(addr)
AttributeError on func_t object:
Call methods on db.functions, not on the func object:
# Wrong: func.get_callers()
# Right: db.functions.get_callers(func)
UnicodeDecodeError when reading strings:
for s in db.strings:
try:
content = str(s)
except:
continue # Skip problematic strings
User: "How many functions are in this binary?"
Claude: I'll count the functions. Let me analyze the binary...
[Writes: <work_dir>/script.py]
[Runs: cd $SKILL_DIR && uv run python run.py <work_dir>/script.py -f binary]
[Output: Functions: 250]
The binary contains 250 functions.
User: "Find all functions that call malloc"
Claude: I'll find all callers of malloc...
[Writes: <work_dir>/script.py]
[Runs: cd $SKILL_DIR && uv run python run.py <work_dir>/script.py -f binary]
[Output: malloc called by 15 functions: sub_401000, sub_402000, ...]
Found 15 functions that call malloc:
- sub_401000 at 0x00401000
- sub_402000 at 0x00402000
...
User: "Decompile the main function and save it"
Claude: I'll decompile main and save the output...
[Writes: <work_dir>/script.py]
[Runs: cd $SKILL_DIR && uv run python run.py <work_dir>/script.py -f binary]
[Output: Saved to /tmp/main.c]
Done! The decompiled code is saved to /tmp/main.c