Generalized from a long hardened-target engagement. Additions target the failure
modes that cost the most time and are not yet covered; nothing here is sample-specific.
New discipline
- SKILL.md: a third override rule -- deliver in the environment the request requires.
A root-only or live-instrumentation result can look like success while failing the
actual requirement (unrooted, installable, self-contained). Also adds two classify
questions: what form the deliverable must take, and which architecture/library is
actually executing.
- long-task-discipline.md: "the most expensive drift" -- a constraint table (privilege,
modification form, ABI, network, persistence, distribution), the checkpoint question,
and how to report a privileged workaround as a fallback rather than a deliverable.
Plus "bound every wait": timeouts on every command, budgets calibrated from
measurement so slow and hung are distinguishable, and sampling an observable you can
inspect instead of sleeping blind.
- environment.md: look at the screen instead of driving blind; which of the two screen
evidence kinds is trustworthy (an empty accessibility tree is common for
runtime-rendered UI, where the image is primary rather than a fallback); emulator
console control and adb recovery; preflight before every experiment block.
- native-and-so.md: what the device claims vs what the package manager chose vs what is
actually mapped; translation layers and their consequences for hooks and native
checks; fat-APK ABI selection.
- runtime-data.md: when the app rewrites your edit (server refresh vs local
regeneration), why chmod/chown cannot work because the app deletes and recreates the
file, and the immutable-attribute fix; decoding a value that only looks encrypted.
- framework-runtimes.md: string encoding traps (a UTF-8 scan of a UTF-16 snapshot
returns nothing and reads as "the strings were stripped"), and non-ASCII obfuscated
identifiers -- resolve by shape, not by name.
- pitfalls.md: P23 the fix lives in a file the app rewrites; P24 the artifact changed
but the wrong one is executing; P25 "search found nothing" treated as "not there".
New scripts (parameterized, path-agnostic, all with explicit timeouts)
- preflight.py environment check: device, root, ABI/translation, clock skew, leftover
proxy/forwards, dead device server, chosen ABI, free space
- lib_map.py what is actually mapped into a live process: path, base, architecture
from the ELF header, and whether it came from the APK or was
materialized at runtime
- blob_decode.py search (don't guess) the framing of a stored value, then re-encode the
edited payload with the same parameters
- snap.py bounded burst screenshots + control-tree capture, with a stall detector
and an explicit verdict on whether the tree is usable
All four were exercised against a live device while writing: preflight correctly
flags multi-device ambiguity and detected the ARM translation layer; lib_map read real
ELF headers and identified the translation shim; blob_decode round-tripped a
rotation+deflate+base64 blob at realistic size in ~0.2s; snap detected a stalled screen
across three hashes.
7.9 KiB
apk-reverse
An Agent Skill for Android APK reverse engineering, debloating, ad removal, surgical dex patching, repacking, and runtime/server analysis.
It is a skill, not a tutorial: it is written to be loaded by an agent (Claude Code,
Codex, or any harness that supports the Agent Skills format) while it works, so it is
organized for progressive disclosure — a short decision-oriented SKILL.md, detailed
references loaded only when a step needs them, and parameterized scripts you can run
directly.
What it is good at
- Deciding fast whether a request is even achievable client-side, instead of burning hours on a paywall that is enforced by a server.
- Deciding what form the deliverable must take before any work starts — an unrooted, self-contained artifact is a different problem from "make it work on this machine", and confusing the two is the most expensive drift in this domain.
- Choosing the safest patch layer for a given change, and avoiding the layers that break the app.
- Separating your own mistakes from the app's or the server's problems — a feature-scoped failure (login, registration, payment) is often a TLS/certificate issue on one code path, not a consequence of the patch you just built. Device state, a dead device server and clock drift masquerade the same way.
- Establishing which architecture and which library are actually executing, rather than trusting what the manifest ships or what the device claims.
- Working through packed/hardened targets: identifying the packer, unpacking, and turning a memory dump back into a patched, installable APK.
- Keeping a long task honest: a live record, graded conclusions, calibrated timeouts, and bounded waits, so progress is not lost and the same mistake is not made twice.
- Avoiding the specific mistakes that produce an APK that builds perfectly and dies at runtime.
Structure
SKILL.md decision tree, workflow, hard constraints, indexes
references/ loaded on demand, one topic each
recon.md identify packer, SDKs, code location, tamper checks; unpacking
packers.md hardened targets: rejection signals, measuring the validation
boundary with single-variable tests, choosing a native host
framework-runtimes.md Flutter / React Native / Unity: which layer owns the UI, and how to
find logic when there are no symbols (string encoding traps)
native-and-so.md .so hosts, DT_NEEDED vs JNI_OnLoad, relocation limits,
relocation-free bootstrapping, replacing Java methods natively,
and which ABI/library is *actually loaded and executing*
long-task-discipline.md live record, conclusion grading, drift control, timeout and
wait calibration, deliverable-form drift, handover
ad-removal.md ad taxonomy, wrapper mapping, callback trap, global gates, verification
membership-and-limits.md server vs client authority; what is and is not patchable
server-api.md probe an app's API; prove who owns the gate
tls-and-cert.md feature-scoped network failures: expired certs, dual trust chains
third-party-builds.md auditing a "cracked"/"modded" APK before trusting it
dex-patching.md patch-layer table + dexlib2 technique in depth
repack-and-sign.md repack rules, unpack-and-repack, signing, post-install hazards
runtime-data.md DataStore / SharedPreferences / SQLite / protobuf; when the app
rewrites your edit, and decoding a value that looks encrypted
dynamic-frida.md Frida setup, version pinning, the four-layer probe, hook strategy
environment.md device/emulator setup, root, ADB, offline devices, log signals,
emulator console control and recovery, preflight, look-at-the-screen
verification.md the claim ladder; what "done" means
pitfalls.md the failure catalogue -- read before building
scripts/ parameterized, path-agnostic
smtool.py baksmali/smali wrapper with a configurable classpath
dexpatch/ dexlib2 method-level surgical rewriter (preferred tool)
patch_smali.py method-body replacement in a smali tree
dex_strpatch.py byte-level string patch with a string_ids ordering guard
dex_classdiff.py prove a dex edit was surgical
dex_strings.py strings/URLs/SDK markers without a decompiler
find_refs.py count callers of a method before patching it
repack.py rebuild APK, strip only signatures, sign, verify
devsh.py quoting-safe ADB shell helper
usb_net_proxy.py give an offline device network over USB
datastore_inject.py encode/inject AndroidX DataStore preferences safely
probe_api.py probe an HTTP API with the right headers
grab_crash.py recover stacks hidden by a crash-reporter SDK
install_test.py install + launch health check with logcat signal scan
frida_probe.js four-layer runtime probe (app net layer + OkHttp + java.net + exceptions)
run_probe.py inject the probe, stream it to a log file, stay resident
tls_check.py strict certificate check for one or more hosts
preflight.py environment check before every experiment block (device, root,
ABI/translation, clock skew, leftover proxy/forwards, dead server)
lib_map.py what is *actually mapped* into a live process: per-library path,
base, architecture, and whether it came from the APK or was
materialized at runtime
blob_decode.py search, don't guess, the framing of a stored value
(base64/hex x rotation x deflate); re-encode the edited payload
snap.py bounded burst screenshots + control-tree capture with a stall
detector, and a verdict on whether the tree is usable at all
Install
Drop this directory where your agent finds skills, e.g.:
<skills-dir>/apk-reverse/SKILL.md
The agent loads SKILL.md when a task matches its description, and pulls in
references/* only as needed. No global state, no machine-specific paths.
Requirements
Nothing is mandatory; each script checks what it needs.
| Tool | Used for |
|---|---|
| Python 3.9+ | all scripts |
baksmali / smali + dexlib2 jars |
disassembly, assembly, surgical patching |
JDK (javac, java) |
building/running the dexlib2 patcher |
Android SDK build-tools (aapt, zipalign, apksigner) |
manifest info, alignment, signing |
uber-apk-signer (optional) |
one-step align + sign |
| ADB | device work |
| Frida (host package + matching on-device server) | dynamic analysis |
| a rooted device or emulator | anything beyond static analysis |
Read this first
references/pitfalls.md. It is the most valuable file here — every entry is a failure
that produced a broken artifact while looking completely healthy.
The three that hurt most:
- Stripping the whole
META-INF/during a repack deletes ServiceLoader registrations and the app dies at startup with an error that names an unrelated library. - Patching a byte-level string without preserving
string_idsordering gets the whole dex rejected, while checksums and signatures verify perfectly. - Rebuilding a dex with a whole-tree smali round-trip damages R8 output invisibly — class tables compare clean, and it only blows up at runtime.
Scope
Built for working on your own applications, on samples you are authorized to analyze, and in CTF/competition sandboxes. It contains no vendored third-party binaries and no target-specific data.