pydepgate 0.3.1

Lightweight Python runner that interdicts suspicious startup behavior.

pydepgate

A lightweight Python runner that interdicts suspicious startup behavior.

pydepgate inspects Python packages and environments for code that executes silently at interpreter startup. This was the attack class used by the March 2026 LiteLLM supply-chain compromise and catalogued as MITRE ATT&CK T1546.018.

Recently Added

Recursive payload decoding with encrypted-archive output

--decode-payload-depth=N runs a recursive re-scan over decoded payloads. When the peek enricher's unwrap chain produces Python source, that source is fed back through the engine, and any payload-bearing findings inside it are themselves decoded. This catches the multi-layer attack shape used by LiteLLM 1.82.8: a base64 outer payload whose decoded source contains a second base64 payload which decodes to the actual exfiltration code.

Output goes to a directory chosen with --decode-location (default ./decoded/), with files named {STATUS}_{timestamp}_{target}{ext} where STATUS is FINDINGS or NOFINDINGS, timestamp is UTC in YYYY-MM-DD_HH-MM-SS format, and target is the sanitized artifact basename. This convention preserves run history and sorts chronologically by filename.

--decode-iocs={off,hashes,full} controls whether IOC data and decoded source are extracted alongside the report. Mode full produces an encrypted ZIP archive (default password infected, the malware-research convention) containing the report, decoded source dumps, and IOC hash records, plus a plaintext IOC sidecar next to the archive for grep-friendly hash extraction.

--min-severity flows into the decoded-payload report as a presentation filter. The decode pass itself runs over every payload-bearing finding regardless of severity, because a low-severity outer finding can decode to a critical inner one. The filter then prunes the resulting tree, with a "keep for context" rule: a node stays if its own severity meets the threshold OR if any of its descendants do, so chains aren't broken when only the inner finding is severe.

See the Payload Decoding section below for the full flag table, output layout, and end-to-end examples.

Tab completion works!

usage: pydepgate completions [-h] {bash,zsh,fish}

Print a shell completion script to stdout. Running this command alone does NOT install completion; you have to do something with the output.

Quickest install (bash, current shell only):
  eval "$(pydepgate completions bash)"

Persistent install (bash, all future shells):
  pydepgate completions bash >> ~/.bashrc

Persistent install (zsh):
  pydepgate completions zsh >> ~/.zshrc

Persistent install (fish):
  pydepgate completions fish > ~/.config/fish/completions/pydepgate.fish

After installing, open a new shell or re-source your rc file, then test with:
  pydepgate <TAB><TAB>

When run interactively (output to a terminal rather than redirected), this command also prints install instructions to stderr.

positional arguments:
  {bash,zsh,fish}  Target shell. Supported: bash, zsh, fish.

Status

Static analysis is functional end-to-end.

pydepgate can statically analyze wheels, sdists, installed packages, and single loose files for the patterns used in real-world Python supply-chain attacks. The detection covers payload encoding, dynamic code execution, string obfuscation, suspicious stdlib usage, and a broad code-density layer that catches obfuscation, Unicode trickery, and machine-generated identifier patterns.

What works today:

• Static analysis of .whl files, sdists (.tar.gz/.tgz/etc.), installed packages by name, and individual loose files via --single.
• Five production analyzers: encoding_abuse, dynamic_execution, string_ops, suspicious_stdlib, and code_density.
• Defense in depth on real attack shapes. The LiteLLM 1.82.8 .pth payload, for example, fires across four analyzers simultaneously (ENC001, DYN002, DENS010, DENS011) so an attacker has to evade every layer to get past the scanner.
• A rules engine that promotes severity based on file kind and signal context, fully data-driven via TOML or JSON. The default rule set includes 32 rules dedicated to density-layer signals alone.
• A safe partial evaluator that resolves obfuscated string expressions without executing user code.
• An optional payload-peek enricher (--peek) that safely partial-decodes large encoded literals so you can see what's inside without executing anything. Handles base64, hex, zlib, gzip, bzip2, and lzma chains up to a configurable depth, classifies the terminal payload, scans for high-signal indicator strings, and emits ENC002 when the unwrap chain is nested. Pickle data is detected but never deserialized; decompression bombs are bounded by an in-flight byte budget. Tunable via --peek-depth, --peek-budget, --peek-min-length, and --peek-chain (verbose per-layer hex dumps).
• An SSH-randomart-style finding-distribution map rendered inline with human-readable scan output, showing where in a file the findings cluster and at what severity.
• Command-line interface with scan (including --single for iteration on individual files) and explain subcommands, environment variable support, configurable severity thresholds, and CI-friendly output modes.
• Three output formats: human-readable terminal, JSON (schema v2), and a stub for SARIF (planned for v0.4).
• Explicit color control via --color={auto,always,never} (or PYDEPGATE_COLOR), with --no-color preserved as an alias. --color=always forces ANSI codes through pipes for less -R and terminal-aware log viewers.
• Pre-commit hook integration. Drop pydepgate into any Python project's .pre-commit-config.yaml to catch startup-vector patterns at commit time. Two hook ids: pydepgate for .py files (defaults to --min-severity high so informational findings don't block commits) and pydepgate-pth for .pth files (no severity filter; .pth files have no legitimate use for the patterns pydepgate detects).
• Official Docker image at ghcr.io/nuclear-treestump/pydepgate. Multi-stage Alpine build under 50 MB, runs as non-root (uid 1000), published for linux/amd64 and linux/arm64, tagged per release. Composes with any Python build pipeline that produces a wheel.

What is in active development:

• The comment_analysis analyzer.
• Runtime interdiction (exec mode).
• Environment auditing (preflight mode).
• Aliased import resolution (from subprocess import Popen as P).
• A pip-wrapper / transitive-dependency audit subcommand.
• SARIF 2.1.0 output for GitHub code scanning and similar consumers.

Available on PyPI as pydepgate.

The problem

Python's interpreter runs several kinds of code automatically at startup, before any user script executes:

• .pth files in site-packages/. Any line beginning with import is passed to exec() by site.py during interpreter initialization.
• sitecustomize.py and usercustomize.py. Imported automatically if present.
• __init__.py top-level code in any imported package.
• setup.py. Executed during pip install for source distributions.
• Console-script entry points. Generated and executed by pip install.

Each of these is a legitimate Python feature. Each has been used in real-world supply-chain attacks. Existing Python security tooling (pip-audit, safety, bandit) does not inspect these startup vectors. The .pth vector in particular has been acknowledged as a security gap in CPython issue #113659 but has no patch.

Installation

pip install pydepgate

Requires Python 3.11 or later. No third-party runtime dependencies.

Usage

Scan a wheel:

pydepgate scan some-package-1.0.0-py3-none-any.whl

Scan a source distribution:

pydepgate scan some-package-1.0.0.tar.gz

Scan an installed package by name:

pydepgate scan litellm

Scan a single loose file (useful for iterating on test fixtures, ad-hoc inspection of a suspicious file, or reproducing a finding without restructuring the file into a package):

pydepgate scan --single suspicious_module.py
pydepgate scan --single fixture.pth
pydepgate scan --single garbage.py --as init_py

--single bypasses wheel/sdist/installed-package dispatch and analyzes the file directly. The file kind is auto-detected from the filename: .pth files are treated as pth; files named setup.py, __init__.py, sitecustomize.py, or usercustomize.py are classified as their natural kind; anything else defaults to setup_py (the most permissive context, ideal for surfacing every signal at realistic attack-shape severity). Override with --as: setup_py / init_py / pth / sitecustomize / usercustomize.

Explain what a signal means and what triggers it:

pydepgate explain STDLIB001
pydepgate explain DENS010
pydepgate explain --rule litellm-pth-stdlib
pydepgate explain --list

In CI, use --ci for compact JSON output and proper exit codes:

pydepgate --ci scan some-package.whl

Filter findings by severity:

pydepgate scan some-package.whl --min-severity high

Apply a custom rules file:

pydepgate scan some-package.whl --rules-file company-rules.gate

Scan an entire library archive:

Recommend using --min-severity as this is noisy by design.

pydepgate scan --deep somefile.whl

Decode payloads recursively into a directory:

pydepgate scan --deep some-package.whl --peek \
    --decode-payload-depth=3 \
    --decode-iocs=full \
    --decode-location ./forensics \
    --decode-archive-password investigation

This produces an encrypted archive at ./forensics/FINDINGS_<timestamp>_some-package.whl.zip and a plaintext IOC sidecar at ./forensics/FINDINGS_<timestamp>_some-package.whl.iocs.txt. The archive contents extract into a subdirectory matching the artifact name. See the Payload Decoding section for full details.

Payload peek

Some malware compresses or base64-encodes its payload to slip past naive string-match scanners. The payload-peek enricher attempts safe partial decoding of large encoded literals so you can see what's actually inside a flagged blob without ever executing it. Off by default; opt in with --peek.

Flag	Env var	Default	Notes
--peek	PYDEPGATE_PEEK	off	Enable the enricher. Runs a bounded decode pass over hint-tagged signals.
--peek-depth N	PYDEPGATE_PEEK_DEPTH	3	Max unwrap layers. Floor 1, ceiling 10.
--peek-budget BYTES	PYDEPGATE_PEEK_BUDGET	524288 (512 KB)	Cumulative output cap across all layers. Floor 1024.
--peek-chain	PYDEPGATE_PEEK_CHAIN	off	Verbose per-layer breakdown with xxd-style hex dump in human output.
--peek-min-length BYTES	PYDEPGATE_PEEK_MIN_LENGTH	1024	Minimum literal size before unwrap is attempted. Floor 16.

These behave as global flags accepted before or after the subcommand:

pydepgate --peek scan litellm-1.82.8-py3-none-any.whl
pydepgate scan litellm-1.82.8-py3-none-any.whl --peek --peek-chain

Scanning the LiteLLM 1.82.8 wheel with --peek surfaces the embedded payload directly:

[CRITICAL] DENS010 (code_density)
  in litellm/proxy/proxy_server.py:130:14
  string literal at line 130 has Shannon entropy 5.61 bits/char (length 34460)
  decoded chain: base64 -> python_source (1 layer, 25.2 KB)
  indicators: subprocess, base64.b64decode

The same decoded block lands in JSON output under findings[*].context.decoded regardless of --peek-chain, with the full chain, terminal classification, indicators list, and a hex-encoded preview of the unwrapped bytes. See docs/json_schema_v2.md for the field reference.

Safety guarantees

The peek loop is strictly read-only. Three specific guarantees worth stating explicitly:

Pickle is detected, never deserialized. When the unwrap loop hits a Python pickle stream as a terminal layer, it sets pickle_warning: true in the decoded block and stops. pickle.loads() on attacker-controlled bytes is code execution by design, that is the bug being analyzed, not a tool action. Inspect such payloads with pickletools.dis() (which walks the opcode stream without executing it) in an isolated environment.

Decompression bombs are bounded. Cumulative output across all unwrap layers is capped by --peek-budget. A 2 KB zlib stream that would expand to 2 GB trips the cap at 512 KB (default), records unwrap_status: exhausted_budget, and stops. The cap is enforced in-flight via incremental decompressobj.decompress(data, max_length=N) calls, bytes that exceed the budget are never materialized.

ENC002 fires on nested chains. When the unwrap chain reaches depth 2 or exhausts --peek-depth with more transformations still possible, the enricher emits an ENC002 signal carrying the decoded block plus a chain summary. A single base64 layer is unremarkable, it's the lingua franca of certificates, tokens, and config blobs. Stacked layers (base64 → zlib → python_source) are intent. Default severities for ENC002 vary by file kind and unwrap status; see pydepgate.rules.defaults for the full table.

Exit codes

• 0 Clean. No findings (or no findings above --min-severity).
• 1 Findings present, but none HIGH or CRITICAL.
• 2 At least one HIGH or CRITICAL finding.
• 3 Tool error. pydepgate could not complete the scan.

These are stable as part of the v0.1+ contract.

Environment variables

All flags can be set via environment variables. Explicit flags override environment values.

Variable	Equivalent flag
PYDEPGATE_CI	--ci
PYDEPGATE_FORMAT	--format
PYDEPGATE_NO_COLOR (or NO_COLOR)	--no-color
PYDEPGATE_MIN_SEVERITY	--min-severity
PYDEPGATE_STRICT_EXIT	--strict-exit
PYDEPGATE_RULES_FILE	--rules-file
PYDEPGATE_PEEK	--peek
PYDEPGATE_PEEK_DEPTH	--peek-depth
PYDEPGATE_PEEK_BUDGET	--peek-budget
PYDEPGATE_PEEK_CHAIN	--peek-chain
PYDEPGATE_PEEK_MIN_LENGTH	--peek-min-length
PYDEPGATE_DECODE_PAYLOAD_DEPTH	--decode-payload-depth
PYDEPGATE_DECODE_LOCATION	--decode-location
PYDEPGATE_DECODE_FORMAT	--decode-format
PYDEPGATE_DECODE_IOCS	--decode-iocs
PYDEPGATE_DECODE_ARCHIVE_PASSWORD	--decode-archive-password

--decode-archive-stored deliberately has no environment variable; it is a per-investigation choice (use STORED when byte-verifiable archive contents matter for that specific investigation) rather than a persistent preference.

What pydepgate detects

The current analyzer set covers five major classes of suspicious behavior in startup vectors:

Encoding abuse (ENC001, ENC002). Patterns where encoded content is decoded and executed in a single chain, e.g. exec(base64.b64decode(payload)). Catches base64, hex, codec-based, zlib, bz2, lzma, and gzip variants. With --peek enabled, ENC002 also fires when the partial-decoder unwrap loop reaches 2+ chain layers or exhausts its configured depth, strong evidence that a literal is intentionally obfuscated rather than a benign encoded blob.

Dynamic execution (DYN001-007). Direct calls to exec, eval, compile, or __import__; access to exec primitives via getattr, globals(), locals(), vars(), or __builtins__ subscripts; compile-then-exec across the file; and aliased call shapes that catch e = exec; e(...) evasions.

String obfuscation (STR001-004). Obfuscated string expressions that resolve to the names of exec primitives, dangerous stdlib functions, or sensitive module names. Uses a safe partial evaluator that statically computes what string an expression would produce, without executing user code. Catches:

• Concatenation: 'ev' + 'al'
• Character codes: chr(101) + chr(118) + chr(97) + chr(108)
• Slicing: 'lave'[::-1]
• str.join of literal pieces: ''.join(['e','v','a','l'])
• bytes.fromhex('6576616c').decode()
• f-string assembly with literal interpolation
• Single-assignment variables containing obfuscated values

Suspicious stdlib usage (STDLIB001-003). Calls to stdlib functions that are highly unusual in startup vectors:

• STDLIB001: process spawn (os.system, subprocess.Popen, subprocess.run, os.exec*, etc.)
• STDLIB002: network operations (urllib.request.urlopen, socket.socket, http.client, etc.)
• STDLIB003: native code loading (ctypes.CDLL, ctypes.WinDLL, etc.)

Confidence is HIGH by default. The rules engine promotes these to CRITICAL when they appear in setup.py or in a .pth file (where they have no legitimate business existing). This is the rule that fires on LiteLLM 1.82.8.

The "harder they hide it the stronger the signal" model is realized through operation counting: an expression that required many obfuscation operations to assemble a sensitive name is treated as more confidently malicious than one that required few.

Code density (DENS001-051). A broad layer that catches the things obfuscated code looks like even when no single primitive call is suspicious on its own. Thirteen distinct signals across five sublayers:

Lexical (line-shape):

• DENS001: single-line token compression (minification or bundler-mimicry shapes)
• DENS002: semicolon chaining of multiple statements on one line

String content:

• DENS010: high-entropy string literals (Shannon entropy consistent with base64, compressed, or encrypted content)
• DENS011: literals using only base64-alphabet characters, even without an accompanying decode call

Identifier shape:

• DENS020: low-vowel-ratio identifiers (machine-generated or deliberately mangled names like _xkjwbq)
• DENS021: confusable single-character identifiers (l, O, I)

Unicode:

• DENS030: invisible Unicode characters in source (zero-width spaces, RTL overrides; the Trojan Source class catalogued as CVE-2021-42574)
• DENS031: Unicode homoglyphs in identifiers (Cyrillic and Greek lookalikes used to evade string-match scanners)

Structural:

• DENS040: AST depth disproportionate to line count (compression hidden inside expression trees)
• DENS041: deeply nested lambdas or comprehensions (functional-style obfuscation)
• DENS042: large byte-range integer arrays (122-element lists of 0-255 ints, the shellcode-staging shape)

Docstring:

• DENS050: high-entropy docstrings (the docstring-as-payload smuggling pattern)
• DENS051: dynamic __doc__ reference passed to a callable (the runtime decode-and-execute half of the smuggling pattern)

The default rule set ships 32 rules covering these signals across five file kinds, calibrated so that the same content scans differently depending on where it lives. A high-entropy base64 literal in .pth is CRITICAL (no benign use case); the same literal in __init__.py is MEDIUM (some packages legitimately ship encoded blobs); the same literal anywhere else is LOW (UUIDs and hashes happen). DENS021 is universally INFO because PEP-8-style confusables aren't a security finding by themselves; they only matter as a contributing signal when other signals fire.

Layered detection in practice

The LiteLLM 1.82.8 .pth payload is a single line:

import base64; exec(base64.b64decode('cHJpbnQoMSkK'))

A scanner that grepped for exec would catch it. A scanner that grepped for base64.b64decode would catch it. But an attacker who knew about either of those evasions could trivially defeat both. pydepgate fires five separate findings on this line from four independent analyzers:

• ENC001 (encoding_abuse): decode-then-execute pattern
• DYN002 (dynamic_execution): exec() with non-literal argument at module scope
• DENS001 (code_density): token-dense single line
• DENS010 (code_density): high-entropy string literal
• DENS011 (code_density): base64-alphabet string literal

Plus the rule layer promotes all of them to CRITICAL because the file is a .pth. To evade pydepgate, an attacker has to defeat every analyzer simultaneously while still producing a working .pth payload. Each evasion narrows what's possible; the intersection of all evasions is the empty set for any shape that could realistically execute on Python startup.

The rules engine

Analyzers emit raw signals. The rules engine maps signals to severity-rated findings using a data-driven rule set. Default rules ship in JSON; users can override or augment them with a pydepgate.gate file (TOML or JSON, auto-detected) in the project root, the venv root, or specified via --rules-file.

A rule is a small structured object:

{
  "id": "litellm-pth-stdlib",
  "match": {
    "signal_id": "STDLIB001",
    "file_kind": "pth"
  },
  "actions": [
    {"type": "set_severity", "severity": "critical"}
  ]
}

Three actions are supported: set_severity, suppress, and set_description. User rules always take precedence over default rules, regardless of specificity. Suppressed findings are tracked separately so users can see what would have fired and why it didn't.

Run pydepgate explain --list to see all default rules and signals, with descriptions of what they catch and how rules promote them.

Payload decoding

Some attacks bury their payload behind multiple decoding stages. Peek shows you what the first decoded layer looks like, but if that layer is itself Python source containing another encoded blob, peek treats it as a terminal and stops. The decode pass picks up where peek leaves off: it takes peek's decoded bytes, re-runs the analyzer engine over them, and recurses on any payload-bearing findings the inner scan turns up. The result is a tree mirroring the discovery path. Each node records what was decoded, what was found inside, and where the recursion stopped.

The pass is opt-in via --decode-payload-depth=N. It requires --peek (the decode driver consumes peek's output, so peek has to be running first). All flag values can be set via environment variables following the same precedence rules as the existing peek envvars; explicit flags override environment values.

Flag	Env var	Default	Notes
--decode-payload-depth N	PYDEPGATE_DECODE_PAYLOAD_DEPTH	3	Max recursion depth. Floor 1, ceiling 8. Requires --peek.
--decode-location PATH	PYDEPGATE_DECODE_LOCATION	./decoded/	Output DIRECTORY. Files inside follow the {STATUS}_{timestamp}_{target}{ext} naming convention; the directory is created if it does not exist.
--decode-format FMT	PYDEPGATE_DECODE_FORMAT	text	text for the human-readable tree report; json for a structured representation suitable for downstream tooling.
--decode-iocs MODE	PYDEPGATE_DECODE_IOCS	off	off, hashes, or full. See below for the full mode matrix.
--decode-archive-password PASSWORD	PYDEPGATE_DECODE_ARCHIVE_PASSWORD	infected	Password for the encrypted archive produced by --decode-iocs=full. The default infected is a malware-research convention recognized by AV vendors as a do-not-scan marker. ZipCrypto is cryptographically broken; this is not a confidentiality control.
--decode-archive-stored	(none)	off	Use STORED compression for the archive instead of DEFLATE. Produces a slightly larger archive but bypasses zlib entirely. Useful when byte-verifiable archive contents matter.

Output filename convention

All decode output files use a consistent naming pattern:

{STATUS}_{timestamp}_{target}{extension}

STATUS is FINDINGS when the decoded tree contains nodes, NOFINDINGS when it does not. timestamp is UTC, formatted YYYY-MM-DD_HH-MM-SS with no Z suffix; the format is sortable lexicographically and unambiguous about timezone. target is the basename of the artifact identity (e.g. the wheel filename), sanitized to [A-Za-z0-9._-] with leading separators stripped. extension is .txt for text output, .json for JSON output, .zip for the encrypted archive, or .iocs.txt for the plaintext IOC sidecar.

This convention preserves run history. Re-running the same command produces a new file with a new timestamp; the previous file is left untouched. Use ls -t <decode-location>/ to find the most recent output.

IOC mode matrix

The three modes of --decode-iocs produce different output shapes:

off (default). A single plaintext file containing only the tree report. No IOC hashes, no decoded source dumps, no archive. When the decoded tree is empty, no file is written; you get a stderr note instead. Useful for quick interactive triage.

hashes. Two plaintext files: the tree report (same as off mode) and a sidecar with the suffix .iocs.txt containing SHA256/SHA512 hashes of every decoded payload, along with the chain summary and location for each. Hash records use a fixed two-token line shape (decoded_sha256 <hex>) so a one-liner like grep '^decoded_sha256' iocs.txt | awk '{print $2}' extracts every hash for batch lookup. Skipped on empty trees, same as off mode.

full. An encrypted ZIP archive plus a plaintext IOC sidecar. The archive contains three files inside a subdirectory matching the sanitized target name:

<target>/report.txt    Tree report (same shape as off-mode output)
<target>/sources.txt   Per-layer decoded source dumps with header
                       blocks and line-numbered bodies
<target>/iocs.txt      Hash records (same content as the sidecar)

The sidecar lives next to the archive, NOT inside it, so you can batch-process IOC hashes without unzipping. Unlike off and hashes, full mode ALWAYS produces output: an empty tree results in a NOFINDINGS stub archive with the same structure but stub markers inside. This consistency lets downstream triage tooling rely on archive presence as a signal that the scan completed.

The bare form --decode-iocs (no value) is accepted as a deprecated synonym for --decode-iocs=hashes and emits a deprecation warning. Use the explicit form to avoid the warning.

--min-severity interaction

--min-severity is applied as a presentation filter AFTER decoding completes. The decode pass itself is NOT gated by severity, because a low-severity outer finding can decode to a critical inner one; gating at the input layer would skip the outer and lose the critical inner. The filter runs once on the resulting tree and applies a "keep for context" rule:

• A node is kept if its own severity meets the threshold, OR if any of its descendants do.
• Leaf child findings (the non-recursive ones) are filtered strictly: dropped if their own severity is below threshold, regardless of parent.

So a low-severity outer that decodes to a critical inner stays in the report, and the chain showing how you got from the outer to the critical inner is preserved. A low-severity outer whose descendants are all also low gets dropped.

Worked example

Scanning the LiteLLM 1.82.8 wheel with the full archive treatment:

pydepgate scan --deep litellm-1.82.8-py3-none-any.whl \
    --peek --peek-chain \
    --min-severity high \
    --decode-payload-depth=4 \
    --decode-iocs=full \
    --decode-location ./forensics \
    --decode-archive-password investigation

Produces in ./forensics/:

FINDINGS_2026-04-29_21-57-15_litellm-1.82.8-py3-none-any.whl.zip
FINDINGS_2026-04-29_21-57-15_litellm-1.82.8-py3-none-any.whl.iocs.txt

Verify and inspect:

unzip -P investigation -l ./forensics/FINDINGS_*.zip
# Should list: <target>/report.txt, <target>/sources.txt, <target>/iocs.txt
 
unzip -P investigation -d /tmp/extracted ./forensics/FINDINGS_*.zip
less /tmp/extracted/litellm-1.82.8-py3-none-any.whl/report.txt
 
# Quick hash extraction from the sidecar:
grep '^decoded_sha256' ./forensics/FINDINGS_*.iocs.txt | awk '{print $2}'

Safety guarantees

The decode pass inherits all the safety properties of the peek enricher (pickle detection without deserialization, decompression-bomb budgets, in-flight cap enforcement) and adds two more.

The encrypted archive is for AV-friendliness, not confidentiality. ZipCrypto is cryptographically broken (known plaintext attacks recover the password in seconds). The default password infected is the malware-research convention; AV vendors recognize archives with that password as do-not-scan and will not quarantine them mid-investigation. The encryption protects you from your own AV, not from any other adversary. Treat the archive contents as you would any malware sample.

The decode pass never executes decoded content. Re-scanning decoded bytes goes through the same engine path as scanning the original artifact, and that engine has been the same read-only analyzer pipeline since v0.1. Decoded Python source is parsed via ast.parse (no compile, no exec), and any signal-bearing literals inside it are themselves treated as data, not code, regardless of how many decode layers deep we are.

Writing rules

Rules live in pydepgate.gate files. The format is either TOML or JSON; pydepgate auto-detects from content. A rule has three parts: identity (an id), a match (which signals it applies to), and an action (what to do when matched).

Discovery

When you run pydepgate scan, rules are loaded from the first match of:

1. The --rules-file CLI flag, if given.
2. The PYDEPGATE_RULES_FILE environment variable.
3. ./pydepgate.gate in the current directory.
4. <venv>/pydepgate.gate in the active virtualenv, if any. If multiple files exist, only the first is loaded. The others are listed in the scan summary so you can see what was skipped.

Minimal rule (TOML)

[[rule]]
id = "my-package-uses-large-base64"
signal_id = "DENS010"
path_glob = "my_package/embedded/*.py"
action = "suppress"
explain = "We legitimately ship a 200KB embedded model in this dir."

The id is yours. signal_id is what to match (see pydepgate explain --list for the catalogue). path_glob is an fnmatch-style pattern matched against the internal path of the file. action is one of set_severity, suppress, or set_description. explain is optional but encouraged: it shows up in pydepgate explain --rule USER_my-package-uses-large-base64.

Match conditions

All non-empty match fields must be satisfied for a rule to apply. The supported fields:

Field	Matches against
signal_id	Signal.signal_id (e.g. "DENS010")
analyzer	Signal.analyzer (e.g. "code_density")
file_kind	The triage decision: pth, setup_py, init_py, sitecustomize, library_py, etc.
scope	Signal.scope: module, function, class
path_glob	fnmatch pattern against the file's internal path
context_contains	Dict of {key: value} pairs that must appear in Signal.context with strict equality
context_predicates	Dict of {key: {operator: value}} pairs evaluated against Signal.context (richer than context_contains, see below)

Context predicates

context_predicates extends context_contains with comparison operators. Each predicate takes the form {field: {op: value}}. The inner dict has exactly one operator key. Multiple predicates on different fields are AND-ed.

# Block any base64-shaped string of 10KB or larger anywhere
[[rule]]
id = "block-large-base64"
signal_id = "DENS010"
context_predicates = { length = { gte = 10240 } }
action = "set_severity"
severity = "critical"
 
# Suppress confusable single-char identifiers in test files only
[[rule]]
id = "ignore-confusables-in-tests"
signal_id = "DENS021"
path_glob = "tests/**/*.py"
context_predicates = { identifier = { in = ["l", "O", "I"] } }
action = "suppress"

Available operators:

Category	Operators	Value type
Numeric	eq, ne, gt, gte, lt, lte	int or float
String	eq, ne, contains, startswith, endswith	string
Collection	in, not_in	list, tuple, or set

Type mismatches (e.g. gte against a string) cause the predicate to silently fail to match rather than error. To AND multiple conditions on the same field, write multiple rules.

Equivalent JSON

{
  "_pydepgate_format": "json",
  "_pydepgate_version": 1,
  "rules": [
    {
      "id": "block-large-base64",
      "signal_id": "DENS010",
      "context_predicates": {"length": {"gte": 10240}},
      "action": "set_severity",
      "severity": "critical"
    }
  ]
}

Actions

• set_severity: requires a severity field (info, low, medium, high, critical).
• suppress: drop the finding from the scan output. The suppression is still recorded; pydepgate scan -v shows what was suppressed and which rule did it.
• set_description: requires a description field; replaces the finding's text.

Precedence

When multiple rules match a signal, pydepgate picks one winner using this order:

1. Source priority: user rules win over system rules win over defaults, regardless of specificity.
2. Specificity: among rules of the same source, more match fields wins. Each context_predicates entry counts as one match field.
3. Load order: among ties on source and specificity, the earlier rule wins. This means a user [[rule]] with the same shape as a default rule always wins. If you want your rule to lose to a more-specific default, add fewer match fields than the rule you want to override.

Validation

Rules are validated when loaded. Errors are accumulated and reported together; if any rule fails validation, the entire file is rejected (no rules loaded). Common errors:

• Unknown field name: Did you mean 'context_contains'?
• Unknown operator: Did you mean 'gte'?
• Multiple operators in one predicate: must be exactly one per field.
• Missing severity for set_severity action. Run pydepgate scan --rules-file my.gate once after editing to confirm everything parses.

Design constraints

• Zero runtime dependencies. Standard library only. This is a load-bearing design constraint, not a stylistic preference: every additional dependency is a supply-chain attack surface for a tool whose job is to defend against supply-chain attacks.
• Safe by construction. Parsers and the partial evaluator never execute, compile, or import input content. Every operation modeled by the resolver is reimplemented from scratch using only Python builtins on values the resolver itself produced.
• Self-integrity at bootstrap. Critical stdlib references are captured into locals before any untrusted code runs (relevant when the runtime engine ships in v0.4).
• Lightweight. The full test suite runs in roughly seven seconds on a modern laptop, including subprocess-based CLI tests against installed packages.

Relationship to PyDepGuard

pydepgate is a narrow, single-purpose tool focused on startup-vector interdiction. PyDepGuard is a broader Python security framework covering runtime sandboxing, and dependency management. The startup-vector engine developed in pydepgate is intended to eventually integrate with PyDepGuard as a subsystem; until then, the two projects are developed independently.

Users who need only startup-vector protection should use pydepgate. Users who need the full runtime security model should use PyDepGuard directly.

Architecture

The codebase is organized as a layered pipeline:

parsers/           bytes -> structured representations (pth, pysource, wheel, sdist)
introspection/     installed package enumeration via importlib.metadata
traffic_control/   path-based triage; decides what to analyze
analyzers/         structured representations -> raw signals
  _resolver.py        safe partial evaluator (shared infrastructure)
  _visitor.py         scope tracking and AST utilities (shared)
  encoding_abuse      ENC001
  dynamic_execution   DYN001-007
  string_ops          STR001-004
  suspicious_stdlib   STDLIB001-003
  density_analyzer    DENS001-051
enrichers/         signal hints -> enriched signal context
  _magic.py           magic-byte tables and ASCII-alphabet predicates
  _unwrap.py          bounded multi-layer decode/decompress loop
  payload_peek        ENC002 emission and decoded context block
rules/             signals + context -> severity-rated findings
  base.py             rule data model and matching logic
  defaults.py         default rule set (90+ rules across all signals)
  loader.py           TOML/JSON parser with validation and typo suggestions
  explanations.py     structured explain-output content
engines/           orchestration (currently: static)
visualizers/       inline rendering helpers for the human reporter
  density_map         SSH-randomart-style finding-distribution renderer
cli/               argparse, dispatch, reporters, explain subcommand

Analyzers do not see raw bytes. They walk parsed representations and emit Signal objects. The rules engine wraps signals with severity to produce Finding objects, applying user and default rules in priority order. The CLI renders findings in human, JSON, or SARIF format.

The _resolver.py module is reusable infrastructure for any analyzer that needs to know what an expression evaluates to. It returns structured ResolutionResult objects with success/failure status, operation counts, partial values, and resolved fragment lists.

The static engine exposes three entry points for single-file analysis. scan_file(path) reads bytes and routes through triage by filename. scan_bytes(content, internal_path, ...) is the per-file workhorse that artifact enumerators (wheel, sdist, installed) call once per in-scope file. scan_loose_file_as(path, file_kind) bypasses triage entirely and forces a file kind, preserving the real path through to finding contexts; this is the entry point used by pydepgate scan --single.

Development

git clone https://github.com/nuclear-treestump/pydep-vector-runner
cd pydep-vector-runner
pip install -e .
python -m unittest discover tests -v

The test suite has grown to approximately 500 tests as the analyzer set has expanded. Tests are organized by module and include happy-path coverage, evasion batteries, false-positive batteries, robustness checks against adversarial inputs, integration tests against synthetic wheels and sdists, and CLI tests via subprocess.

To regenerate the binary .pth test fixtures after editing them:

python scripts/generate_fixtures.py

Safety notes

This project builds tooling to defend against Python supply-chain attacks. The test fixtures in tests/fixtures/ and the synthetic samples used in integration tests model the structural shape of known attacks (LiteLLM 1.82.8, Trojan Source CVE-2021-42574, others catalogued under T1546.018) but contain only inert payloads. No actual malicious code is present in this repository.

For regression testing against real malicious samples, use the OSSF malicious-packages, Datadog malicious-software-packages-dataset, or lxyeternal/pypi_malregistry datasets. Do so in disposable VMs or containers, and do not commit samples to this repository.

Known limitations

pydepgate's static analysis is honest about what it can and cannot catch. Documented gaps include:

Analysis gaps:

• Function return tracking. code = make_payload() where make_payload() internally calls compile(...) is not flagged.
• __builtins__ as a Name subscript (rather than via a function call).
• Tuple unpacking, augmented assignment, and conditional assignments in the resolver's variable tracking.
• Lambda scope precision (lambdas count as their enclosing scope).
• Aliased stdlib imports such as from subprocess import Popen as P.
  • For now. I will add this soon enough.

Density-layer caveats:

• DENS020 (low-vowel-ratio identifiers) and DENS040 (AST depth) both produce false positives on legitimate machine-generated code (Cython output, parser tables, generated configuration). They ship at LOW severity outside startup vectors so they surface as contributing signals rather than standalone alerts.
• DENS031 (homoglyphs) can fire on legitimate non-English variable names in non-Latin codebases. The default rule keeps it at HIGH rather than CRITICAL outside startup vectors so users with intentional non-Latin naming can suppress with a single user rule.

Author

Ikari (@0xIkari)

License

Apache 2.0. See LICENSE.