Trailmark
Trail of BitsOfficialPublished by Trail of Bits
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- Tool integration
- Security
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AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
Trailmark is a security-focused tool that parses source code and binaries into a directed graph of functions, classes, and calls. It provides deep visibility into complex, polyglot codebases by enabling structural traversal, call path analysis, and automated pre-analysis passes. These passes identify critical security indicators such as blast radius, privilege boundaries, and taint propagation paths. By integrating with SARIF and weAudit findings, Trailmark helps security engineers prioritize audit efforts, identify entry points, and understand the impact of potential vulnerabilities across language and RPC boundaries.
What it does
- Parses multi-language source code and binaries into a queryable directed graph.
- Performs automated pre-analysis to identify blast radius, taint propagation, and privilege boundaries.
- Enables complex graph queries for call paths, transitive slices, and entry point reachability.
- Supports cross-language and external link configuration via repository-level settings.
- Provides programmatic access to graph data, annotations, and structural metadata for custom security workflows.
- Imports external binary-analysis graphs to bridge the gap between source and binary security views.
When to use it
- When mapping attack surfaces and identifying entry points in unfamiliar or large codebases.
- When performing security audits and needing to prioritize high-complexity or high-blast-radius functions.
- When tracing potential taint flow from untrusted entry points to sensitive sinks.
- When analyzing call relationships across FFI, RPC, or multi-language boundaries.
- When preparing evidence packets for specific security findings or candidate vulnerabilities.
Advantages
- Provides a unified graph view across polyglot projects and binary boundaries.
- Automates the identification of high-risk areas through pre-analysis passes.
- Reduces manual effort in mapping complex call chains and attack surfaces.
- Allows for precise, programmatic security queries rather than relying on manual code reading.
- Integrates seamlessly with existing security reporting formats like SARIF.
Usage examples
- “Analyze the current directory for security hotspots and entry points.”
- The agent runs trailmark analyze --language auto, generates a summary, and identifies high-complexity functions and entry points for audit prioritization.
- “Find all call paths from user input to the sensitive function execute_query.”
- The agent uses engine.paths_between('handle_request', 'execute_query') to map and report the specific call chains.
- “Identify nodes that sit on a privilege boundary.”
- The agent runs engine.preanalysis() and retrieves the privilege_boundary subgraph to highlight trust transitions.
- “Check if a specific function is reachable from any untrusted entry point.”
- The agent queries the tainted subgraph or uses engine.entrypoint_paths_to() to determine if the function is exposed to untrusted input.
Install
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/trailofbits/trailmark/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip trailmark.zip -d .agents/skills
Documentation by Trail of Bits
Trailmark
Parses source code into a directed graph of functions, classes, calls, and semantic metadata for security analysis.
When to Use
Mapping call paths from user input to sensitive functions
Finding complexity hotspots for audit prioritization
Identifying attack surface and entrypoints
Understanding call relationships in unfamiliar codebases
Security review or audit preparation across polyglot projects
Adding LLM-inferred annotations (assumptions, preconditions) to code units
Importing external binary-analysis graphs to connect source and binary views
Querying transitive slices, entrypoint paths, subgraph edges, or type references
Producing graph evidence for one suspicious function or candidate finding
Pre-analysis before mutation testing (genotoxic skill) or diagramming
When NOT to Use
Single-file scripts where call graph adds no value (read the file directly)
Architecture diagrams not derived from code (use the
diagramming-codeskill or draw by hand)Mutation testing triage (use the genotoxic skill, which calls trailmark internally)
Runtime behavior analysis (trailmark is static, not dynamic)
Rationalizations to Reject
| Rationalization | Why It's Wrong | Required Action |
|---|---|---|
| "I'll just read the source files manually" | Manual reading misses call paths, blast radius, and taint data | Install trailmark and use the API |
| "Pre-analysis isn't needed for a quick query" | Blast radius, taint, and privilege data are only available after preanalysis() | Always run engine.preanalysis() before handing off to other skills |
| "The graph is too large, I'll sample" | Sampling misses cross-module attack paths | Build the full graph; use subgraph queries to focus |
| "Uncertain edges don't matter" | Dynamic dispatch is where type confusion bugs hide | Account for uncertain edges in security claims |
| "Single-language analysis is enough" | Polyglot repos have FFI boundaries where bugs cluster | Use the correct --language flag per component |
| "Complexity hotspots are the only thing worth checking" | Low-complexity functions on tainted paths are high-value targets | Combine complexity with taint and blast radius data |
| "The docs mention a version-gated method, so I can call it anywhere" | Many environments still have Trailmark 0.2.x installed | Check the installed version or probe feature availability before using v0.4+/v0.5+ features |
Installation
MANDATORY: If trailmark is not found, install the CLI before doing anything else:
uv tool install trailmarkA tool install provides the CLI only — it does not make import trailmark resolvable.
Run the Python snippets in this skill with uv run --with trailmark python -; that, not
installation, is the fix for an import error or ModuleNotFoundError in a snippet.
DO NOT fall back to "manual verification", "manual analysis", or reading source files by hand as a substitute for running trailmark. The tool must be installed and used programmatically. If installation fails, report the error to the user instead of silently switching to manual code reading.
Version Gate
Trailmark 0.4.0 expands the graph model and query surface, and 0.5.0 adds a SQL parser, repository-link configuration, and richer entrypoint metadata. Before using a feature listed as v0.4+ or v0.5+, check the installed version:
trailmark --version 2>/dev/null || uv run trailmark --version 2>/dev/nullCompare the reported version numerically (not lexically). 0.4.0 or newer
means the full v0.4 surface is available. The version command itself was added
in 0.2.2, so a failure means either a pre-0.2.2 install or trailmark missing
entirely — distinguish with trailmark analyze --help. When working
programmatically, probe with hasattr() and fall back instead of assuming a
v0.4-only method exists:
if hasattr(engine, "subgraph_edges"):
edges = engine.subgraph_edges("tainted")
else:
# v0.2 fallback: filter engine.to_json() edges whose endpoints
# are both in engine.subgraph("tainted")
edges = []v0.2-safe baseline: CLI analyze, diff, entrypoints, augment, and
--language auto; QueryEngine.from_directory(), callers_of(),
callees_of(), paths_between(), ancestors_of(), reachable_from(),
entrypoint_paths_to(), complexity_hotspots(), attack_surface(),
summary(), to_json(), preanalysis(), annotate(), annotations_of(),
nodes_with_annotation(), clear_annotations(), findings(), subgraph(),
subgraph_names(), diff_against(), augment_sarif(), and
augment_weaudit().
Added in 0.2.2: CLI --version flag and version subcommand.
Added in 0.3.x: the trailmark.parse module with module-level
detect_languages() and supported_languages(). detect_languages() itself
is v0.2-safe via from trailmark.query.api import detect_languages (kept as a
deprecated alias in 0.3+); supported_languages() has no 0.2.x equivalent.
v0.4+ features: native diagram subcommand; expanded parser coverage;
proxy nodes for unresolved calls; node origins; binary graph augmentation via
augment_binary(); connect_subgraphs(); subgraph_edges();
generic_parameters(); and type_references().
v0.5+ features: sql parser (PostgreSQL-oriented schemas, tables, views,
functions, procedures, dependencies); node kinds schema, table, view,
procedure; .trailmark/links.toml repository-link configuration (see
Repository Links below), including proxy.external:<symbol> nodes for
declared external endpoints; repository links, unresolved-call proxies, and
type_uses edges now materialize for single-language directory parses (0.4
emitted them only for polyglot parses); Solidity entrypoints detected from
parser metadata (interfaces excluded; solidity_visibility,
solidity_mutability, solidity_override, solidity_container_kind, and
solidity_overridden_by node attributes); attack_surface() entries carry an
attributes key when the node has attributes; TypeScript resolves receivers
assigned with new ConcreteClass(); C# file-scoped namespaces.
v0.5.0 adds no new QueryEngine methods, so hasattr(engine, ...) cannot
detect it. Gate v0.5 features on the reported version, or probe structurally:
from trailmark.models.nodes import NodeKind
has_v05 = "SCHEMA" in NodeKind.__members__ # sql kinds are 0.5+Quick Start
# Auto-detect and merge every supported language under the tree
uv run trailmark analyze --language auto --summary {targetDir}
# Explicit languages (single language or comma-separated list)
uv run trailmark analyze --language rust {targetDir}
uv run trailmark analyze --language python,rust {targetDir}
# Complexity hotspots
uv run trailmark analyze --language auto --complexity 10 {targetDir}
# Entrypoint inventory and structural diff (v0.2-safe)
uv run trailmark entrypoints --language auto {targetDir}
uv run trailmark diff --language auto --repo {repoDir} main HEAD --json
# Version report (0.2.2+)
uv run trailmark --version
# v0.4+: native diagram command
uv run trailmark diagram -t {targetDir} -T call-graph -f main --depth 2Programmatic API
# trailmark.parse is a 0.3+ module; on 0.2.x import detect_languages from
# trailmark.query.api instead (supported_languages has no 0.2.x equivalent)
from trailmark.parse import detect_languages, supported_languages
from trailmark.query.api import QueryEngine
# Ask the installed Trailmark build what it supports
supported_languages()
detect_languages("{targetDir}")
# Prefer auto for unknown or polyglot trees; use explicit lists when needed
engine = QueryEngine.from_directory("{targetDir}", language="auto")
engine = QueryEngine.from_directory("{targetDir}", language="python,rust")
engine.callers_of("function_name")
engine.callees_of("function_name")
engine.paths_between("entry_func", "db_query")
engine.complexity_hotspots(threshold=10)
engine.attack_surface()
engine.summary()
engine.to_json()
# Transitive slices and entrypoint path queries (v0.2-safe)
engine.ancestors_of("sensitive_sink")
engine.reachable_from("entry_func")
engine.entrypoint_paths_to("sensitive_sink")
# v0.4+: connect named subgraphs
if hasattr(engine, "connect_subgraphs"):
engine.connect_subgraphs("tainted", "privilege_boundary")
# Run pre-analysis (blast radius, entrypoints, privilege
# boundaries, taint propagation)
result = engine.preanalysis()
# Query subgraphs created by pre-analysis
engine.subgraph_names()
engine.subgraph("tainted")
engine.subgraph("high_blast_radius")
engine.subgraph("privilege_boundary")
engine.subgraph("entrypoint_reachable")
if hasattr(engine, "subgraph_edges"):
engine.subgraph_edges("tainted")
# Add LLM-inferred annotations
from trailmark.models import AnnotationKind
engine.annotate("function_name", AnnotationKind.ASSUMPTION,
"input is URL-encoded", source="llm")
# Query annotations (including pre-analysis results)
engine.annotations_of("function_name")
engine.annotations_of("function_name",
kind=AnnotationKind.BLAST_RADIUS)
engine.annotations_of("function_name",
kind=AnnotationKind.TAINT_PROPAGATION)
engine.nodes_with_annotation(AnnotationKind.FINDING)
engine.clear_annotations("function_name", kind=AnnotationKind.ASSUMPTION)
# v0.4+: generic/type-reference and binary augmentation APIs
if hasattr(engine, "generic_parameters"):
engine.generic_parameters("GenericTypeOrFunction")
if hasattr(engine, "type_references"):
engine.type_references("function_name")
if hasattr(engine, "augment_binary"):
engine.augment_binary("binary_graph.json")Pre-Analysis Passes
Always run engine.preanalysis() before handing off to the genotoxic
skill. (diagramming-code builds its own graph and does not use it.)
Pre-analysis enriches the graph with four passes:
Blast radius estimation — counts downstream and upstream nodes per function, identifies critical high-complexity descendants
Entry point enumeration — maps entrypoints by trust level, computes reachable node sets
Privilege boundary detection — finds call edges where trust levels change (untrusted -> trusted)
Taint propagation — marks all nodes reachable from untrusted entrypoints
Results are stored as annotations and named subgraphs on the graph.
For detailed documentation, see references/preanalysis-passes.md.
Language Selection
Do not hardcode a stale language table in downstream workflows. Ask the installed Trailmark build what it supports:
from trailmark.parse import detect_languages, supported_languages
supported_languages()
detect_languages("{targetDir}")CLI patterns:
# Auto-detect and merge
uv run trailmark analyze --language auto {targetDir}
# Explicit list for a known polyglot target
uv run trailmark analyze --language python,rust {targetDir}As of Trailmark 0.5.0, parser names include: python, javascript,
typescript, php, ruby, c, cpp, c_sharp, java, go, rust,
solidity, cairo, circom, haskell, erlang, masm, swift, objc,
kotlin, dart, move, tact, func, sway, rego, proto, thrift,
graphql, and sql (added in 0.5.0; PostgreSQL-oriented, .sql files).
Treat this list as documentation, not a source of truth; call
supported_languages() on the installed build before relying on a parser.
Repository Links (v0.5+)
Parsers cannot see cross-language calls (FFI, RPC, IPC, contract invocation)
or edges into external systems. Declare them in .trailmark/links.toml at the
analysis root and Trailmark materializes the edges on every parse — this is a
stable public configuration interface:
[[link]]
source = "backend:submit"
target = "contract:Verifier.verify"
kind = "calls" # any EdgeKind; defaults to calls
confidence = "certain" # certain | inferred | uncertain; defaults to inferred
description = "JSON-RPC eth_call"
[[link]]
source = "backend:notify"
target = "payments-webhook"
target_external = true # required because target is unresolvedEndpoint references may be exact node IDs or unique names/suffixes. Validation
fails closed: ambiguous references, unknown internal endpoints, invalid enum
values, and malformed TOML raise ValueError rather than silently weakening
the graph. source_external = true / target_external = true permit an
unresolved endpoint by creating a proxy.external:<symbol> node. Configured
edges carry a configured_by = .trailmark/links.toml attribute so they are
distinguishable from parser-derived edges.
Use this when the audit spans an FFI/RPC boundary the rationalization table warns about: declare the boundary edges first, then path and taint queries cross them like any other call edge.
Graph Model
Node kinds: function, method, class, module, struct,
interface, trait, enum, namespace, contract, library,
template; v0.4+ also materializes unresolved references as proxy
nodes; v0.5+ adds schema, table, view, and procedure for SQL
graphs.
Node origins: v0.4+ nodes may carry origin source, proxy,
binary, or synthetic. v0.2 exports may omit origin.
Edge kinds: calls, inherits, implements, contains, imports;
v0.4+ adds resolves_to, type_uses, specializes, and
corresponds_to.
Edge confidence: certain (direct call, self.method()), inferred
(attribute access on non-self object), uncertain (dynamic dispatch)
Per Code Unit
Parameters with types, return types, exception types
Cyclomatic complexity and branch metadata
Docstrings
Annotations:
assumption,precondition,postcondition,invariant,blast_radius,privilege_boundary,taint_propagation,finding,audit_note(last two set byaugment_sarif/augment_weaudit)
Per Edge
Source/target node IDs, edge kind, confidence level
Project Level
Dependencies (imported packages)
Entrypoints with trust levels and asset values
Named subgraphs (populated by pre-analysis)
Key Concepts
Declared contract vs. effective input domain: Trailmark separates what a function declares it accepts from what can actually reach it via call paths. Mismatches are where vulnerabilities hide:
Widening: Unconstrained data reaches a function that assumes validation
Safe by coincidence: No validation, but only safe callers exist today
Edge confidence: Dynamic dispatch produces uncertain edges. Account for
confidence when making security claims.
Proxy nodes (v0.4+): Unresolved calls are preserved as nodes such as
proxy.unresolved:<symbol>. Do not treat these as source code functions; use
them to identify resolution gaps, dynamic dispatch, external APIs, or binary
linkage candidates. v0.5+ also emits proxy.external:<symbol> nodes for
endpoints declared external in .trailmark/links.toml.
Reachability is not taint: entrypoint_paths_to() and the taint subgraph
answer different questions. Path queries report call-graph reachability;
preanalysis taint marks nodes reachable from untrusted entrypoints as a coarse
signal. Trailmark does not perform interprocedural taint analysis — do not
present either as proof that attacker-controlled data reaches a sink.
Binary augmentation (v0.4+): engine.augment_binary() imports an external
binary-analysis graph JSON file. Trailmark connects it to source nodes when
possible; it does not disassemble binaries itself.
Subgraphs: Named collections of node IDs produced by pre-analysis.
Query with engine.subgraph("name"). Available after engine.preanalysis().
Query Patterns
See references/query-patterns.md for common security analysis patterns.
See references/preanalysis-passes.md for pre-analysis pass documentation.
Use trailmark-finding-triage when the user has one concrete candidate
finding, SARIF result, weAudit annotation, suspicious function, or report
excerpt and needs a handoff-ready reachability and blast-radius evidence packet.
Use trailmark-variant-neighborhood after one seed issue is known and the user
needs graph-derived variant candidates for variant-analysis, Semgrep, CodeQL,
or manual review.
Files
- ATTRIBUTION.mdAdded by AutoGineer921 B
- LICENSELicence file added by AutoGineer19.7 KiB
- SKILL.md17.0 KiB
- agents/openai.yaml242 B
- assets/trail-of-bits-mark.svg3.0 KiB
- references/preanalysis-passes.md5.6 KiB
- references/query-patterns.md8.7 KiB
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Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Needs Python, Needs Node.js
Security
No issues found by our static scan· No issues found
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
Attribution and licence
- Published by
- Trail of Bits
- Publisher
- Trail of Bits (Official)
- Source
- trailofbits/skills · plugins/trailmark/skills/trailmark · commit e4dd0bb
- Licence
- Creative Commons Attribution-ShareAlike 4.0 International (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
AutoGineer is not affiliated with or endorsed by Trail of Bits.
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download trailmark.zip