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trailmark

Builds and queries multi-language source and binary code graphs for security analysis. Includes pre-analysis passes for blast radius, taint propagation, privilege boundaries, entry point enumeration, proxy/unresolved-call tracking, type/reference queries, structural traversal, graph diffs, audit augmentation, declared cross-language/FFI/external links via `.trailmark/links.toml`, and SQL schema graphs. Use when analyzing call paths, mapping attack surface, finding complexity hotspots, enumerating entry points, tracing taint propagation, measuring blast radius, importing SARIF/weAudit/binary findings, linking source graphs across language or RPC boundaries, or building a code graph for audit prioritization. Feature-gate version-specific Trailmark APIs before using them; prefer `trailmark.parse.detect_languages()` or `--language auto` when the target language is unknown or polyglot.

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trailmark
description
Builds and queries multi-language source and binary code graphs for security analysis. Includes pre-analysis passes for blast radius, taint propagation, privilege boundaries, entry point enumeration, proxy/unresolved-call tracking, type/reference queries, structural traversal, graph diffs, audit augmentation, declared cross-language/FFI/external links via `.trailmark/links.toml`, and SQL schema graphs. Use when analyzing call paths, mapping attack surface, finding complexity hotspots, enumerating entry points, tracing taint propagation, measuring blast radius, importing SARIF/weAudit/binary findings, linking source graphs across language or RPC boundaries, or building a code graph for audit prioritization. Feature-gate version-specific Trailmark APIs before using them; prefer `trailmark.parse.detect_languages()` or `--language auto` when the target language is unknown or polyglot.
# 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-code` skill 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: ```bash uv tool install trailmark ``` A 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: ```bash trailmark --version 2>/dev/null || uv run trailmark --version 2>/dev/null ``` Compare 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: ```python 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: ```python from trailmark.models.nodes import NodeKind has_v05 = "SCHEMA" in NodeKind.__members__ # sql kinds are 0.5+ ``` ## Quick Start ```bash # 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 2 ``` ### Programmatic API ```python # 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: 1. **Blast radius estimation** — counts downstream and upstream nodes per function, identifies critical high-complexity descendants 2. **Entry point enumeration** — maps entrypoints by trust level, computes reachable node sets 3. **Privilege boundary detection** — finds call edges where trust levels change (untrusted -> trusted) 4. **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](references/preanalysis-passes.md). ## Language Selection Do not hardcode a stale language table in downstream workflows. Ask the installed Trailmark build what it supports: ```python from trailmark.parse import detect_languages, supported_languages supported_languages() detect_languages("{targetDir}") ``` CLI patterns: ```bash # 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: ```toml [[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 unresolved ``` Endpoint 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`,
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