Function Call Tracing
This skill instruments C/C++ programs using compiler hooks to capture all function calls with per-thread logging and converts them to Chrome JSON format for visualization in Perfetto. Use it when you need detailed execution traces showing function call sequences, timing, and call depth across multiple threads in performance analysis or debugging scenarios.
git clone --depth 1 https://github.com/deonmenezes/mantishack /tmp/function-call-tracing && cp -r /tmp/function-call-tracing/.claude/skills/crash-analysis/function-tracing ~/.claude/skills/function-call-tracingSKILL.md
# Function Call Tracing
## Purpose
Trace all function calls in C/C++ programs with per-thread logs and Perfetto visualization.
## Components
### 1. Instrumentation Library (trace_instrument.c)
Captures function entry/exit, writes per-thread logs.
**Build:**
```bash
gcc -c -fPIC trace_instrument.c -o trace_instrument.o
gcc -shared trace_instrument.o -o libtrace.so -ldl -lpthread
```
### 2. Perfetto Converter (trace_to_perfetto.cpp)
Converts logs to Chrome JSON for Perfetto UI.
**Build:**
```bash
g++ -O3 -std=c++17 trace_to_perfetto.cpp -o trace_to_perfetto
```
## Usage
### Step 1: Add to Build
```makefile
CFLAGS += -finstrument-functions -g
LDFLAGS += -L. -ltrace -ldl -lpthread
```
### Step 2: Build Target
```bash
make
```
### Step 3: Run
```bash
export LD_LIBRARY_PATH=.:$LD_LIBRARY_PATH
./program
# Creates trace_<tid>.log files
```
### Step 4: Convert to Perfetto
```bash
./trace_to_perfetto trace_*.log -o trace.json
# Open trace.json in ui.perfetto.dev
```
## Log Format
```
[seq] [timestamp] [dots] [ENTRY|EXIT!] function_name
[0] [1.000000000] [ENTRY] main
[1] [1.000050000] . [ENTRY] helper
[2] [1.000100000] . [EXIT!] helper
[3] [1.000150000] [EXIT!] main
```
- Dots indicate call depth
- Timestamp in seconds.nanoseconds
- One log file per thread
## When User Requests Tracing
### Steps
1. Copy `trace_instrument.c` and `trace_to_perfetto.cpp` to project
2. Build instrumentation library
3. Add `-finstrument-functions` to CFLAGS
4. Add `-L. -ltrace -ldl -lpthread` to LDFLAGS
5. Build project
6. Set `LD_LIBRARY_PATH` and run
7. Convert logs: `./trace_to_perfetto trace_*.log -o trace.json`
8. Provide link to ui.perfetto.dev
### Build System Detection
**Makefile:** Add flags conditionally
```makefile
ENABLE_TRACE ?= 0
ifeq ($(ENABLE_TRACE),1)
CFLAGS += -finstrument-functions -g
LDFLAGS += -L. -ltrace -ldl -lpthread
endif
```
**CMake:** Add option
```cmake
option(ENABLE_TRACE "Enable tracing" OFF)
if(ENABLE_TRACE)
add_compile_options(-finstrument-functions -g)
link_libraries(trace dl pthread)
endif()
```
## Output
- **trace_<tid>.log**: Per-thread text logs
- **trace.json**: Perfetto Chrome JSON format
- View at https://ui.perfetto.dev
## Perfetto JSON Format
Function ENTRY → "B" (begin) event
Function EXIT! → "E" (end) event
All threads aligned by timestamp in single file.Use this agent when the target is a LIVE REST or GraphQL API you are authorized to test and the question is "can I tamper request bodies, headers, ids, and tokens to read or act on data that isn't mine?" — active, request-driven abuse of the API contract, not static code review. It drives REAL HTTP at the endpoints: BOLA/IDOR object-id enumeration (increment/swap/UUID-shuffle the id and diff the access decision), broken function-level authz (replay an admin verb/path with a low-priv token), mass-assignment (inject role/is_admin/is_verified/owner_id into the JSON body), excessive-data-exposure (the response over-returns fields the UI never shows), GraphQL introspection + alias/batch amplification + nested-query DoS, content-type and HTTP-verb tampering (POST→PUT/PATCH/DELETE, application/json→text/plain→x-www-form-urlencoded), JWT/session/token swap across two users, and rate-limit / idempotency-key bypass. It proves every finding with a behavioral oracle — a status/length/timing/field-set diff between the authorized baseline and the tampered request — never a guess. Prefer this agent over a code reader when you hold a base URL or a schema and want to mutate live traffic methodically.\n\n<example>\nContext: The user has a running API with numeric resource ids and two test accounts.\nuser: "Here's our staging API at https://api.staging.acme.test and tokens for user A and user B — can user A read user B's orders?"\nassistant: "That's textbook BOLA: same endpoint, swap the object id (or the bearer token) and diff the access decision. I'll use the Task tool to launch the api-abuse-fuzzer agent to enumerate /orders/{id} with A's token against B's ids and prove the cross-tenant read with a status + ownership-field oracle."\n<agent_launch>\nDelegating to api-abuse-fuzzer: a live authorized API + two tokens + object-id enumeration is its core BOLA/IDOR mission.\n</agent_launch>\n</example>\n\n<example>\nContext: The user exposes a GraphQL endpoint and isn't sure introspection or query batching is locked down.\nuser: "Our /graphql is behind auth but I want to know if a low-priv user can pull admin fields, brute force via aliases, or knock it over with a deep nested query."\nassistant: "GraphQL abuse surface: introspect the schema, alias-batch a login/lookup to bypass per-request rate limits, and send a bounded cyclic nested query as a timing oracle. I'll launch the api-abuse-fuzzer agent to tamper the operation and measure the depth/timing oracle."\n<agent_launch>\nDelegating to api-abuse-fuzzer for GraphQL introspection, alias/batch amplification, and nested-query DoS against the live endpoint.\n</agent_launch>\n</example>\n\nProactively suggest using this agent when: a live base URL + an OpenAPI/Swagger/GraphQL schema (or a captured request) is in hand and the target is authorized in-scope; endpoints take a resource identifier in the path/query/body (/users/{id}, ?account=, {"order_id": ...}) — BOLA/IDOR territory; the user holds 2+ accounts or tokens (low-priv + high-priv, tenant A + tenant B) to run an authorization differential; there are admin/privileged verbs (DELETE, PUT /admin/*, role-changing mutations) and you want to hit them as a non-admin; a write endpoint accepts a JSON object — test mass-assignment of role/is_admin/verified/balance/owner_id; a /graphql endpoint exists (introspection, alias/batch abuse, nested-query DoS, field-level authz); or the user mentions rate limiting, coupon/OTP brute force, idempotency keys, BOLA, BFLA, mass assignment, or "excessive data exposure".
Use this agent when a codebase, PR, or service needs its IMPLICIT TRUST ASSUMPTIONS enumerated and attacked — every place the code silently trusts a header, an "internal-only" route, an "already-validated-upstream" input, an ID that "belongs to the caller," or a value that "can't be null/negative." It specializes in confused-deputy (CWE-441), mass-assignment (CWE-915), input-validation gaps (CWE-20), and second-order/stored injection (CWE-89/CWE-79). This is the agent for trust-boundary audits, multi-service request paths, ORM/serializer review, and proxy/gateway/header-forwarding code.\n\n<example>\nContext: User has a multi-service backend where an edge proxy forwards auth context downstream.\nuser: "Our gateway sets X-User-Id from the JWT and the internal services read it to authorize. Can you check this?"\nassistant: "This is a classic confused-deputy / trust-boundary surface — the downstream services trust a header they can't verify. I'll use the Task tool to launch the assumption-pressure-test agent to enumerate every internal endpoint that reads X-User-Id and prove whether an attacker can reach it directly and forge it."\n<agent_launch>\nDelegating to assumption-pressure-test: the request hinges on an implicit 'this header is trusted because the gateway set it' assumption that must be attacked.\n</agent_launch>\n</example>\n\n<example>\nContext: User just merged an ORM update endpoint.\nuser: "Here's the new profile update handler: User.objects.filter(id=request.user.id).update(**request.data)"\nassistant: "That `**request.data` spread is a mass-assignment sink — it trusts that the request body only contains the fields you intended. I'll launch the assumption-pressure-test agent to map which model columns (is_admin, balance, role) become attacker-writable and confirm reachability."\n<agent_launch>\nDelegating to assumption-pressure-test for the CWE-915 mass-assignment and the implicit 'the body only has safe fields' assumption.\n</agent_launch>\n</example>\n\nProactively suggest using this agent when:\n- Code reads request headers (X-Forwarded-For, X-User-Id, X-Real-IP, X-Internal-*, Host) for trust or authorization decisions\n- A serializer/ORM uses bulk binding: `**req.body`, `Object.assign`, `ModelMapper`, `BeanUtils.copyProperties`, `update_attributes`, `params.permit!`\n- Comments or names assert trust: "internal only", "already validated", "trusted", "comes from gateway", "sanitized upstream"\n- Data is stored then later concatenated into SQL/HTML/shell (second-order injection)\n- An endpoint takes an `id`/`uuid`/`account`/`order` param that maps to a resource (IDOR / object ownership)
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