github-evidence-kit
The GitHub Evidence Kit generates, stores, and verifies forensic evidence from GitHub API, local git repositories, GH Archive, Wayback Machine, and security vendor reports. Use it when creating verifiable evidence collections from GitHub activity, performing local git forensics on cloned repositories, exporting evidence to JSON for archival, recovering deleted GitHub content, or tracking indicators of compromise with source verification capabilities.
git clone --depth 1 https://github.com/deonmenezes/mantishack /tmp/github-evidence-kit && cp -r /tmp/github-evidence-kit/.claude/skills/oss-forensics/github-evidence-kit ~/.claude/skills/github-evidence-kitSKILL.md
# GH Evidence Kit
**Purpose**: Create, store, and verify forensic evidence from GitHub-related public sources and local git repositories.
## When to Use This Skill
- Creating verifiable evidence objects from GitHub activity
- **Local git forensics** - analyzing cloned repositories, dangling commits, reflog
- Exporting evidence collections to JSON for sharing/archival
- Loading and re-verifying previously collected evidence
- Recovering deleted GitHub content (issues, PRs, commits) from GH Archive
- Tracking IOCs (Indicators of Compromise) with source verification
## Quick Start
```python
from src.collectors import GitHubAPICollector, LocalGitCollector, GHArchiveCollector
from src import EvidenceStore
# Create collectors for different sources
github = GitHubAPICollector()
local = LocalGitCollector("/path/to/repo")
archive = GHArchiveCollector()
# Collect evidence from GitHub API
commit = github.collect_commit("aws", "aws-toolkit-vscode", "678851b...")
pr = github.collect_pull_request("aws", "aws-toolkit-vscode", 7710)
# Collect evidence from local git (first-class forensic source)
local_commit = local.collect_commit("HEAD")
dangling = local.collect_dangling_commits() # Forensic gold!
# Store and export
store = EvidenceStore()
store.add(commit)
store.add(pr)
store.add(local_commit)
store.add_all(dangling)
store.save("evidence.json")
# Verify all evidence against original sources
is_valid, errors = store.verify_all()
```
## Collectors
### GitHubAPICollector
Collects evidence from the live GitHub API.
```python
from src.collectors import GitHubAPICollector
collector = GitHubAPICollector()
```
| Method | Returns |
|--------|---------|
| `collect_commit(owner, repo, sha)` | CommitObservation |
| `collect_issue(owner, repo, number)` | IssueObservation |
| `collect_pull_request(owner, repo, number)` | IssueObservation |
| `collect_file(owner, repo, path, ref)` | FileObservation |
| `collect_branch(owner, repo, branch_name)` | BranchObservation |
| `collect_tag(owner, repo, tag_name)` | TagObservation |
| `collect_release(owner, repo, tag_name)` | ReleaseObservation |
| `collect_forks(owner, repo)` | list[ForkObservation] |
### LocalGitCollector (First-Class Forensics)
Collects evidence from local git repositories. Essential for forensic analysis of cloned repos.
```python
from src.collectors import LocalGitCollector
collector = LocalGitCollector("/path/to/cloned/repo")
# Collect a specific commit
commit = collector.collect_commit("HEAD")
commit = collector.collect_commit("abc123")
# Find dangling commits (not reachable from any ref)
# This is forensic gold - reveals force-pushed or deleted commits!
dangling = collector.collect_dangling_commits()
for commit in dangling:
print(f"Found dangling: {commit.sha[:8]} - {commit.message}")
```
| Method | Returns |
|--------|---------|
| `collect_commit(sha)` | CommitObservation |
| `collect_dangling_commits()` | list[CommitObservation] |
### GHArchiveCollector
Collects and recovers evidence from GH Archive (BigQuery). Requires credentials.
```python
from src.collectors import GHArchiveCollector
collector = GHArchiveCollector()
# Query events by timestamp (YYYYMMDDHHMM format)
events = collector.collect_events(
timestamp="202507132037",
repo="aws/aws-toolkit-vscode"
)
# Recover deleted content
deleted_issue = collector.recover_issue("aws/aws-toolkit-vscode", 123, "2025-07-13T20:30:24Z")
deleted_pr = collector.recover_pr("aws/aws-toolkit-vscode", 7710, "2025-07-13T20:30:24Z")
deleted_commit = collector.recover_commit("aws/aws-toolkit-vscode", "678851b", "2025-07-13T20:30:24Z")
force_pushed = collector.recover_force_push("aws/aws-toolkit-vscode", "2025-07-13T20:30:24Z")
```
| Method | Returns |
|--------|---------|
| `collect_events(timestamp, repo, actor, event_type)` | list[Event] |
| `recover_issue(repo, number, timestamp)` | IssueObservation |
| `recover_pr(repo, number, timestamp)` | IssueObservation |
| `recover_commit(repo, sha, timestamp)` | CommitObservation |
| `recover_force_push(repo, timestamp)` | CommitObservation |
### WaybackCollector
Collects archived snapshots from the Wayback Machine.
```python
from src.collectors import WaybackCollector
collector = WaybackCollector()
# Get all snapshots for a URL
snapshots = collector.collect_snapshots("https://github.com/owner/repo")
# With date filtering
snapshots = collector.collect_snapshots(
"https://github.com/owner/repo",
from_date="20250101",
to_date="20250731"
)
# Fetch actual content of a snapshot
content = collector.collect_snapshot_content(
"https://github.com/owner/repo",
"20250713203024" # YYYYMMDDHHMMSS format
)
```
## Verification
Verification is separated from data collection. Use `ConsistencyVerifier` to validate evidence against original sources.
```python
from src.verifiers import ConsistencyVerifier
verifier = ConsistencyVerifier()
# Verify single evidence
result = verifier.verify(commit)
if not result.is_valid:
print(f"Errors: {result.errors}")
# Verify multiple
result = verifier.verify_all([commit, pr, issue])
```
Or use the convenience method on `EvidenceStore`:
```python
store = EvidenceStore()
store.add_all([commit, pr, issue])
is_valid, errors = store.verify_all()
```
## EvidenceStore
Store, query, and export evidence collections.
```python
from src import EvidenceStore
from datetime import datetime
store = EvidenceStore()
# Add evidence
store.add(commit)
store.add_all([pr, issue, ioc])
# Query
commits = store.filter(observation_type="commit")
recent = store.filter(after=datetime(2025, 7, 1))
from_github = store.filter(source="github")
from_git = store.filter(source="git")
repo_events = store.filter(repo="aws/aws-toolkit-vscode")
# Export/Import
store.save("evidence.json")
store = EvidenceStore.load("evidence.json")
# Summary
print(store.summary())
# {'total': 5, 'events': {...}, 'observations': {...}, 'by_source': {...}}
# Verify all against sources
is_valid, errors = store.verify_all()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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